From 235e3846c949423f6cad43f178065628caa58d87 Mon Sep 17 00:00:00 2001 From: davidlmobley Date: Thu, 17 Nov 2016 11:28:36 -0800 Subject: [PATCH 1/5] Fix PDB code for n-phenylglycinonitrile --- README.md | 2 +- paper/benchmarkset.tex | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 33d2eac..a49c75d 100644 --- a/README.md +++ b/README.md @@ -60,7 +60,7 @@ We also welcome contributions to the material which is already here to extend it ## Contributors - David Slochower (UCSD): Grammar corrections and improved table formatting - +- Nascimento (in a comment on biorxiv): Highlighted PDB code error for n-phenylglycinonitrile ## Versions - [v1.0](https://github.com/MobleyLab/benchmarksets/releases/tag/v1.0): As posted to bioRxiv diff --git a/paper/benchmarkset.tex b/paper/benchmarkset.tex index 0590c39..8c3b52d 100644 --- a/paper/benchmarkset.tex +++ b/paper/benchmarkset.tex @@ -644,7 +644,7 @@ \subsubsection{The apolar and polar cavities and their ligands} 2-ethoxyphenol$^{\rm d}$ & 66755 & \parbox[c]{1em}{\includegraphics[scale=0.2]{figures/66755.pdf}} & CCOc1ccccc1O & -4.02\pm0.03 & 3HU8~\cite{boyce_predicting_2009} & \cite{boyce_predicting_2009} \\% relative set we did benzyl acetate$^{\rm e, f}$ & 8785 & \parbox[c]{1em}{\includegraphics[scale=0.2]{figures/8785.pdf}} & CC(=O)OCc1ccccc1 & -4.48\pm0.16 & 3HUK~\cite{boyce_predicting_2009} & \cite{boyce_predicting_2009} \\ %induces helix motions 4,5,6,7-tetrahydroindole$^{\rm f}$ & 57452536 & \parbox[c]{1em}{\includegraphics[scale=0.2]{figures/57452536.pdf}} & c1c[nH]c2c1CCCC2 & -4.61\pm0.09 & 3HUA~\cite{boyce_predicting_2009} & \cite{boyce_predicting_2009} \\ % induces helix motion -n-phenylglycinonitrile$^{\rm g}$ & 76372 & \parbox[c]{1em}{\includegraphics[scale=0.2]{figures/76372.pdf}} & c1ccccc1NCC\#N & -5.52\pm0.18 & 2RBO~\cite{boyce_predicting_2009} & \cite{boyce_predicting_2009} \\ +n-phenylglycinonitrile$^{\rm g}$ & 76372 & \parbox[c]{1em}{\includegraphics[scale=0.2]{figures/76372.pdf}} & c1ccccc1NCC\#N & -5.52\pm0.18 & 2RBN~\cite{boyce_predicting_2009} & \cite{boyce_predicting_2009} \\ 3-chlorophenol & 7933 & \parbox[c]{1em}{\includegraphics[scale=0.2]{figures/7933.pdf}} & c1cc(cc(c1)Cl)O & -5.51 & 1LI3~\cite{wei_model_2002} & \cite{wei_model_2002} \\ 2-methoxyphenol & 460 & \parbox[c]{1em}{\includegraphics[scale=0.2]{figures/460.pdf}} & COc1ccccc1O & {NB$^{\rm i}$} & ND$^{\rm c}$ & \cite{boyce_predicting_2009} \\ % relative set 4-vinylpyridine & 7502 & \parbox[c]{1em}{\includegraphics[scale=0.2]{figures/7502.pdf}} & C=Cc1ccncc1 & {NB$^{\rm i}$} & ND$^{\rm c}$ & \cite{wei_model_2002} \\ From eb990c9c9d35a4f25cf634899350fb9ba28ed82f Mon Sep 17 00:00:00 2001 From: davidlmobley Date: Thu, 17 Nov 2016 11:56:40 -0800 Subject: [PATCH 2/5] Add Abel reference; fix some cite keys which had changed. --- paper/benchmarkset.bib | 251 +++++++++++++++++++++++------------------ paper/benchmarkset.tex | 29 ++--- 2 files changed, 156 insertions(+), 124 deletions(-) diff --git a/paper/benchmarkset.bib b/paper/benchmarkset.bib index d75df37..a748e31 100644 --- a/paper/benchmarkset.bib +++ b/paper/benchmarkset.bib @@ -1,9 +1,9 @@ @article{sherborne_preprint_2016, title = {Opening the Lid on {{FEP}}}, - timestamp = {2016-07-21T17:58:46Z}, + timestamp = {2016-09-27T19:55:36Z}, journal = {J Comput Aided Mol Des}, - author = {{Sherborne, Bradley}}, + author = {Sherborne, Bradley}, year = {2016}, file = {Opening the lid on FEP v1.docx:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/9X6N7IRE/Opening the lid on FEP v1.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document} } @@ -27,16 +27,6 @@ @article{henriksen_computational_2015 file = {b00405.pdf:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/83KZV5MM/b00405.pdf:application/pdf} } -@article{yin_sampl5_preprint, - title = {Overview of the {{SAMPL5 Host}}-{{Guest Challenge}}: {{Are We Doing Better}}?}, - timestamp = {2016-09-01T18:53:18Z}, - journal = {J Comput Aided Mol Des}, - author = {Yin, Jian and Henriksen, Niel M. and Slochower, David R. and Chiu, Michael W. and Mobley, David L. and Gilson, Michael K.}, - year = {2016}, - keywords = {alchemical,host–guest complexation,OctaAcid}, - file = {JCAM-D-16-00196-no-preamble.pdf:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/F3NIHBQ2/JCAM-D-16-00196-no-preamble.pdf:application/pdf} -} - @article{monroe_converging_2014, title = {Converging Free Energies of Binding in cucurbit[7]uril and Octa-Acid Host\textendash{}guest Systems from {{SAMPL4}} Using Expanded Ensemble Simulations}, volume = {28}, @@ -51,7 +41,7 @@ @article{monroe_converging_2014 author = {Monroe, Jacob I. and Shirts, Michael R.}, month = mar, year = {2014}, - keywords = {alchemical,CB7,host–guest complexation,OctaAcid,SAMPL4}, + keywords = {alchemical,CB7,host–guest complexation,OctaAcid,SAMPL,SAMPL4}, pages = {401--415}, file = {Full Text PDF:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/NRVQCRED/Monroe and Shirts - 2014 - Converging free energies of binding in cucurbit[7].pdf:application/pdf;Snapshot:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/Q76K952R/s10822-014-9716-4.html:text/html} } @@ -77,10 +67,10 @@ @article{fenley_bridging_2014 @article{wickstrom_parameterization_2016, title = {Parameterization of an Effective Potential for Protein\textendash{}ligand Binding from Host\textendash{}guest Affinity Data}, volume = {29}, - copyright = {Copyright \textcopyright 2015 John Wiley \& Sons, Ltd.}, + copyright = {Copyright \textcopyright{} 2015 John Wiley \& Sons, Ltd.}, issn = {1099-1352}, doi = {10.1002/jmr.2489}, - abstract = {Force field accuracy is still one of the ``stalemates'' in biomolecular modeling. Model systems with high quality experimental data are valuable instruments for the validation and improvement of effective potentials. With respect to protein\textendash{}ligand binding, organic host\textendash{}guest complexes have long served as models for both experimental and computational studies because of the abundance of binding affinity data available for such systems. Binding affinity data collected for cyclodextrin (CD) inclusion complexes, a popular model for molecular recognition, is potentially a more reliable resource for tuning energy parameters than hydration free energy measurements. Convergence of binding free energy calculations on CD host\textendash{}guest systems can also be obtained rapidly, thus offering the opportunity to assess the robustness of these parameters. In this work, we demonstrate how implicit solvent parameters can be developed using binding affinity experimental data and the binding energy distribution analysis method (BEDAM) and validated using the Grid Inhomogeneous Solvation Theory analysis. These new solvation parameters were used to study protein\textendash{}ligand binding in two drug targets against the HIV-1 virus and improved the agreement between the calculated and the experimental binding affinities. This work illustrates how benchmark sets of high quality experimental binding affinity data and physics-based binding free energy models can be used to evaluate and optimize force fields for protein\textendash{}ligand systems. Copyright \textcopyright 2015 John Wiley \& Sons, Ltd.}, + abstract = {Force field accuracy is still one of the ``stalemates'' in biomolecular modeling. Model systems with high quality experimental data are valuable instruments for the validation and improvement of effective potentials. With respect to protein\textendash{}ligand binding, organic host\textendash{}guest complexes have long served as models for both experimental and computational studies because of the abundance of binding affinity data available for such systems. Binding affinity data collected for cyclodextrin (CD) inclusion complexes, a popular model for molecular recognition, is potentially a more reliable resource for tuning energy parameters than hydration free energy measurements. Convergence of binding free energy calculations on CD host\textendash{}guest systems can also be obtained rapidly, thus offering the opportunity to assess the robustness of these parameters. In this work, we demonstrate how implicit solvent parameters can be developed using binding affinity experimental data and the binding energy distribution analysis method (BEDAM) and validated using the Grid Inhomogeneous Solvation Theory analysis. These new solvation parameters were used to study protein\textendash{}ligand binding in two drug targets against the HIV-1 virus and improved the agreement between the calculated and the experimental binding affinities. This work illustrates how benchmark sets of high quality experimental binding affinity data and physics-based binding free energy models can be used to evaluate and optimize force fields for protein\textendash{}ligand systems. Copyright \textcopyright{} 2015 John Wiley \& Sons, Ltd.}, language = {en}, timestamp = {2016-07-21T18:32:55Z}, number = {1}, @@ -126,7 +116,7 @@ @article{muddana_blind_2014 author = {Muddana, Hari S. and Yin, Jian and Sapra, Neil V. and Fenley, Andrew T. and Gilson, Michael K.}, month = feb, year = {2014}, - keywords = {alchemical,CB7,cucurbituril,host–guest complexation,SAMPL4}, + keywords = {alchemical,CB7,cucurbituril,host–guest complexation,SAMPL,SAMPL4}, pages = {463--474}, file = {Full Text PDF:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/P4GC5C8T/Muddana et al. - 2014 - Blind prediction of SAMPL4 cucurbit[7]uril binding.pdf:application/pdf;Snapshot:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/FUMU345G/s10822-014-9726-2.html:text/html} } @@ -244,13 +234,13 @@ @article{gilson_stress_2010 } @article{moghaddam_hostguest_2009, - title = {{{Host}}-{{Guest Complexes}} with {{Protein}}-{{Ligand}}-like {{Affinities}}: {{Computational Analysis}} and {{Design}}}, + title = {{{Host}}-guest Complexes with Protein-ligand-like Affinities: {{Computational}} Analysis and Design}, volume = {131}, issn = {0002-7863, 1520-5126}, shorttitle = {{{Host}}-{{Guest Complexes}} with {{Protein}}-{{Ligand}}-like {{Affinities}}}, doi = {10.1021/ja808175m}, language = {en}, - timestamp = {2016-07-28T20:18:03Z}, + timestamp = {2016-10-13T22:28:42Z}, number = {11}, urldate = {2016-07-28}, journal = {Journal of the American Chemical Society}, @@ -315,7 +305,7 @@ @article{gao_binding_2015 file = {acs%2Ejctc%2E5b00676.pdf:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/F4NVWD9F/acs%2Ejctc%2E5b00676.pdf:application/pdf} } -@article{isaacs_cucurbit[n]urils:_2009, +@article{Isaacs:2009:Chem.Commun., title = {Cucurbit[n]urils: From Mechanism to Structure and Function}, issn = {1359-7345, 1364-548X}, shorttitle = {Cucurbit[n]urils}, @@ -364,7 +354,7 @@ @article{cao_absolute_2014 author = {Cao, Liping and Isaacs, Lyle}, month = mar, year = {2014}, - keywords = {CB7,cucurbituril,experiment,host–guest complexation,SAMPL4}, + keywords = {CB7,cucurbituril,experiment,host–guest complexation,SAMPL,SAMPL4}, pages = {251--258}, file = {Full Text PDF:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/AMSNNXHI/Cao and Isaacs - 2014 - Absolute and relative binding affinity of cucurbit.pdf:application/pdf;Snapshot:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/2NNAUM4M/10610278.2013.html:text/html} } @@ -384,13 +374,13 @@ @article{muddana_prediction_2012 author = {Muddana, Hari S. and Gilson, Michael K.}, month = jan, year = {2012}, - keywords = {CB7,Free energy,host–guest complexation,SAMPL3}, + keywords = {CB7,Free energy,host–guest complexation,SAMPL,SAMPL3}, pages = {517--525}, file = {Full Text PDF:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/ZJD6SRS8/Muddana and Gilson - 2012 - Prediction of SAMPL3 host–guest binding affinities.pdf:application/pdf;Snapshot:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/H83HPWZG/fulltext.html:text/html} } @misc{schreiner_theoretical_2016, - title = {Theoretical Prediction of Affinities to Cucurbiturils \textendash the Blind Prediction Hydrophobe Challenge}, + title = {Theoretical Prediction of Affinities to Cucurbiturils \textendash{} the Blind Prediction Hydrophobe Challenge}, timestamp = {2016-09-01T18:53:37Z}, urldate = {2016-08-02}, howpublished = {\url{https://www.uni-giessen.de/fbz/fb08/dispersion/projects/HydrophobeChallenge}}, @@ -450,7 +440,7 @@ @article{gallicchio_bedam_2015-1 author = {Gallicchio, Emilio and Chen, Haoyuan and Chen, He and Fitzgerald, Michael and Gao, Yang and He, Peng and Kalyanikar, Malathi and Kao, Chuan and Lu, Beidi and Niu, Yijie and Pethe, Manasi and Zhu, Jie and Levy, Ronald M.}, month = mar, year = {2015}, - keywords = {binding free energy,host–guest complexation,implicit solvent,OctaAcid,SAMPL4}, + keywords = {BEDAM,binding free energy,host–guest complexation,implicit solvent,OctaAcid,SAMPL,SAMPL4}, pages = {315--325}, file = {Full Text PDF:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/43VF6CMD/Gallicchio et al. - 2015 - BEDAM binding free energy predictions for the SAMP.pdf:application/pdf;Snapshot:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/PBD7BWDV/s10822-014-9795-2.html:text/html} } @@ -506,7 +496,7 @@ @article{mikulskis_free-energy_2014 author = {Mikulskis, Paulius and Cioloboc, Daniela and Andreji{\'c}, Milica and Khare, Sakshi and Brorsson, Joakim and Genheden, Samuel and Mata, Ricardo A. and S{\"o}derhjelm, P{\"a}r and Ryde, Ulf}, month = apr, year = {2014}, - keywords = {host–guest complexation,OctaAcid,SAMPL4}, + keywords = {alchemical,host–guest complexation,OctaAcid,SAMPL,SAMPL4}, pages = {375--400}, file = {Full Text PDF:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/26ITGVPJ/Mikulskis et al. - 2014 - Free-energy perturbation and quantum mechanical st.pdf:application/pdf;Snapshot:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/ET79ZEFJ/10.html:text/html} } @@ -530,7 +520,7 @@ @article{gibb_guests_2009 file = {ScienceDirect Full Text PDF:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/4FMWUMN7/Gibb and Gibb - 2009 - Guests of differing polarities provide insight int.pdf:application/pdf;ScienceDirect Snapshot:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/7XEX4GWD/S0040402009001744.html:text/html} } -@article{xi_deep-cavity_1998, +@article{Xi:1998:Chem.Commun., title = {Deep-Cavity Cavitands: Synthesis and Solid State Structure of Host Molecules Possessing Large Bowl-Shaped Cavities}, issn = {1364-548X}, shorttitle = {Deep-Cavity Cavitands}, @@ -590,7 +580,7 @@ @article{gibb_binding_2013 volume = {28}, issn = {0920-654X, 1573-4951}, doi = {10.1007/s10822-013-9690-2}, - abstract = {As part of the fourth statistical assessment of modeling of proteins and ligands (sampl.eyesopen.com) prediction challenge, the strength of association of nine guests (1\textendash{}9) binding to octa-acid host was determined by a combination of 1H NMR and isothermal titration calorimetry. Association constants in sodium tetraborate buffered (pH 9.2) aqueous solution ranged from 5.39 \texttimes 102 M-1 in the case of benzoate 1, up to 3.82 \texttimes 105 M-1 for trans-4-methylcyclohexanoate 7. Overall, the free energy difference between the free energies of complexation of these weakest and strongest binding guests was $\Delta\Delta$G$^\circ$ = 3.88 kcal mol-1. Based on a multitude of previous studies, the anticipated order of strength of binding was close to that which was actually obtained. However, the binding of guest 3 (4-ethylbenzoate) was considerably stronger than initially estimated.}, + abstract = {As part of the fourth statistical assessment of modeling of proteins and ligands (sampl.eyesopen.com) prediction challenge, the strength of association of nine guests (1\textendash{}9) binding to octa-acid host was determined by a combination of 1H NMR and isothermal titration calorimetry. Association constants in sodium tetraborate buffered (pH 9.2) aqueous solution ranged from 5.39 \texttimes{} 102 M-1 in the case of benzoate 1, up to 3.82 \texttimes{} 105 M-1 for trans-4-methylcyclohexanoate 7. Overall, the free energy difference between the free energies of complexation of these weakest and strongest binding guests was $\Delta\Delta$G$^\circ$ = 3.88 kcal mol-1. Based on a multitude of previous studies, the anticipated order of strength of binding was close to that which was actually obtained. However, the binding of guest 3 (4-ethylbenzoate) was considerably stronger than initially estimated.}, language = {en}, timestamp = {2016-08-11T22:21:33Z}, number = {4}, @@ -599,7 +589,7 @@ @article{gibb_binding_2013 author = {Gibb, Corinne L. D. and Gibb, Bruce C.}, month = nov, year = {2013}, - keywords = {experiment,host–guest complexation,OctaAcid,SAMPL4}, + keywords = {experiment,host–guest complexation,OctaAcid,SAMPL,SAMPL4}, pages = {319--325}, file = {Full Text PDF:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/37DJAJ5Q/Gibb and Gibb - 2013 - Binding of cyclic carboxylates to octa-acid deep-c.pdf:application/pdf;Snapshot:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/IK59HCQR/10.html:text/html} } @@ -618,7 +608,7 @@ @article{hsiao_prediction_2014 author = {Hsiao, Ya-Wen and S{\"o}derhjelm, P{\"a}r}, month = feb, year = {2014}, - keywords = {binding free energy,CB7,host–guest complexation,metadynamics,SAMPL4}, + keywords = {binding free energy,CB7,host–guest complexation,metadynamics,SAMPL,SAMPL4}, pages = {443--454}, file = {Full Text PDF:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/SIHP3AD8/Hsiao and Söderhjelm - 2014 - Prediction of SAMPL4 host–guest binding affinities.pdf:application/pdf;Snapshot:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/J7DCAE3Z/10.html:text/html} } @@ -629,7 +619,7 @@ @article{bhakat_resolving_2016 journal = {J Comput Aided Mol Des}, author = {Bhakat, Soumendranath and S{\"o}derhjelm, P{\"a}r}, year = {2016}, - keywords = {binding free energy,host–guest complexation,metadynamics,OctaAcid,SAMPL5}, + keywords = {binding free energy,host–guest complexation,metadynamics,OctaAcid,SAMPL,SAMPL5}, file = {JCAM-D-16-00194.pdf:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/5PBMP7HI/JCAM-D-16-00194.pdf:application/pdf} } @@ -639,7 +629,7 @@ @article{pal_combined_2016 journal = {Journal of Computer-Aided Molecular Design}, author = {Pal, Rajat Kumar and Haider, Kamran and Kaur, Divya and Flynn, William and Xia, Junchao and Levy, Ronald M. and Taran, Tetiana and Wickstrom, Lauren and Kurtzman, Tom and Gallicchio, Emilio}, year = {2016}, - keywords = {binding free energy,host–guest complexation,OctaAcid,SAMPL5}, + keywords = {alchemical,BEDAM,binding free energy,host–guest complexation,OctaAcid,SAMPL,SAMPL5}, file = {JCAM-D-16-00173 (1).pdf:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/7V2PUB89/JCAM-D-16-00173 (1).pdf:application/pdf} } @@ -649,7 +639,7 @@ @article{yin_sampl5_2016 journal = {J Comput Aided Mol Des}, author = {Yin, Jian and Henriksen, Niel M. and Slochower, David R. and Gilson, Michael K.}, year = {2016}, - keywords = {alchemical,binding free energy,host–guest complexation,SAMPL5}, + keywords = {alchemical,binding free energy,host–guest complexation,SAMPL,SAMPL5}, file = {JCAM-D-16-00203 (1).pdf:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/AZI7FQNU/JCAM-D-16-00203 (1).pdf:application/pdf} } @@ -659,7 +649,7 @@ @article{bosisio_blinded_2016 journal = {J Comput Aided Mol Des}, author = {Bosisio, Stefano and Mey, Antonia S. J. S. and Michel, Julien}, year = {2016}, - keywords = {alchemical,binding free energy,CBClip,host–guest complexation,OctaAcid,SAMPL5,standard binding free energy,standard state}, + keywords = {alchemical,binding free energy,CBClip,host–guest complexation,OctaAcid,SAMPL,SAMPL5,standard binding free energy,standard state}, file = {JCAM-D-16-00176_R1 (1).pdf:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/VP99HX8Q/JCAM-D-16-00176_R1 (1).pdf:application/pdf} } @@ -684,9 +674,9 @@ @article{tofoleanu_absolute_2016 title = {Absolute Binding Free Energy Calculations for Octa-Acids and Guests}, timestamp = {2016-08-13T20:49:54Z}, journal = {J Comput Aided Mol Des}, - author = {Tofoleanu, Florentina and Lee, Juyong and {Pickard IV.}, Frank C. and K{\"o}nig, Gerhard and Huang, Jing and Baek, Minkyung and Seok, Chaok and Brooks, Bernard R.}, + author = {Tofoleanu, Florentina and Lee, Juyong and Pickard IV., Frank C. and K{\"o}nig, Gerhard and Huang, Jing and Baek, Minkyung and Seok, Chaok and Brooks, Bernard R.}, year = {2016}, - keywords = {absolute binding free energy,alchemical,host–guest complexation,OAMe,OctaAcid,SAMPL5}, + keywords = {absolute binding free energy,alchemical,host–guest complexation,OAMe,OctaAcid,SAMPL,SAMPL5}, file = {JCAM-D-16-00189.pdf:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/MGTCD94A/JCAM-D-16-00189.pdf:application/pdf} } @@ -774,7 +764,8 @@ @article{lim_sensitivity_2016 journal = {Journal of Chemical Theory and Computation}, author = {Lim, Nathan M. and Wang, Lingle and Abel, Robert and Mobley, David L}, month = jul, - year = {2016} + year = {2016}, + file = {acs%2Ejctc%2E6b00532.pdf:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/SVUZNG5Q/acs%2Ejctc%2E6b00532.pdf:application/pdf} } @article{wang_achieving_2012, @@ -950,7 +941,7 @@ @article{wei_model_2002 issn = {0022-2836}, doi = {10.1016/S0022-2836(02)00777-5}, abstract = {Prediction of interaction energies between ligands and their receptors remains a major challenge for structure-based inhibitor discovery. Much effort has been devoted to developing scoring schemes that can successfully rank the affinities of a diverse set of possible ligands to a binding site for which the structure is known. To test these scoring functions, well-characterized experimental systems can be very useful. Here, mutation-created binding sites in T4 lysozyme were used to investigate how the quality of atomic charges and solvation energies affects molecular docking. Atomic charges and solvation energies were calculated for 172,118 molecules in the Available Chemicals Directory using a semi-empirical quantum mechanical approach by the program AMSOL\textdagger\textdagger{}http://t1.chem.umn.edu/amsol -. The database was first screened against the apolar cavity site created by the mutation Leu99$\rightarrow$Ala (L99A). Compared to the electronegativity-based charges that are widely used, the new charges and desolvation energies improved ranking of known apolar ligands, and better distinguished them from more polar isosteres that are not observed to bind. To investigate whether the new charges had predictive value, the non-polar residue Met102, which forms part of the binding site, was changed to the polar residue glutamine. The structure of the resulting Leu99$\rightarrow$Ala and Met102$\rightarrow$Gln double mutant of T4 lysozyme (L99A/M102Q) was determined and the docking calculation was repeated for the new site. Seven representative polar molecules that preferentially docked to the polar versus the apolar binding site were tested experimentally. All seven bind to the polar cavity (L99A/M102Q) but do not detectably bind to the apolar cavity (L99A). Five ligand-bound structures of L99A/M102Q were determined by X-ray crystallography. Docking predictions corresponded to the crystallographic results to within 0.4 \AA RMSD. Improved treatment of partial atomic charges and desolvation energies in database docking appears feasible and leads to better distinction of true ligands. Simple model binding sites, such as L99A and its more polar variants, may find broad use in the development and testing of docking algorithms.}, +. The database was first screened against the apolar cavity site created by the mutation Leu99$\rightarrow$Ala (L99A). Compared to the electronegativity-based charges that are widely used, the new charges and desolvation energies improved ranking of known apolar ligands, and better distinguished them from more polar isosteres that are not observed to bind. To investigate whether the new charges had predictive value, the non-polar residue Met102, which forms part of the binding site, was changed to the polar residue glutamine. The structure of the resulting Leu99$\rightarrow$Ala and Met102$\rightarrow$Gln double mutant of T4 lysozyme (L99A/M102Q) was determined and the docking calculation was repeated for the new site. Seven representative polar molecules that preferentially docked to the polar versus the apolar binding site were tested experimentally. All seven bind to the polar cavity (L99A/M102Q) but do not detectably bind to the apolar cavity (L99A). Five ligand-bound structures of L99A/M102Q were determined by X-ray crystallography. Docking predictions corresponded to the crystallographic results to within 0.4 \AA{} RMSD. Improved treatment of partial atomic charges and desolvation energies in database docking appears feasible and leads to better distinction of true ligands. Simple model binding sites, such as L99A and its more polar variants, may find broad use in the development and testing of docking algorithms.}, timestamp = {2016-08-15T19:06:59Z}, number = {2}, urldate = {2016-08-15}, @@ -1166,7 +1157,7 @@ @article{muddana_sampl4_2014 author = {Muddana, Hari S and Fenley, Andrew T and Mobley, David L and Gilson, Michael K}, month = mar, year = {2014}, - keywords = {alchemical,CB7,cucurbituril,host–guest complexation,OctaAcid,SAMPL4}, + keywords = {alchemical,CB7,cucurbituril,host–guest complexation,OctaAcid,overview,SAMPL,SAMPL4}, pages = {305--317}, file = {Muddana_2014-J Comput Aided Mol Des:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/FG5FXVAS/Muddana_2014-J Comput Aided Mol Des.pdf:application/pdf;Muddana_2014-J Comput Aided Mol Des:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/QAVCZ38I/Muddana_2014-J Comput Aided Mol Des.pdf:application/pdf} } @@ -1176,7 +1167,7 @@ @article{reif_net_2014 volume = {35}, issn = {1096-987X}, doi = {10.1002/jcc.23490}, - abstract = {The calculation of binding free energies of charged species to a target molecule is a frequently encountered problem in molecular dynamics studies of (bio-)chemical thermodynamics. Many important endogenous receptor-binding molecules, enzyme substrates, or drug molecules have a nonzero net charge. Absolute binding free energies, as well as binding free energies relative to another molecule with a different net charge will be affected by artifacts due to the used effective electrostatic interaction function and associated parameters (e.g., size of the computational box). In the present study, charging contributions to binding free energies of small oligoatomic ions to a series of model host cavities functionalized with different chemical groups are calculated with classical atomistic molecular dynamics simulation. Electrostatic interactions are treated using a lattice-summation scheme or a cutoff-truncation scheme with Barker\textendash{}Watts reaction-field correction, and the simulations are conducted in boxes of different edge lengths. It is illustrated that the charging free energies of the guest molecules in water and in the host strongly depend on the applied methodology and that neglect of correction terms for the artifacts introduced by the finite size of the simulated system and the use of an effective electrostatic interaction function considerably impairs the thermodynamic interpretation of guest-host interactions. Application of correction terms for the various artifacts yields consistent results for the charging contribution to binding free energies and is thus a prerequisite for the valid interpretation or prediction of experimental data via molecular dynamics simulation. Analysis and correction of electrostatic artifacts according to the scheme proposed in the present study should therefore be considered an integral part of careful free-energy calculation studies if changes in the net charge are involved. \textcopyright 2013 The Authors Journal of Computational Chemistry Published by Wiley Periodicals, Inc.}, + abstract = {The calculation of binding free energies of charged species to a target molecule is a frequently encountered problem in molecular dynamics studies of (bio-)chemical thermodynamics. Many important endogenous receptor-binding molecules, enzyme substrates, or drug molecules have a nonzero net charge. Absolute binding free energies, as well as binding free energies relative to another molecule with a different net charge will be affected by artifacts due to the used effective electrostatic interaction function and associated parameters (e.g., size of the computational box). In the present study, charging contributions to binding free energies of small oligoatomic ions to a series of model host cavities functionalized with different chemical groups are calculated with classical atomistic molecular dynamics simulation. Electrostatic interactions are treated using a lattice-summation scheme or a cutoff-truncation scheme with Barker\textendash{}Watts reaction-field correction, and the simulations are conducted in boxes of different edge lengths. It is illustrated that the charging free energies of the guest molecules in water and in the host strongly depend on the applied methodology and that neglect of correction terms for the artifacts introduced by the finite size of the simulated system and the use of an effective electrostatic interaction function considerably impairs the thermodynamic interpretation of guest-host interactions. Application of correction terms for the various artifacts yields consistent results for the charging contribution to binding free energies and is thus a prerequisite for the valid interpretation or prediction of experimental data via molecular dynamics simulation. Analysis and correction of electrostatic artifacts according to the scheme proposed in the present study should therefore be considered an integral part of careful free-energy calculation studies if changes in the net charge are involved. \textcopyright{} 2013 The Authors Journal of Computational Chemistry Published by Wiley Periodicals, Inc.}, language = {en}, timestamp = {2016-09-02T18:46:21Z}, number = {3}, @@ -1245,7 +1236,7 @@ @incollection{shirts_free-energy_2010 file = {Shirts_2010:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/CHVMA5SB/Shirts_2010.pdf:application/pdf;Shirts_2010:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/TQWKWMK9/Shirts_2010.pdf:application/pdf} } -@article{shirts_accurate_2007, +@article{Shirts:2007:JPhysChemB, title = {Accurate and Efficient Corrections for Missing Dispersion Interactions in Molecular Simulations.}, volume = {111}, doi = {10.1021/jp0735987}, @@ -1335,7 +1326,7 @@ @article{sullivan_binding_2016 title = {Binding of Carboxylate and Trimethylammonium Salts to Octa-Acid and {{TEMOA}} Deep-Cavity Cavitands}, issn = {0920-654X, 1573-4951}, doi = {10.1007/s10822-016-9925-0}, - abstract = {In participation of the fifth statistical assessment of modeling of proteins and ligands (SAMPL5), the strength of association of six guests (3\textendash{}8) to two hosts (1 and 2) were measured by 1H NMR and ITC. Each host possessed a unique and well-defined binding pocket, whilst the wide array of amphiphilic guests possessed binding moieties that included: a terminal alkyne, nitro-arene, alkyl halide and cyano-arene groups. Solubilizing head groups for the guests included both positively charged trimethylammonium and negatively charged carboxylate functionality. Measured association constants (Ka) covered five orders of magnitude, ranging from 56 M-1 for guest 6 binding with host 2 up to 7.43 \texttimes 106 M-1 for guest 6 binding to host 1.}, + abstract = {In participation of the fifth statistical assessment of modeling of proteins and ligands (SAMPL5), the strength of association of six guests (3\textendash{}8) to two hosts (1 and 2) were measured by 1H NMR and ITC. Each host possessed a unique and well-defined binding pocket, whilst the wide array of amphiphilic guests possessed binding moieties that included: a terminal alkyne, nitro-arene, alkyl halide and cyano-arene groups. Solubilizing head groups for the guests included both positively charged trimethylammonium and negatively charged carboxylate functionality. Measured association constants (Ka) covered five orders of magnitude, ranging from 56 M-1 for guest 6 binding with host 2 up to 7.43 \texttimes{} 106 M-1 for guest 6 binding to host 1.}, language = {en}, timestamp = {2016-09-05T19:07:42Z}, urldate = {2016-09-05}, @@ -1343,6 +1334,7 @@ @article{sullivan_binding_2016 author = {Sullivan, Matthew R. and Sokkalingam, Punidha and Nguyen, Thong and Donahue, James P. and Gibb, Bruce C.}, month = jul, year = {2016}, + keywords = {experiment,OctaAcid,SAMPL,SAMPL5}, pages = {1--8}, file = {Full Text PDF:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/DZECQZV7/Sullivan et al. - 2016 - Binding of carboxylate and trimethylammonium salts.pdf:application/pdf;Snapshot:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/AZS2AFW7/10.html:text/html} } @@ -1417,7 +1409,7 @@ @article{rekharsky_synthetic_2007 volume = {104}, issn = {0027-8424, 1091-6490}, doi = {10.1073/pnas.0706407105}, - abstract = {The molecular host cucurbit[7]uril forms an extremely stable inclusion complex with the dicationic ferrocene derivative bis(trimethylammoniomethyl)ferrocene in aqueous solution. The equilibrium association constant for this host-guest pair is 3 \texttimes 1015 M-1 (K d = 3 \texttimes 10-16 M), equivalent to that exhibited by the avidin\textendash{}biotin pair. Although purely synthetic systems with larger association constants have been reported, the present one is unique because it does not rely on polyvalency. Instead, it achieves its extreme affinity by overcoming the compensatory enthalpy\textendash{}entropy relationship usually observed in supramolecular complexes. Its disproportionately low entropic cost is traced to extensive host desolvation and to the rigidity of both the host and the guest.}, + abstract = {The molecular host cucurbit[7]uril forms an extremely stable inclusion complex with the dicationic ferrocene derivative bis(trimethylammoniomethyl)ferrocene in aqueous solution. The equilibrium association constant for this host-guest pair is 3 \texttimes{} 1015 M-1 (K d = 3 \texttimes{} 10-16 M), equivalent to that exhibited by the avidin\textendash{}biotin pair. Although purely synthetic systems with larger association constants have been reported, the present one is unique because it does not rely on polyvalency. Instead, it achieves its extreme affinity by overcoming the compensatory enthalpy\textendash{}entropy relationship usually observed in supramolecular complexes. Its disproportionately low entropic cost is traced to extensive host desolvation and to the rigidity of both the host and the guest.}, language = {en}, timestamp = {2016-07-20T18:03:48Z}, number = {52}, @@ -1452,21 +1444,21 @@ @article{liu_cucurbituril_2005 } @article{muddana_sampl3_2012, - title = {Blind Prediction of Host\textendash{}guest Binding Affinities: A New {{SAMPL3}} Challenge}, + title = {Blind Prediction of Host\textendash{}guest Binding Affinities: {{A}} New {{SAMPL3}} Challenge}, volume = {26}, issn = {0920-654X, 1573-4951}, shorttitle = {Blind Prediction of Host\textendash{}guest Binding Affinities}, doi = {10.1007/s10822-012-9554-1}, abstract = {The computational prediction of protein\textendash{}ligand binding affinities is of central interest in early-stage drug-discovery, and there is a widely recognized need for improved methods. Low molecular weight receptors and their ligands\textemdash{}i.e., host\textendash{}guest systems\textemdash{}represent valuable test-beds for such affinity prediction methods, because their small size makes for fast calculations and relatively facile numerical convergence. The SAMPL3 community exercise included the first ever blind prediction challenge for host\textendash{}guest binding affinities, through the incorporation of 11 new host\textendash{}guest complexes. Ten participating research groups addressed this challenge with a variety of approaches. Statistical assessment indicates that, although most methods performed well at predicting some general trends in binding affinity, overall accuracy was not high, as all the methods suffered from either poor correlation or high RMS errors or both. There was no clear advantage in using explicit versus implicit solvent models, any particular force field, or any particular approach to conformational sampling. In a few cases, predictions using very similar energy models but different sampling and/or free-energy methods resulted in significantly different results. The protonation states of one host and some guest molecules emerged as key uncertainties beyond the choice of computational approach. The present results have implications for methods development and future blind prediction exercises.}, language = {en}, - timestamp = {2016-07-20T18:25:53Z}, + timestamp = {2016-10-13T22:27:28Z}, number = {5}, urldate = {2016-07-20}, journal = {J Comput Aided Mol Des}, author = {Muddana, Hari S. and Varnado, C. Daniel and Bielawski, Christopher W. and Urbach, Adam R. and Isaacs, Lyle and Geballe, Matthew T. and Gilson, Michael K.}, month = feb, year = {2012}, - keywords = {alchemical,CB7,cucurbituril,host–guest complexation,SAMPL3}, + keywords = {alchemical,CB7,cucurbituril,host–guest complexation,overview,SAMPL,SAMPL3}, pages = {475--487}, file = {Full Text PDF:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/QPWKPVRN/Muddana et al. - 2012 - Blind prediction of host–guest binding affinities.pdf:application/pdf;Snapshot:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/ZUQH39X3/10.html:text/html} } @@ -1513,12 +1505,12 @@ @article{deng_distinguishing_2015 author = {Deng, Nanjie and Forli, Stefano and He, Peng and Perryman, Alex and Wickstrom, Lauren and Vijayan, R. S. K. and Tiefenbrunn, Theresa and Stout, David and Gallicchio, Emilio and Olson, Arthur J. and Levy, Ronald M.}, month = jan, year = {2015}, - keywords = {alchemical,BEDAM,HIV integrase,SAMPL4}, + keywords = {alchemical,BEDAM,binding free energy,HIV integrase,SAMPL,SAMPL4}, pages = {976--988}, file = {ACS Full Text PDF w/ Links:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/RJZ9GWA9/Deng et al. - 2015 - Distinguishing Binders from False Positives by Fre.pdf:application/pdf;ACS Full Text Snapshot:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/G9RBHPQI/jp506376z.html:text/html} } -@article{schnieders_structure_2012, +@article{Schnieders:2012:J.Chem.TheoryComput., title = {The {{Structure}}, {{Thermodynamics}}, and {{Solubility}} of {{Organic Crystals}} from {{Simulation}} with a {{Polarizable Force Field}}}, volume = {8}, issn = {1549-9618}, @@ -1629,7 +1621,7 @@ @article{mobley_proposal_2015 @article{mosca_preparative_2016, title = {Preparative Scale and Convenient Synthesis of a Water-Soluble, Deep Cavitand}, volume = {11}, - copyright = {\textcopyright 2016 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.}, + copyright = {\textcopyright{} 2016 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.}, issn = {1754-2189}, doi = {10.1038/nprot.2016.078}, abstract = {Cavitands are established tools of supramolecular chemistry and molecular recognition, and they are finding increasing application in sensing and sequestration of physiologically relevant molecules in aqueous solution. The synthesis of a water-soluble, deep cavitand is described. The route comprises six (linear) steps from commercially available precursors, and it relies on the fourfold oligomeric cyclization reaction of resorcinol with 2,3-dihydrofuran that leads to the formation of a shallow resorcinarene framework; condensation with aromatic panels, which deepens the hydrophobic binding cavity; construction of rigid urea functionalities on the upper rim; and the introduction of the water-solubilizing methylimidazolium groups on the lower rim. Late intermediates of the synthesis can be used in the preparation of congener cavitands with different properties and applications, and a sample of such a synthetic procedure is included in this protocol. Emphasis is placed on scaled-up reactions and on purification procedures that afford materials in high yield and avoid chromatographic purification. This protocol provides improvements over previously described procedures, and it enables the preparation of sizable amounts of deep cavitands: 7 g of a water-soluble cavitand can be prepared from resorcinol in 13 working days. @@ -1639,7 +1631,7 @@ @article{mosca_preparative_2016 number = {8}, urldate = {2016-09-05}, journal = {Nat. Protocols}, - author = {Mosca, Simone and Yu, Yang and {Rebek Jr}, Julius}, + author = {Mosca, Simone and Yu, Yang and Rebek Jr, Julius}, month = aug, year = {2016}, keywords = {Chemical biology,Chemical synthesis,Organic chemistry,Supramolecular chemistry}, @@ -1666,7 +1658,7 @@ @article{cao_attomolar_2014 file = {Full Text PDF:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/FNHB6VJ4/Cao et al. - 2014 - Cucurbit[7]uril⋅Guest Pair with an Attomolar Disso.pdf:application/pdf;Snapshot:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/CBJSPQSX/abstract.html:text/html} } -@article{jang_cucurbit[7]uril:_2014, +@article{Jang:2014:Angew.Chem.Int.Ed., title = {Cucurbit[7]uril: {{A High}}-{{Affinity Host}} for {{Encapsulation}} of {{Amino Saccharides}} and {{Supramolecular Stabilization}} of {{Their}} $\alpha$-{{Anomers}} in {{Water}}}, volume = {53}, issn = {1521-3773}, @@ -1692,7 +1684,7 @@ @article{su_docking_2001 issn = {1097-0134}, shorttitle = {Docking Molecules by Families to Increase the Diversity of Hits in Database Screens}, doi = {10.1002/1097-0134(20010201)42:2<279::AID-PROT150>3.0.CO;2-U}, - abstract = {Molecular docking programs screen chemical databases for novel ligands that fit protein binding sites. When one compound fits the site well, close analogs typically do the same. Therefore, many of the compounds that are found in such screens resemble one another. This reduces the variety and novelty of the compounds suggested. In an attempt to increase the diversity of docking hit lists, the Available Chemicals Directory was grouped into families of related structures. All members of every family were docked and scored, but only the best scoring molecule of a high-ranking family was allowed in the hit list. The identity and scores of the other members of these families were recorded as annotations to the best family member, but they were not independently ranked. This family-based docking method was compared with molecule-by-molecule docking in screens against the structures of thymidylate synthase, dihydrofolate reductase (DHFR), and the cavity site of the mutant T4 lysozyme Leu99 $\rightarrow$ Ala (L99A). In each case, the diversity of the hit list increased, and more families of known ligands were found. To investigate whether the newly identified hits were sensible, we tested representative examples experimentally for binding to L99A and DHFR. Of the six compounds tested against L99A, five bound to the internal cavity. Of the seven compounds tested against DHFR, six inhibited the enzyme with apparent Ki values between 0.26 and 100 $\mu$M. The segregation of potential ligands into families of related molecules is a simple technique to increase the diversity of candidates suggested by database screens. The general approach should be applicable to most docking methods. Proteins 2001;42:279\textendash{}293. \textcopyright 2000 Wiley-Liss, Inc.}, + abstract = {Molecular docking programs screen chemical databases for novel ligands that fit protein binding sites. When one compound fits the site well, close analogs typically do the same. Therefore, many of the compounds that are found in such screens resemble one another. This reduces the variety and novelty of the compounds suggested. In an attempt to increase the diversity of docking hit lists, the Available Chemicals Directory was grouped into families of related structures. All members of every family were docked and scored, but only the best scoring molecule of a high-ranking family was allowed in the hit list. The identity and scores of the other members of these families were recorded as annotations to the best family member, but they were not independently ranked. This family-based docking method was compared with molecule-by-molecule docking in screens against the structures of thymidylate synthase, dihydrofolate reductase (DHFR), and the cavity site of the mutant T4 lysozyme Leu99 $\rightarrow$ Ala (L99A). In each case, the diversity of the hit list increased, and more families of known ligands were found. To investigate whether the newly identified hits were sensible, we tested representative examples experimentally for binding to L99A and DHFR. Of the six compounds tested against L99A, five bound to the internal cavity. Of the seven compounds tested against DHFR, six inhibited the enzyme with apparent Ki values between 0.26 and 100 $\mu$M. The segregation of potential ligands into families of related molecules is a simple technique to increase the diversity of candidates suggested by database screens. The general approach should be applicable to most docking methods. Proteins 2001;42:279\textendash{}293. \textcopyright{} 2000 Wiley-Liss, Inc.}, language = {en}, timestamp = {2016-08-31T18:03:51Z}, number = {2}, @@ -1728,7 +1720,7 @@ @article{wei_testing_2004 volume = {337}, issn = {0022-2836}, doi = {10.1016/j.jmb.2004.02.015}, - abstract = {Sampling receptor flexibility is challenging for database docking. We consider a method that treats multiple flexible regions of the binding site independently, recombining them to generate different discrete conformations. This algorithm scales linearly rather than exponentially with the receptor's degrees of freedom. The method was first evaluated for its ability to identify known ligands of a hydrophobic cavity mutant of T4 lysozyme (L99A). Some 200,000 molecules of the Available Chemical Directory (ACD) were docked against an ensemble of cavity conformations. Surprisingly, the enrichment of known ligands from among a much larger number of decoys in the ACD was worse than simply docking to the apo conformation alone. Large decoys, accommodated in the larger cavity conformations sampled in the ensemble, were ranked better than known small ligands. The calculation was redone with an energy correction term that considered the cost of forming the larger cavity conformations. Enrichment improved, as did the balance between high-ranking large and small ligands. In a second retrospective test, the ACD was docked against a conformational ensemble of thymidylate synthase. Compared to docking against individual enzyme conformations, the flexible receptor docking approach improved enrichment of known ligands. Including a receptor conformational energy weighting term improved enrichment further. To test the method prospectively, the ACD database was docked against another cavity mutant of lysozyme (L99A/M102Q). A total of 18 new compounds predicted to bind this polar cavity and to change its conformation were tested experimentally; 14 were found to bind. The bound structures for seven ligands were determined by X-ray crystallography. The predicted geometries of these ligands all corresponded to the observed geometries to within 0.7 \AA RMSD or better. Significant conformational changes of the cavity were observed in all seven complexes. In five structures, part of the observed accommodations were correctly predicted; in two structures, the receptor conformational changes were unanticipated and thus never sampled. These results suggest that although sampling receptor flexibility can lead to novel ligands that would have been missed when docking a rigid structure, it is also important to consider receptor conformational energy.}, + abstract = {Sampling receptor flexibility is challenging for database docking. We consider a method that treats multiple flexible regions of the binding site independently, recombining them to generate different discrete conformations. This algorithm scales linearly rather than exponentially with the receptor's degrees of freedom. The method was first evaluated for its ability to identify known ligands of a hydrophobic cavity mutant of T4 lysozyme (L99A). Some 200,000 molecules of the Available Chemical Directory (ACD) were docked against an ensemble of cavity conformations. Surprisingly, the enrichment of known ligands from among a much larger number of decoys in the ACD was worse than simply docking to the apo conformation alone. Large decoys, accommodated in the larger cavity conformations sampled in the ensemble, were ranked better than known small ligands. The calculation was redone with an energy correction term that considered the cost of forming the larger cavity conformations. Enrichment improved, as did the balance between high-ranking large and small ligands. In a second retrospective test, the ACD was docked against a conformational ensemble of thymidylate synthase. Compared to docking against individual enzyme conformations, the flexible receptor docking approach improved enrichment of known ligands. Including a receptor conformational energy weighting term improved enrichment further. To test the method prospectively, the ACD database was docked against another cavity mutant of lysozyme (L99A/M102Q). A total of 18 new compounds predicted to bind this polar cavity and to change its conformation were tested experimentally; 14 were found to bind. The bound structures for seven ligands were determined by X-ray crystallography. The predicted geometries of these ligands all corresponded to the observed geometries to within 0.7 \AA{} RMSD or better. Significant conformational changes of the cavity were observed in all seven complexes. In five structures, part of the observed accommodations were correctly predicted; in two structures, the receptor conformational changes were unanticipated and thus never sampled. These results suggest that although sampling receptor flexibility can lead to novel ligands that would have been missed when docking a rigid structure, it is also important to consider receptor conformational energy.}, timestamp = {2016-08-31T19:58:29Z}, number = {5}, urldate = {2016-08-31}, @@ -1751,7 +1743,7 @@ @article{banba_efficient_2000 number = {29}, urldate = {2016-08-31}, journal = {J. Phys. Chem. B}, - author = {Banba, Shinichi and Guo, Zhuyan and {Brooks III}, Charles L}, + author = {Banba, Shinichi and Guo, Zhuyan and Brooks III, Charles L}, month = jul, year = {2000}, keywords = {alchemical,binding free energy,CCP,CCP closed,closed}, @@ -1769,7 +1761,7 @@ @article{banba_free_2000 number = {8}, urldate = {2016-08-31}, journal = {The Journal of Chemical Physics}, - author = {Banba, Shinichi and {Brooks III}, Charles L}, + author = {Banba, Shinichi and Brooks III, Charles L}, month = aug, year = {2000}, keywords = {binding free energy,Cavitation,CCP,CCP closed,closed,Entropy,Free energy,Physics demonstrations,Proteins}, @@ -1797,7 +1789,7 @@ @article{rosenfeld_excision_2002 } @article{musah_artificial_2002, - title = {Artificial Protein Cavities as Specific Ligand-Binding Templates: Characterization of an Engineered Heterocyclic Cation-Binding Site that Preserves the Evolved Specificity of the Parent protein1}, + title = {Artificial Protein Cavities as Specific Ligand-Binding Templates: Characterization of an Engineered Heterocyclic Cation-Binding Site That Preserves the Evolved Specificity of the Parent protein1}, volume = {315}, issn = {0022-2836}, shorttitle = {Artificial Protein Cavities as Specific Ligand-Binding Templates}, @@ -1818,7 +1810,7 @@ @article{musah_artificial_2002 @article{fitzgerald_ligand-gated_1996, title = {A Ligand-Gated, Hinged Loop Rearrangement Opens a Channel to a Buried Artificial Protein Cavity}, volume = {3}, - copyright = {\textcopyright 1996 Nature Publishing Group}, + copyright = {\textcopyright{} 1996 Nature Publishing Group}, doi = {10.1038/nsb0796-626}, abstract = {Conformational changes that gate the access of substrates or ligands to an active site are important features of enzyme function. In this report, we describe an unusual example of a structural rearrangement near a buried artificial cavity in cytochrome cperoxidase that occurs on binding protonated benzimidazole. A hinged main-chain rotation at two residues (Pro 190 and Asn 195) results in a surface loop rearrangement that opens a large solvent-accessible channel for the entry of ligands to an otherwise inaccessible binding site. The trapping of this alternate conformational state provides a unique view of the extent to which protein dynamics can allow small molecule penetration into buried protein cavities.}, language = {en}, @@ -1839,7 +1831,7 @@ @article{mikulskis_large-scale_2014 volume = {54}, issn = {1549-9596}, doi = {10.1021/ci5004027}, - abstract = {We have performed a large-scale test of alchemical perturbation calculations with the Bennett acceptance-ratio (BAR) approach to estimate relative affinities for the binding of 107 ligands to 10 different proteins. Employing 20-\AA truncated spherical systems and only one intermediate state in the perturbations, we obtain an error of less than 4 kJ/mol for 54\% of the studied relative affinities and a precision of 0.5 kJ/mol on average. However, only four of the proteins gave acceptable errors, correlations, and rankings. The results could be improved by using nine intermediate states in the simulations or including the entire protein in the simulations using periodic boundary conditions. However, 27 of the calculated affinities still gave errors of more than 4 kJ/mol, and for three of the proteins the results were not satisfactory. This shows that the performance of BAR calculations depends on the target protein and that several transformations gave poor results owing to limitations in the molecular-mechanics force field or the restricted sampling possible within a reasonable simulation time. Still, the BAR results are better than docking calculations for most of the proteins.}, + abstract = {We have performed a large-scale test of alchemical perturbation calculations with the Bennett acceptance-ratio (BAR) approach to estimate relative affinities for the binding of 107 ligands to 10 different proteins. Employing 20-\AA{} truncated spherical systems and only one intermediate state in the perturbations, we obtain an error of less than 4 kJ/mol for 54\% of the studied relative affinities and a precision of 0.5 kJ/mol on average. However, only four of the proteins gave acceptable errors, correlations, and rankings. The results could be improved by using nine intermediate states in the simulations or including the entire protein in the simulations using periodic boundary conditions. However, 27 of the calculated affinities still gave errors of more than 4 kJ/mol, and for three of the proteins the results were not satisfactory. This shows that the performance of BAR calculations depends on the target protein and that several transformations gave poor results owing to limitations in the molecular-mechanics force field or the restricted sampling possible within a reasonable simulation time. Still, the BAR results are better than docking calculations for most of the proteins.}, timestamp = {2016-08-31T23:04:40Z}, number = {10}, urldate = {2016-08-31}, @@ -1936,12 +1928,12 @@ @article{skillman_sampl3_2012 author = {Skillman, A. Geoffrey}, month = may, year = {2012}, - keywords = {overview,SAMPL3,trypsin}, + keywords = {overview,SAMPL,SAMPL3,trypsin}, pages = {473--474}, file = {Full Text PDF:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/ZXEXV4TQ/Skillman - 2012 - SAMPL3 blinded prediction of host–guest binding a.pdf:application/pdf;Snapshot:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/ZVXSPHDE/s10822-012-9580-z.html:text/html} } -@article{newman_dingo_2011, +@article{Newman:2011:JComputAidedMolDes, title = {The {{DINGO}} Dataset: A Comprehensive Set of Data for the {{SAMPL}} Challenge}, volume = {26}, issn = {0920-654X, 1573-4951}, @@ -1956,7 +1948,7 @@ @article{newman_dingo_2011 author = {Newman, Janet and Dolezal, Olan and Fazio, Vincent and Caradoc-Davies, Tom and Peat, Thomas S.}, month = dec, year = {2011}, - keywords = {SAMPL3,trypsin}, + keywords = {crystallography,experiment,SAMPL,SAMPL3,trypsin}, pages = {497--503}, file = {Full Text PDF:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/DI58Q3BZ/Newman et al. - 2011 - The DINGO dataset a comprehensive set of data for.pdf:application/pdf;Snapshot:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/DSAP4RSI/s10822-011-9521-2.html:text/html} } @@ -2021,7 +2013,7 @@ @article{jiao_trypsin_2009 volume = {30}, issn = {1096-987X}, doi = {10.1002/jcc.21268}, - abstract = {We have calculated the binding free energies of a series of benzamidine-like inhibitors to trypsin with a polarizable force field using both explicit and implicit solvent approaches. Free energy perturbation has been performed for the ligands in bulk water and in protein complex with molecular dynamics simulations. The binding free energies calculated from explicit solvent simulations are well within the accuracy of experimental measurement and the direction of change is predicted correctly in all cases. We analyzed the molecular dipole moments of the ligands in gas, water and protein environments. Neither binding affinity nor ligand solvation free energy in bulk water shows much dependence on the molecular dipole moments of the ligands. Substitution of the aromatic or the charged group in the ligand results in considerable change in the solvation energy in bulk water and protein whereas the binding affinity varies insignificantly due to cancellation. The effect of chemical modification on ligand charge distribution is mostly local. Replacing benzene with diazine has minimal impact on the atomic multipoles at the amidinium group. We have also utilized an implicit solvent based end-state approach to evaluate the binding free energies of these inhibitors. In this approach, the polarizable multipole model combined with Poisson-Boltzmann/surface area (PMPB/SA) provides the electrostatic interaction energy and the polar solvation free energy. Overall the relative binding free energies obtained from the MM-PMPB/SA model are in good agreement with the experimental data. \textcopyright 2009 Wiley Periodicals, Inc. J Comput Chem 2009}, + abstract = {We have calculated the binding free energies of a series of benzamidine-like inhibitors to trypsin with a polarizable force field using both explicit and implicit solvent approaches. Free energy perturbation has been performed for the ligands in bulk water and in protein complex with molecular dynamics simulations. The binding free energies calculated from explicit solvent simulations are well within the accuracy of experimental measurement and the direction of change is predicted correctly in all cases. We analyzed the molecular dipole moments of the ligands in gas, water and protein environments. Neither binding affinity nor ligand solvation free energy in bulk water shows much dependence on the molecular dipole moments of the ligands. Substitution of the aromatic or the charged group in the ligand results in considerable change in the solvation energy in bulk water and protein whereas the binding affinity varies insignificantly due to cancellation. The effect of chemical modification on ligand charge distribution is mostly local. Replacing benzene with diazine has minimal impact on the atomic multipoles at the amidinium group. We have also utilized an implicit solvent based end-state approach to evaluate the binding free energies of these inhibitors. In this approach, the polarizable multipole model combined with Poisson-Boltzmann/surface area (PMPB/SA) provides the electrostatic interaction energy and the polar solvation free energy. Overall the relative binding free energies obtained from the MM-PMPB/SA model are in good agreement with the experimental data. \textcopyright{} 2009 Wiley Periodicals, Inc. J Comput Chem 2009}, language = {en}, timestamp = {2016-09-01T17:46:51Z}, number = {11}, @@ -2050,7 +2042,7 @@ @article{gallicchio_virtual_2014 author = {Gallicchio, Emilio and Deng, Nanjie and He, Peng and Wickstrom, Lauren and Perryman, Alexander L. and Santiago, Daniel N. and Forli, Stefano and Olson, Arthur J. and Levy, Ronald M.}, month = feb, year = {2014}, - keywords = {alchemical,HIV integrase,SAMPL4}, + keywords = {alchemical,HIV integrase,SAMPL,SAMPL4}, pages = {475--490}, file = {Full Text PDF:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/E8RDGITW/Gallicchio et al. - 2014 - Virtual screening of integrase inhibitors by large.pdf:application/pdf;Snapshot:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/2W2FXFN7/10.html:text/html} } @@ -2074,7 +2066,7 @@ @article{mobley_blind_2014 } @article{peat_interrogating_2014, - title = {Interrogating {{HIV}} Integrase for Compounds that Bind- a {{SAMPL}} Challenge}, + title = {Interrogating {{HIV}} Integrase for Compounds That Bind- a {{SAMPL}} Challenge}, volume = {28}, issn = {0920-654X, 1573-4951}, doi = {10.1007/s10822-014-9721-7}, @@ -2288,7 +2280,7 @@ @article{tame_crystal_1995 doi = {10.1016/S0969-2126(01)00276-3}, abstract = {Background: The periplasmic oligopeptide-binding protein OppA has a remarkably broad substrate specificity, binding peptides of two to five amino-acid residues with high affinity, but little regard to sequence. It is therefore an ideal system for studying how different chemical groups can be accommodated in a protein interior. The ability of the protein to bind peptides of different lengths has been studied by co-crystallising it with different ligands. -Results Crystals of OppA from Salmonella typhimurium complexed with the peptides Lys\textendash{}Lys\textendash{}Lys (KKK) and Lys\textendash{}Lys\textendash{}Lys\textendash{}Ala (KKKA) have been grown in the presence of uranyl ions which form important crystal contacts. These structures have been refined to 1.4 \aa and 2.1 \aa, respectively. The ligands are completely enclosed, their side chains pointing into large hydrated cavities and making few strong interactions with the protein. +Results Crystals of OppA from Salmonella typhimurium complexed with the peptides Lys\textendash{}Lys\textendash{}Lys (KKK) and Lys\textendash{}Lys\textendash{}Lys\textendash{}Ala (KKKA) have been grown in the presence of uranyl ions which form important crystal contacts. These structures have been refined to 1.4 \aa{} and 2.1 \aa, respectively. The ligands are completely enclosed, their side chains pointing into large hydrated cavities and making few strong interactions with the protein. Conclusion Tight peptide binding by OppA arises from strong hydrogen bonding and electrostatic interactions between the protein and the main chain of the ligand. Different basic side chains on the protein form salt bridges with the C terminus of peptide ligands of different lengths.}, timestamp = {2016-09-01T18:44:30Z}, @@ -2396,7 +2388,7 @@ @article{velez-vega_overcoming_2013 volume = {34}, issn = {1096-987X}, doi = {10.1002/jcc.23398}, - abstract = {This article addresses calculations of the standard free energy of binding from molecular simulations in which a bound ligand is extracted from its binding site by steered molecular dynamics (MD) simulations or equilibrium umbrella sampling (US). Host\textendash{}guest systems are used as test beds to examine the requirements for obtaining the reversible work of ligand extraction. We find that, for both steered MD and US, marked irreversibilities can occur when the guest molecule crosses an energy barrier and suddenly jumps to a new position, causing dissipation of energy stored in the stretched molecule(s). For flexible molecules, this occurs even when a stiff pulling spring is used, and it is difficult to suppress in calculations where the spring is attached to the molecules by single, fixed attachment points. We, therefore, introduce and test a method, fluctuation-guided pulling, which adaptively adjusts the spring's attachment points based on the guest's atomic fluctuations relative to the host. This adaptive approach is found to substantially improve the reversibility of both steered MD and US calculations for the present systems. The results are then used to estimate standard binding free energies within a comprehensive framework, termed attach-pull-release, which recognizes that the standard free energy of binding must include not only the pulling work itself, but also the work of attaching and then releasing the spring, where the release work includes an accounting of the standard concentration to which the ligand is discharged. \textcopyright 2013 Wiley Periodicals, Inc.}, + abstract = {This article addresses calculations of the standard free energy of binding from molecular simulations in which a bound ligand is extracted from its binding site by steered molecular dynamics (MD) simulations or equilibrium umbrella sampling (US). Host\textendash{}guest systems are used as test beds to examine the requirements for obtaining the reversible work of ligand extraction. We find that, for both steered MD and US, marked irreversibilities can occur when the guest molecule crosses an energy barrier and suddenly jumps to a new position, causing dissipation of energy stored in the stretched molecule(s). For flexible molecules, this occurs even when a stiff pulling spring is used, and it is difficult to suppress in calculations where the spring is attached to the molecules by single, fixed attachment points. We, therefore, introduce and test a method, fluctuation-guided pulling, which adaptively adjusts the spring's attachment points based on the guest's atomic fluctuations relative to the host. This adaptive approach is found to substantially improve the reversibility of both steered MD and US calculations for the present systems. The results are then used to estimate standard binding free energies within a comprehensive framework, termed attach-pull-release, which recognizes that the standard free energy of binding must include not only the pulling work itself, but also the work of attaching and then releasing the spring, where the release work includes an accounting of the standard concentration to which the ligand is discharged. \textcopyright{} 2013 Wiley Periodicals, Inc.}, language = {en}, timestamp = {2016-09-01T19:28:56Z}, number = {27}, @@ -2501,7 +2493,7 @@ @article{christ_basic_2010 issn = {1096-987X}, shorttitle = {Basic Ingredients of Free Energy Calculations}, doi = {10.1002/jcc.21450}, - abstract = {Methods to compute free energy differences between different states of a molecular system are reviewed with the aim of identifying their basic ingredients and their utility when applied in practice to biomolecular systems. A free energy calculation is comprised of three basic components: (i) a suitable model or Hamiltonian, (ii) a sampling protocol with which one can generate a representative ensemble of molecular configurations, and (iii) an estimator of the free energy difference itself. Alternative sampling protocols can be distinguished according to whether one or more states are to be sampled. In cases where only a single state is considered, six alternative techniques could be distinguished: (i) changing the dynamics, (ii) deforming the energy surface, (iii) extending the dimensionality, (iv) perturbing the forces, (v) reducing the number of degrees of freedom, and (vi) multi-copy approaches. In cases where multiple states are to be sampled, the three primary techniques are staging, importance sampling, and adiabatic decoupling. Estimators of the free energy can be classified as global methods that either count the number of times a given state is sampled or use energy differences. Or, they can be classified as local methods that either make use of the force or are based on transition probabilities. Finally, this overview of the available techniques and how they can be best used in a practical context is aimed at helping the reader choose the most appropriate combination of approaches for the biomolecular system, Hamiltonian and free energy difference of interest. \textcopyright 2009 Wiley Periodicals, Inc. J Comput Chem, 2010}, + abstract = {Methods to compute free energy differences between different states of a molecular system are reviewed with the aim of identifying their basic ingredients and their utility when applied in practice to biomolecular systems. A free energy calculation is comprised of three basic components: (i) a suitable model or Hamiltonian, (ii) a sampling protocol with which one can generate a representative ensemble of molecular configurations, and (iii) an estimator of the free energy difference itself. Alternative sampling protocols can be distinguished according to whether one or more states are to be sampled. In cases where only a single state is considered, six alternative techniques could be distinguished: (i) changing the dynamics, (ii) deforming the energy surface, (iii) extending the dimensionality, (iv) perturbing the forces, (v) reducing the number of degrees of freedom, and (vi) multi-copy approaches. In cases where multiple states are to be sampled, the three primary techniques are staging, importance sampling, and adiabatic decoupling. Estimators of the free energy can be classified as global methods that either count the number of times a given state is sampled or use energy differences. Or, they can be classified as local methods that either make use of the force or are based on transition probabilities. Finally, this overview of the available techniques and how they can be best used in a practical context is aimed at helping the reader choose the most appropriate combination of approaches for the biomolecular system, Hamiltonian and free energy difference of interest. \textcopyright{} 2009 Wiley Periodicals, Inc. J Comput Chem, 2010}, language = {en}, timestamp = {2016-09-02T17:41:49Z}, number = {8}, @@ -2651,7 +2643,7 @@ @article{calabro_accelerating_2015 @article{eriksson_cavity-containing_1992, title = {A Cavity-Containing Mutant of {{T4}} Lysozyme Is Stabilized by Buried Benzene}, volume = {355}, - copyright = {\textcopyright 1992 Nature Publishing Group}, + copyright = {\textcopyright{} 1992 Nature Publishing Group}, issn = {0028-0836}, doi = {10.1038/355371a0}, language = {en}, @@ -2677,7 +2669,7 @@ @book{allen_computer_1989 year = {1989} } -@article{tembe_ligand_1984, +@article{Tembe:1984:ComputChem, title = {Ligand {{Receptor Interactions}}}, volume = {8}, timestamp = {2016-09-07T17:13:27Z}, @@ -2690,7 +2682,7 @@ @article{tembe_ligand_1984 file = {Tembe_1984-Comput Chem:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/ZGQAI9B9/Tembe_1984-Comput Chem.pdf:application/pdf} } -@article{hermans_free_1986, +@article{Hermans:1986:Isr.J.Chem., title = {The Free Energy of Xenon Binding to Myoglobin from Molecular Dynamics Simulation}, volume = {27}, timestamp = {2016-09-07T17:17:14Z}, @@ -2708,7 +2700,7 @@ @article{jorgensen_efficient_1988 volume = {89}, issn = {0021-9606, 1089-7690}, doi = {10.1063/1.454895}, - abstract = {An efficient procedure is noted for computing absolute free energies of binding for complexes in solution. Two series of computer simulations are required in which the substrate is annihilated in the solvent by itself and in the solvated complex. For illustration, the free energy of binding for two methane-like particles at their contact separation of 4 \AA has been computed in TIP4P water. Though several alternatives are possible, in this case, Monte Carlo simulations were employed with statistical perturbation theory in the NPT ensemble at 25 $^\circ$C and 1 atm. The results for the free energy of binding as well as for the potential of mean force are consistent with prior findings from the integral equation theory of Pratt and Chandler.}, + abstract = {An efficient procedure is noted for computing absolute free energies of binding for complexes in solution. Two series of computer simulations are required in which the substrate is annihilated in the solvent by itself and in the solvated complex. For illustration, the free energy of binding for two methane-like particles at their contact separation of 4 \AA{} has been computed in TIP4P water. Though several alternatives are possible, in this case, Monte Carlo simulations were employed with statistical perturbation theory in the NPT ensemble at 25 $^\circ$C and 1 atm. The results for the free energy of binding as well as for the potential of mean force are consistent with prior findings from the integral equation theory of Pratt and Chandler.}, timestamp = {2016-09-07T17:46:10Z}, number = {6}, urldate = {2016-09-07}, @@ -2769,7 +2761,7 @@ @article{michel_hit_2008 @article{karplus_molecular_2002, title = {Molecular Dynamics Simulations of Biomolecules}, volume = {9}, - copyright = {\textcopyright 2002 Nature Publishing Group}, + copyright = {\textcopyright{} 2002 Nature Publishing Group}, issn = {1072-8368}, doi = {10.1038/nsb0902-646}, abstract = {Molecular dynamics simulations are important tools for understanding the physical basis of the structure and function of biological macromolecules. The early view of proteins as relatively rigid structures has been replaced by a dynamic model in which the internal motions and resulting conformational changes play an essential role in their function. This review presents a brief description of the origin and early uses of biomolecular simulations. It then outlines some recent studies that illustrate the utility of such simulations and closes with a discussion of their ever-increasing potential for contributing to biology.}, @@ -2785,7 +2777,7 @@ @article{karplus_molecular_2002 file = {Full Text PDF:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/MFN33HBH/Karplus and McCammon - 2002 - Molecular dynamics simulations of biomolecules.pdf:application/pdf;Snapshot:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/585BXC72/nsb0902-646.html:text/html} } -@article{gibb_well-defined_2004-1, +@article{Gibb:2004:J.Am.Chem.Soc., title = {Well-Defined, Organic Nanoenvironments in Water: The Hydrophobic Effect Drives a Capsular Assembly}, volume = {126}, issn = {0002-7863}, @@ -2803,8 +2795,8 @@ @article{gibb_well-defined_2004-1 pmid = {15366865} } -@article{cong_synthesis_2016, - title = {Synthesis and Separation of Cucurbit[n]urils and their Derivatives}, +@article{Cong:2016:Org.Biomol.Chem., + title = {Synthesis and Separation of Cucurbit[n]urils and Their Derivatives}, volume = {14}, issn = {1477-0539}, doi = {10.1039/c6ob00268d}, @@ -2871,7 +2863,7 @@ @article{jorgensen_quantum_1981 pages = {345--350} } -@article{lee_cucurbituril_2003, +@article{Lee:2003:Acc.Chem.Res., title = {Cucurbituril Homologues and Derivatives: New Opportunities in Supramolecular Chemistry}, volume = {36}, issn = {0001-4842}, @@ -2922,15 +2914,6 @@ @article{flyvbjerg_error_1989 pages = {461} } -@article{gathiaka_d3r_2016, - title = {{{D3R Grand Challenge}} 2015: {{Evaluation}} of {{Protein}}-{{Ligand Pose}} and {{Affinity Predictions}}}, - volume = {(In press)}, - timestamp = {2016-09-08T23:14:47Z}, - journal = {J. Comput. Aided Mol. Des.}, - author = {Gathiaka, S. and Liu, S. and Chiu, M. and Yang, H. and Stuckey, J.A. and Kang, Y.N. and Delproposto, J. and Kubish, G. and Dunbar, J.B. and Carlson, H.A. and Burley, S.K. and Walters, W.P. and Amaro, R.E. and Feher, V.A. and Gilson, M.K.}, - year = {2016} -} - @article{tai_conformational_2004, title = {Conformational Sampling for the Impatient}, volume = {107}, @@ -2948,7 +2931,7 @@ @article{tai_conformational_2004 file = {1-s2.0-S0301462203002813-main.pdf:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/NGJEE54M/1-s2.0-S0301462203002813-main.pdf:application/pdf} } -@article{lee_cucurbituril_2003-1, +@article{Lee:2003:AccountsofChemicalResearch, title = {Cucurbituril {{Homologues}} and {{Derivatives}}:\, {{New Opportunities}} in {{Supramolecular Chemistry}}}, volume = {36}, shorttitle = {Cucurbituril {{Homologues}} and {{Derivatives}}}, @@ -3023,6 +3006,54 @@ @article{godinez_thermodynamic_1997 file = {ACS Full Text PDF w/ Links:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/QMMXAKHI/Godínez et al. - 1997 - Thermodynamic Studies on the Cyclodextrin Complexa.pdf:application/pdf;ACS Full Text Snapshot:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/I54V7VFT/jp970359i.html:text/html} } +@article{yin_overview_2016, + title = {Overview of the {{SAMPL5}} Host\textendash{}guest Challenge: {{Are}} We Doing Better?}, + issn = {0920-654X, 1573-4951}, + shorttitle = {Overview of the {{SAMPL5}} Host\textendash{}guest Challenge}, + doi = {10.1007/s10822-016-9974-4}, + abstract = {The ability to computationally predict protein-small molecule binding affinities with high accuracy would accelerate drug discovery and reduce its cost by eliminating rounds of trial-and-error synthesis and experimental evaluation of candidate ligands. As academic and industrial groups work toward this capability, there is an ongoing need for datasets that can be used to rigorously test new computational methods. Although protein\textendash{}ligand data are clearly important for this purpose, their size and complexity make it difficult to obtain well-converged results and to troubleshoot computational methods. Host\textendash{}guest systems offer a valuable alternative class of test cases, as they exemplify noncovalent molecular recognition but are far smaller and simpler. As a consequence, host\textendash{}guest systems have been part of the prior two rounds of SAMPL prediction exercises, and they also figure in the present SAMPL5 round. In addition to being blinded, and thus avoiding biases that may arise in retrospective studies, the SAMPL challenges have the merit of focusing multiple researchers on a common set of molecular systems, so that methods may be compared and ideas exchanged. The present paper provides an overview of the host\textendash{}guest component of SAMPL5, which centers on three different hosts, two octa-acids and a glycoluril-based molecular clip, and two different sets of guest molecules, in aqueous solution. A range of methods were applied, including electronic structure calculations with implicit solvent models; methods that combine empirical force fields with implicit solvent models; and explicit solvent free energy simulations. The most reliable methods tend to fall in the latter class, consistent with results in prior SAMPL rounds, but the level of accuracy is still below that sought for reliable computer-aided drug design. Advances in force field accuracy, modeling of protonation equilibria, electronic structure methods, and solvent models, hold promise for future improvements.}, + language = {en}, + timestamp = {2016-09-22T21:04:27Z}, + urldate = {2016-09-22}, + journal = {J Comput Aided Mol Des}, + author = {Yin, Jian and Henriksen, Niel M. and Slochower, David R. and Shirts, Michael R. and Chiu, Michael W. and Mobley, David L. and Gilson, Michael K.}, + month = sep, + year = {2016}, + keywords = {CBClip,host–guest complexation,OctaAcid,overview,SAMPL,SAMPL5}, + pages = {1--19}, + file = {Full Text PDF:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/22989I64/Yin et al. - 2016 - Overview of the SAMPL5 host–guest challenge Are w.pdf:application/pdf;Snapshot:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/5NTTWBRW/s10822-016-9974-4.html:text/html} +} + +@misc{Abel:2016:vertex, + address = {Boston, MA}, + title = {Accelerating Drug Discovery with Free Energy Calculations}, + timestamp = {2016-11-17T19:43:12Z}, + urldate = {2016-11-17}, + author = {Abel, Robert}, + month = may, + year = {2016}, + file = {Vertex_talk_5_15_2016_clean3.pdf:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/4NKZGMWC/Vertex_talk_5_15_2016_clean3.pdf:application/pdf} +} + +@article{Gathiaka:2016:JComputAidedMolDes, + title = {{{D3R}} Grand Challenge 2015: {{Evaluation}} of Protein\textendash{}ligand Pose and Affinity Predictions}, + volume = {30}, + issn = {0920-654X, 1573-4951}, + shorttitle = {{{D3R}} Grand Challenge 2015}, + doi = {10.1007/s10822-016-9946-8}, + abstract = {The Drug Design Data Resource (D3R) ran Grand Challenge 2015 between September 2015 and February 2016. Two targets served as the framework to test community docking and scoring methods: (1) HSP90, donated by AbbVie and the Community Structure Activity Resource (CSAR), and (2) MAP4K4, donated by Genentech. The challenges for both target datasets were conducted in two stages, with the first stage testing pose predictions and the capacity to rank compounds by affinity with minimal structural data; and the second stage testing methods for ranking compounds with knowledge of at least a subset of the ligand\textendash{}protein poses. An additional sub-challenge provided small groups of chemically similar HSP90 compounds amenable to alchemical calculations of relative binding free energy. Unlike previous blinded Challenges, we did not provide cognate receptors or receptors prepared with hydrogens and likewise did not require a specified crystal structure to be used for pose or affinity prediction in Stage 1. Given the freedom to select from over 200 crystal structures of HSP90 in the PDB, participants employed workflows that tested not only core docking and scoring technologies, but also methods for addressing water-mediated ligand\textendash{}protein interactions, binding pocket flexibility, and the optimal selection of protein structures for use in docking calculations. Nearly 40 participating groups submitted over 350 prediction sets for Grand Challenge 2015. This overview describes the datasets and the organization of the challenge components, summarizes the results across all submitted predictions, and considers broad conclusions that may be drawn from this collaborative community endeavor.}, + language = {en}, + timestamp = {2016-11-17T19:54:35Z}, + number = {9}, + urldate = {2016-11-17}, + journal = {J Comput Aided Mol Des}, + author = {Gathiaka, Symon and Liu, Shuai and Chiu, Michael and Yang, Huanwang and Stuckey, Jeanne A. and Kang, You Na and Delproposto, Jim and Kubish, Ginger and Dunbar, James B. and Carlson, Heather A. and Burley, Stephen K. and Walters, W. Patrick and Amaro, Rommie E. and Feher, Victoria A. and Gilson, Michael K.}, + month = sep, + year = {2016}, + pages = {651--668}, + file = {Full Text PDF:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/XD77JTXE/Gathiaka et al. - 2016 - D3R grand challenge 2015 Evaluation of protein–li.pdf:application/pdf;Snapshot:/Users/dmobley/Library/Application Support/Zotero/Profiles/i2jd8b87.default/zotero/storage/I6GRFPMA/s10822-016-9946-8.html:text/html} +} + @comment{jabref-meta: groupsversion:3;} @comment{jabref-meta: groupstree: 0 AllEntriesGroup:; @@ -3030,15 +3061,15 @@ @comment{jabref-meta: 1 ExplicitGroup:CB7\;0\;henriksen_computational_2015\;monroe_convergin g_2014\;fenley_bridging_2014\;yin_toward_2015\;muddana_blind_2014\;mog haddam_new_2011\;gilson_stress_2010\;moghaddam_hostguest_2009\;wyman_c -ucurbituril_2008\;gao_binding_2015\;isaacs_cucurbit[n]urils:_2009\;ngu -yen_grid_2012\;cao_absolute_2014\;muddana_prediction_2012\;schreiner_t -heoretical_2016\;hsiao_prediction_2014\;mock_structure_1986\;mock_host --guest_1983\;lee_deciphering_2015\;muddana_sampl4_2014\;rekharsky_synt -hetic_2007\;liu_cucurbituril_2005\;muddana_sampl3_2012\;rogers_role_20 -13\;cao_attomolar_2014\;jang_cucurbit[7]uril:_2014\;freeman_cucurbitur -il_1981\;velez-vega_force_2012\;velez-vega_overcoming_2013\;cong_synth -esis_2016\;vinciguerra_synthesis_2015\;assaf_cucurbiturils:_2015\;lee_ -cucurbituril_2003\;; 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+1 ExplicitGroup:OctaAcid\;0\;monroe_converging_2014\;gibb_well-defined +_2004\;sokkalingam_binding_2016\;carnegie_anion_2014\;ewell_water_2008 +\;wanjari_simulation_2013\;gallicchio_bedam_2015-1\;gibb_anion_2011\;s +un_calorimetric_2008\;mikulskis_free-energy_2014\;gibb_guests_2009\;Xi +:1998:Chem.Commun.\;gan_nonmonotonic_2011\;gibb_binding_2013\;bhakat_r +esolving_2016\;pal_combined_2016\;yin_sampl5_2016\;bosisio_blinded_201 +6\;tofoleanu_absolute_2016\;wang_itc_2016\;muddana_sampl4_2014\;sulliv +an_binding_2016\;mosca_preparative_2016\;hillyer_synthesis_2016\;; 1 ExplicitGroup:others\;0\;smith_dihydropyrancarboxamides_1998\;michel _protein_2006\;kerry_structural_2013\;maurer_calculation_2016\;tame_cr ystal_1995\;davies_relating_1999\;sleigh_crystallographic_1999\;kaus_h @@ -3080,7 +3110,8 @@ @comment{jabref-meta: _2015\;calabro_elucidation_2016\;baum_non-additivity_2010\;calabro_acc elerating_2015\;; 1 ExplicitGroup:trypsin\;0\;plattner_protein_2015\;talhout_understandi -ng_2003\;skillman_sampl3_2012\;newman_dingo_2011\;de_ruiter_efficient_ -2012\;jiao_calculation_2008\;villa_sampling_2003\;jiao_trypsin_2009\;; +ng_2003\;skillman_sampl3_2012\;Newman:2011:JComputAidedMolDes\;de_ruit +er_efficient_2012\;jiao_calculation_2008\;villa_sampling_2003\;jiao_tr +ypsin_2009\;; } diff --git a/paper/benchmarkset.tex b/paper/benchmarkset.tex index 8c3b52d..0af3801 100644 --- a/paper/benchmarkset.tex +++ b/paper/benchmarkset.tex @@ -85,7 +85,7 @@ \subsection{Imagining a tool for drug discovery} If synthesizing and testing each compound takes several days, this workflow compresses roughly a year's work into a few days. -While this workflow is not yet a reality, huge strides have been made in this direction, with calculated binding affinity predictions now showing real promise~\cite{mobley_perspective_2012, christ_accuracy_2014, deng_distinguishing_2015, sherborne_preprint_2016, schrodinger_accurate_2015, christ_binding_2016, cui_affinity_2016, verras_free_2016}, solubility predictions beginning to come online~\cite{schnieders_structure_2012, park_absolute_2014, liu_using_2016}, and predicted drug resistance/selectivity also apparently tractable~\cite{leonis_contribution_2013, leonis_contribution_2013}, with some headway apparent on membrane permeability~\cite{lee_permeability_2016, comer_permeability_2014}. +While this workflow is not yet a reality, huge strides have been made in this direction, with calculated binding affinity predictions now showing real promise~\cite{mobley_perspective_2012, christ_accuracy_2014, deng_distinguishing_2015, sherborne_preprint_2016, schrodinger_accurate_2015, christ_binding_2016, cui_affinity_2016, verras_free_2016}, solubility predictions beginning to come online~\cite{Schnieders:2012:J.Chem.TheoryComput., park_absolute_2014, liu_using_2016}, and predicted drug resistance/selectivity also apparently tractable~\cite{leonis_contribution_2013, leonis_contribution_2013}, with some headway apparent on membrane permeability~\cite{lee_permeability_2016, comer_permeability_2014}. A considerable amount of science and engineering still remains to make this vision a reality, but, given recent progress, the question now seems more one of \emph{when} rather than \emph{whether}. \subsection{Increasing accuracy will yield increasing payoffs} @@ -119,12 +119,12 @@ \subsection{Overview of free energy calculations} Physical pathway methods provide the standard binding free energy by computing the reversible work of, in effect, pulling the ligand out of the binding site. Although, by definition, the pathway used must be a physical one that could occur in nature, it need not be probable, and improbable pathways, governed by an order parameter specifying how far the ligand is from the binding site, are often used~\cite{woo_calculation_2005, ytreberg_absolute_2009, velez-vega_overcoming_2013, henriksen_computational_2015, hsiao_prediction_2014, bhakat_resolving_2016}. In addition, artificial restraints may be useful to avoid sampling problems in the face of often complex barriers along the pathway ~\cite{woo_calculation_2005, velez-vega_overcoming_2013, henriksen_computational_2015, hsiao_prediction_2014, bhakat_resolving_2016}. -By contrast, alchemical pathway methods artificially decouple the ligand from the binding site and then recouple it to solution from the protein~\cite{jorgensen_efficient_1988, hermans_free_1986, gilson_statistical-thermodynamic_1997, boresch_absolute_2003, mobley_use_2006}. +By contrast, alchemical pathway methods artificially decouple the ligand from the binding site and then recouple it to solution from the protein~\cite{jorgensen_efficient_1988, Hermans:1986:Isr.J.Chem., gilson_statistical-thermodynamic_1997, boresch_absolute_2003, mobley_use_2006}. Although alchemical decoupling methods may avoid clashes of the ligand with the protein that might be problematic in pathway methods for a tight binding site, they still can pose some of the same sampling challenges. For example, sampling of the unbound receptor must be adequate after the ligand is removed, and water molecules must have time to equilibrate in the vacated binding site. -Given that free energy is a state function, it is not surprising that alchemical and physical pathway approaches yield apparently comparable results when applied to the same systems~\cite{lee_calculation_2006, gumbart_standard_2013, de_ruiter_proteinligand_2013, yin_sampl5_preprint}. +Given that free energy is a state function, it is not surprising that alchemical and physical pathway approaches yield apparently comparable results when applied to the same systems~\cite{lee_calculation_2006, gumbart_standard_2013, de_ruiter_proteinligand_2013, yin_overview_2016}. -The second general approach computes the difference between the binding free energies of two different ligands for the same receptor, by computing the work of artificially converting one ligand into another, first in the bound state and then free in solution \cite{tembe_ligand_1984, michel_prediction_2010, christ_basic_2010, chodera_alchemical_2011}. +The second general approach computes the difference between the binding free energies of two different ligands for the same receptor, by computing the work of artificially converting one ligand into another, first in the bound state and then free in solution \cite{Tembe:1984:ComputChem, michel_prediction_2010, christ_basic_2010, chodera_alchemical_2011}. Because these conversions are not physically realizable, such calculations are, again, called alchemical. These calculations can be quite efficient if the two ligands are very similar to each other, but they become more complicated and pose greater sampling problems if the two ligands are very different chemically or if there is a high barrier to interconversion between their most stable bound conformations ~\cite{liu_lead_2013}. In addition, there may be concerns about slow conformational relaxation of the protein in response to the change in ligand. Nonetheless, alchemical relative free energy calculations currently are the best automated and most widely used free energy methods~\cite{mobley_perspective_2012, liu_lead_2013, schrodinger_accurate_2015}. @@ -150,7 +150,7 @@ \subsection{Challenges and the domain of applicability} \end{itemize} \vspace{2mm} -Beyond this domain of applicability---whose dimensions are, in fact, still somewhat vague --- substantial challenges may be encountered. +Beyond this domain of applicability---whose dimensions are, in fact, still somewhat vague~\cite{Abel:2016:vertex} --- substantial challenges may be encountered. For example, binding free energy calculations for a cytochrome C peroxidase mutant suggest limitations of fixed-charge force fields. In this case, the strength of electrostatic interactions in a buried, relatively nonpolar binding site appears to be overestimated by a conventional fixed-charge force field, likely due to underestimation of polarization effects~\cite{rocklin_blind_2013}. Sampling problems are also common, with slow sidechain rearrangements and ligand binding mode rearrangements in model binding sites in T4 lysozyme posing timescale problems unless enhanced or biased sampling methods are carefully applied~\cite{mobley_confine_2007, boyce_predicting_2009, mobley_predicting_2007, jiang_free_2010, gallicchio_binding_2010, wang_achieving_2012}; and larger-scale protein motions induced by some ligands also posing challenges~\cite{boyce_predicting_2009, lim_sensitivity_2016}. @@ -170,7 +170,7 @@ \section{THE NEED FOR WELL-CHOSEN BENCHMARK SYSTEMS} Although tests of individual free energy methods are not uncommon today~\cite{mikulskis_large-scale_2014, schrodinger_accurate_2015, christ_binding_2016, cui_affinity_2016, verras_free_2016}, the use of nonoverlapping molecular systems and computational protocols makes it difficult to compare methods on a rigorous basis. In addition, few studies are designed to identify key sources of error and thereby focus future research and development. A few molecular systems have now emerged as \emph{de facto} standards for general study (Section~\ref{benchmarks}). -These selections result in part from two series of blinded prediction challenges (SAMPL~\cite{muddana_sampl4_2014}, and CSAR~\cite{dunbar_csar_2011} followed by D3R~\cite{gathiaka_d3r_2016}), which have helped focus the computational chemistry community on a succession of test cases and highlighted the need for methodological improvements. +These selections result in part from two series of blinded prediction challenges (SAMPL~\cite{muddana_sampl4_2014}, and CSAR~\cite{dunbar_csar_2011} followed by D3R~\cite{Gathiaka:2016:JComputAidedMolDes}), which have helped focus the computational chemistry community on a succession of test cases and highlighted the need for methodological improvements. However, broader adoption of a larger and more persistent set of test cases is needed. By coalescing around a compact set of benchmarks, well chosen to challenge and probe free energy calculations, practitioners and developers will be able to better assess and drive progress in binding free energy calculations. @@ -280,7 +280,7 @@ \subsection{Host-guest benchmarks} For example, all members of the cyclodextrin family are chiral rings of glucose monomers; family members then differ in the number of monomers and in the presence or absence of various chemical substituents. For tests of computational methods ultimately aimed at predicting protein-ligand binding affinities in aqueous solution, water soluble hosts are, arguably, most relevant. On the other hand, host-guest systems in organic solvents may usefully test how well force fields work in the nonaqueous environment within a lipid membrane. -Here, we focus on two host families, the cucurbiturils \cite{freeman_cucurbituril_1981,mock_host-guest_1983}; and the octa-acids (more generally, Gibb deep cavity cavitands)~\cite{gibb_well-defined_2004, hillyer_synthesis_2016}, which have already been the subject of concerted attention from the simulation community, due in part to their use in the SAMPL blinded prediction challenges~\cite{muddana_sampl3_2012, muddana_sampl4_2014, yin_sampl5_preprint}. +Here, we focus on two host families, the cucurbiturils \cite{freeman_cucurbituril_1981,mock_host-guest_1983}; and the octa-acids (more generally, Gibb deep cavity cavitands)~\cite{gibb_well-defined_2004, hillyer_synthesis_2016}, which have already been the subject of concerted attention from the simulation community, due in part to their use in the SAMPL blinded prediction challenges~\cite{muddana_sampl3_2012, muddana_sampl4_2014, yin_overview_2016}. \begin{figure*} \includegraphics[width=\textwidth]{figures/hosts.pdf} @@ -292,7 +292,7 @@ \subsubsection{Cucurbiturils} The cucurbiturils ({\bf Figure~\ref{hosts}}) are achiral rings of glycoluril monomers~\cite{freeman_cucurbituril_1981}. The first characterized family member, cucurbit[6]uril, has six glycoluril units, and subsequent synthetic efforts led to the five-, seven-, eight- and ten-monomer versions, cucurbit[n]uril (n=5,6,7,8,10)~\cite{liu_cucurbituril_2005}, which have been characterized to different extents. Of note, the n=6,7,8 variants accommodate guests of progressively larger size, but are consistent in preferring to bind guests with a hydrophobic core sized to fit snugly into the relatively nonpolar binding cavity, along with at least one cationic moiety (though neutral compounds do bind~\cite{wyman_cucurbituril_2008, lee_deciphering_2015}) that forms stabilizing interactions with the oxygens of the carbonyl groups fringing both portals of the host~\cite{liu_cucurbituril_2005}. -Although derivatives of these parent compounds, have been made \cite{lee_cucurbituril_2003, vinciguerra_synthesis_2015, assaf_cucurbiturils:_2015, cong_synthesis_2016}, +Although derivatives of these parent compounds, have been made \cite{Lee:2003:AccountsofChemicalResearch, vinciguerra_synthesis_2015, assaf_cucurbiturils:_2015, Cong:2016:Org.Biomol.Chem.}, most of the binding data published for this class of hosts pertain to the non-derivatized forms. @@ -416,7 +416,7 @@ \subsubsection{Gibb Deep Cavity Cavitands (GDCC)} The octa-acids (OA) ({\bf Figure~\ref{hosts}}) are synthetic hosts with deep, basket-shaped, hydrophobic binding sites~\cite{gibb_well-defined_2004}. The eight carboxylic acidic groups for which they were originally named make these hosts water-soluble, but do not interact directly with bound hosts; instead, they project outward into solvent. Binding data have been reported for the original form of this host (OA)~\cite{gibb_well-defined_2004} and for a derivative with four added methyl groups at equivalent locations in the entryway, where they can contact a bound guest (TEMOA)~\cite{gan_nonmonotonic_2011, sullivan_binding_2016}. -(Note that OA and TEMOA have also been called OAH and OAMe, respectively~\cite{yin_sampl5_preprint}.) +(Note that OA and TEMOA have also been called OAH and OAMe, respectively~\cite{yin_overview_2016}.) Additional family members with other substituents around the portal have been reported, as has a new series in which the eponymic carboxylic groups are replaced by various other groups, including a number of basic amines~\cite{hillyer_synthesis_2016}. However, we are not aware of binding data for these derivatives. In view of these other hosts, however, we propose the more general name Gibb deep cavity cavitands (GDCCs) for this family of hosts. @@ -436,13 +436,13 @@ \subsubsection{Gibb Deep Cavity Cavitands (GDCC)} Second, elongated guests can generate ternary complexes, in which two OA hosts encapsulate one guest, especially if both ends of the guest are not very polar~\cite{gibb_guests_2009}. \paragraph{The proposed GDCC benchmark sets are drawn from SAMPL} -As a core benchmark series for this family, we propose two sets which formed part of the SAMPL4 and SAMPL5 challenges, based on adamantane derivatives (Table~\ref{gdcc_benchmark1}) and cyclic (aromatic and saturated) carboxylic acids (Table~\ref{gdcc_benchmark2}) binding to hosts OA and TEMOA with free energies of -3.7 to -7.6 kcal/mol. These cases offer aqueous binding data with a reasonably broad range of binding free energies, frequently along with binding enthalpies; the hosts and many or all of their guests are small and rigid enough to allow convincing convergence of binding thermodynamics with readily feasible simulations; and, like the cucurbiturils, they are already emerging as \emph{de facto} computational benchmarks, due to their use in the SAMPL4 and SAMPL5 challenges~\cite{muddana_sampl4_2014, yin_sampl5_preprint}. +As a core benchmark series for this family, we propose two sets which formed part of the SAMPL4 and SAMPL5 challenges, based on adamantane derivatives (Table~\ref{gdcc_benchmark1}) and cyclic (aromatic and saturated) carboxylic acids (Table~\ref{gdcc_benchmark2}) binding to hosts OA and TEMOA with free energies of -3.7 to -7.6 kcal/mol. These cases offer aqueous binding data with a reasonably broad range of binding free energies, frequently along with binding enthalpies; the hosts and many or all of their guests are small and rigid enough to allow convincing convergence of binding thermodynamics with readily feasible simulations; and, like the cucurbiturils, they are already emerging as \emph{de facto} computational benchmarks, due to their use in the SAMPL4 and SAMPL5 challenges~\cite{muddana_sampl4_2014, yin_overview_2016}. \paragraph{OA introduces new challenges beyond CB7} Issues deserving attention when interpreting the experimental data and calculating the binding thermodynamics of these systems include the following: \begin{enumerate} \item{{\bf Tight exit portal}: The methyl groups of the TEMOA variant narrow the entryway and can generate a barrier to the entry or exit of guest molecules with bulky hydrophobic cores, though the degree of constriction is not as marked as for CB7 (above). -The TEMOA methyls groups can additionally hinder sampling of guest poses in the bound state, leading to convergence problems~\cite{yin_sampl5_preprint} specific to TEMOA. } +The TEMOA methyls groups can additionally hinder sampling of guest poses in the bound state, leading to convergence problems~\cite{yin_overview_2016} specific to TEMOA. } \item{{\bf Host conformational sampling}: Although the flexible propionate groups are not proximal to the binding cavity, they are charged and so can have long-ranged interactions. As a consequence, it may be important to ensure their conformations are well sampled, though motions may be slow~\cite{mikulskis_free-energy_2014}. @@ -489,7 +489,7 @@ \subsubsection{Gibb Deep Cavity Cavitands (GDCC)} 8 / OA-G5 & trimethylphenethylaminium & 14108 & \parbox[c]{1em}{\includegraphics[scale=0.15]{figures/14108.pdf}} & C[N+](C)(C)CCC1=CC=CC=C1 & {ND$^{\rm e}$} & {ND$^{\rm e}$} \\ \bottomrule \end{tabular}\\ -$^{\rm a}$ Compound ID from ~\cite{sullivan_binding_2016} and SAMPL5 ID from ~\cite{yin_sampl5_preprint}; $^{\rm b}$ PubChem Compound ID; $^{\rm c}$ Standard binding free energy from~\cite{sullivan_binding_2016}, where all measurements were done via ITC in 50 mM sodium phosphate buffer at pH 11.5 and 298 K. Uncertainties, drawn from the experimental paper, were computed from triplicate measurements taken with freshly made solutions of host and guest. However, based on personal communication with the authors, it may be advisable to regard the accuracy more conservatively, at $\sim$2\% for $\Delta$G and $\sim$6\% for $\Delta$H; $^{\rm d}$ measured binding enthalpy~\cite{sullivan_binding_2016}, subject to the same conditions/caveats as $^{\rm c}$. $^{\rm e}$ not done. +$^{\rm a}$ Compound ID from ~\cite{sullivan_binding_2016} and SAMPL5 ID from ~\cite{yin_overview_2016}; $^{\rm b}$ PubChem Compound ID; $^{\rm c}$ Standard binding free energy from~\cite{sullivan_binding_2016}, where all measurements were done via ITC in 50 mM sodium phosphate buffer at pH 11.5 and 298 K. Uncertainties, drawn from the experimental paper, were computed from triplicate measurements taken with freshly made solutions of host and guest. However, based on personal communication with the authors, it may be advisable to regard the accuracy more conservatively, at $\sim$2\% for $\Delta$G and $\sim$6\% for $\Delta$H; $^{\rm d}$ measured binding enthalpy~\cite{sullivan_binding_2016}, subject to the same conditions/caveats as $^{\rm c}$. $^{\rm e}$ not done. \end{table*} \endgroup @@ -520,7 +520,7 @@ \subsubsection{Gibb Deep Cavity Cavitands (GDCC)} %SAMPLING As noted, two different host conformational sampling issues have been observed, with dihedral transitions for the proprionate groups occurring on 1-2 ns timescales~\cite{mikulskis_free-energy_2014}); motions of the benzoic acid flaps were also relatively slow~\cite{yin_sampl5_2016, tofoleanu_absolute_2016} though perhaps thermodynamically unimportant. -Guest sampling can also be an issue, at least in TEMOA~\cite{yin_sampl5_preprint}, and this hosts's tight cavity may also have implications for binding entropy~\cite{yin_sampl5_2016}. +Guest sampling can also be an issue, at least in TEMOA~\cite{yin_overview_2016}, and this hosts's tight cavity may also have implications for binding entropy~\cite{yin_sampl5_2016}. % SYSTEM: Salt concentration strongly modulates binding affinity, at least for anions, and the nature of the salt also plays an important role~\cite{carnegie_anion_2014}. @@ -538,7 +538,7 @@ \subsubsection{Gibb Deep Cavity Cavitands (GDCC)} %The challenges of system definition and conformational sampling appear to be greater for OA and TEMOA than for CB7, , so evidence of force field limitations, if present, is not yet as clear. There have been some comparisons of charge~\cite{mikulskis_free-energy_2014, muddana_sampl4_2014, monroe_converging_2014} and water models~\cite{yin_sampl5_2016}, but differences so far seem mostly inconclusive or at least not that large. Similarly, OPLS and GAFF results did not appear dramatically different in accuracy~\cite{bhakat_resolving_2016} %The above paragraph could be cut for space if we need -Several groups used different methods but the same force field and water model in SAMPL5, with rather varied levels of success because of discrepancies in calculated free energies~\cite{yin_sampl5_preprint, bosisio_blinded_2016, bhakat_resolving_2016}. +Several groups used different methods but the same force field and water model in SAMPL5, with rather varied levels of success because of discrepancies in calculated free energies~\cite{yin_overview_2016, bosisio_blinded_2016, bhakat_resolving_2016}. However, some of these issues were resolved in follow-up work~\cite{bhakat_resolving_2016}, bringing the methods into fairly good agreement for the majority of cases~\cite{yin_sampl5_2016, bosisio_blinded_2016}. \subsection{Protein-ligand benchmarks: the T4 lysozyme model binding sites} @@ -719,6 +719,7 @@ \section{CONCLUSIONS AND OUTLOOK} Hopefully, these systems will serve as challenging standard test cases for new methods, force fields, protocols, and workflows. Our desire is that these benchmarks will advance the science and technology of modeling and predicting molecular interactions, and that other researchers in the field will contribute to identifying new benchmark sets and updating the information provided about these informative systems. + \section*{DISCLOSURE STATEMENT} D.L.M. is a member of the Scientific Advisory Board for Schr\"{o}dinger, LLC. M.K.G. is a cofounder and has equity interest in the company VeraChem LLC. From 4c9ba5b388605017b1c87228f5b220feb0689313 Mon Sep 17 00:00:00 2001 From: davidlmobley Date: Thu, 17 Nov 2016 12:01:54 -0800 Subject: [PATCH 3/5] Add bindingdb HG link in one place. --- paper/benchmarkset.tex | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/paper/benchmarkset.tex b/paper/benchmarkset.tex index 0af3801..cccd84d 100644 --- a/paper/benchmarkset.tex +++ b/paper/benchmarkset.tex @@ -274,7 +274,7 @@ \subsection{Host-guest benchmarks} Moreover, their small size, and, in many cases, their rigidity, can make it feasible to sample all relevant conformations, making for ``hard" benchmarks as defined above (Section~\ref{subsec:benchmarktypes}). Furthermore, experiments can often be run under conditions that make the protonation states of the host and guest unambiguous. Under these conditions, the level of agreement of correctly executed calculations with experiment effectively reports on the validity of the force field (Section~\ref{pgph:accuracy}. For a number of host-guest systems, the use of isothermal titration calorimetry (ITC) to characterize binding provides both binding free energies and binding enthalpies. -Binding enthalpies can often also be computed to good numerical precision~\cite{henriksen_computational_2015}, so they provide an additional check of the validity of simulations. +Binding enthalpies can often also be computed to good numerical precision~\cite{henriksen_computational_2015}, so they provide an additional check of the validity of simulations. A variety of curated host-guest binding data is available on BindingDB at \url{http://bindingdb.org/bind/HostGuest.jsp}. Hosts fall into chemical families, such that all members of each family share a major chemical motif, but individuals vary in terms of localized chemical substitutions and, in some families, the number of characteristic monomers they comprise. For example, all members of the cyclodextrin family are chiral rings of glucose monomers; family members then differ in the number of monomers and in the presence or absence of various chemical substituents. From fd578dbad5e40d281d8e461d1a30c60c24edf8c5 Mon Sep 17 00:00:00 2001 From: davidlmobley Date: Thu, 17 Nov 2016 12:02:16 -0800 Subject: [PATCH 4/5] Remove some comments --- paper/benchmarkset.tex | 12 ------------ 1 file changed, 12 deletions(-) diff --git a/paper/benchmarkset.tex b/paper/benchmarkset.tex index cccd84d..c170909 100644 --- a/paper/benchmarkset.tex +++ b/paper/benchmarkset.tex @@ -347,18 +347,6 @@ \subsubsection{Cucurbiturils} Despite its apparent simplicity, CB7 is still a challenging benchmark that can put important issues into high relief. For example, in SAMPL4, free energy methods yielded $R^2$ values from 0.1 to 0.8 and RMS errors of about 1.9 to 4.9 kcal/mol for the same set of CB7 cases. This spread of results across rather similar methods highlights the need for shared benchmarks. Potential explanations include convergence difficulties, subtle methodological differences, and details of how the methods were applied~\cite{muddana_sampl4_2014}. Until the origin of such discrepancies is clear, it is difficult to know how accurate our methods truly are. -% Changes -% Used booktabs for formatting (may not be completely compatible with revtex...). -% Used siunitx to format the numbers and set automatic alignment with uncertainty. -% Changed the width of the figures to be a scale factor, so common chemical features are constant size for all compounds. -% To make room for the new figures, I chagned the column to type `p`. -% Used \ttfamily for the SMILES strings. -% Used multicolumn to center the titles, even though the text is left aligned. -% Added superscript annotation in another column. -% Fixed casing so all compounds are lowercase unless started with a symbol or element. -% Got rid of \tabcolsep -% Aligned the table in auctex. - \begingroup \squeezetable \begin{table*} From 4e7c412c1c41d2cec38c9d0a81f2e3382dc7ebd1 Mon Sep 17 00:00:00 2001 From: davidlmobley Date: Thu, 17 Nov 2016 12:03:25 -0800 Subject: [PATCH 5/5] Add second link to HG bindingDB data --- paper/benchmarkset.tex | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/paper/benchmarkset.tex b/paper/benchmarkset.tex index c170909..d853385 100644 --- a/paper/benchmarkset.tex +++ b/paper/benchmarkset.tex @@ -293,7 +293,7 @@ \subsubsection{Cucurbiturils} which have been characterized to different extents. Of note, the n=6,7,8 variants accommodate guests of progressively larger size, but are consistent in preferring to bind guests with a hydrophobic core sized to fit snugly into the relatively nonpolar binding cavity, along with at least one cationic moiety (though neutral compounds do bind~\cite{wyman_cucurbituril_2008, lee_deciphering_2015}) that forms stabilizing interactions with the oxygens of the carbonyl groups fringing both portals of the host~\cite{liu_cucurbituril_2005}. Although derivatives of these parent compounds, have been made \cite{Lee:2003:AccountsofChemicalResearch, vinciguerra_synthesis_2015, assaf_cucurbiturils:_2015, Cong:2016:Org.Biomol.Chem.}, -most of the binding data published for this class of hosts pertain to the non-derivatized forms. +most of the binding data published for this class of hosts pertain to the non-derivatized forms. A fairly extensive set of data is available in BindingDB at \url{http://bindingdb.org/bind/HostGuest.jsp}. We propose cucurbit[7]uril (CB7) as the basis of one series of host-guest benchmark systems ({\bf Figure~\ref{hosts}}, {\bf Tables~\ref{cb7_benchmark1} and~\ref{cb7_benchmark2}}).