Protein-ligand binding enthalpies from near-millisecond simulations: Analysis of a preorganization paradox
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Abstract
Calorimetric studies of protein-ligand binding sometimes yield thermodynamic data that are difficult to understand. Today, molecular simulations can be used to seek insight into such calorimetric puzzles, and, when simulations and experiments diverge, the results can usefully motivate further improvements in computational methods. Here, we apply near-millisecond duration simulations to estimate the relative binding enthalpies of four peptidic ligands with the Grb2 SH2 domain. The ligands fall into matched pairs, where one member of each pair has an added bond that preorganizes the ligand for binding and thus may be expected to favor binding entropically, due to a smaller loss in configurational entropy. Calorimetric studies have shown that the constrained ligands do in fact bind the SH2 domain more tightly than the flexible ones, but, paradoxically, the improvement in affinity for the constrained ligands is enthalpic, rather than entropic. The present enthalpy calculations yield the opposite trend, as they suggest that the flexible ligands bind more exothermically. Additionally, the small relative binding enthalpies are found to be balances of large differences in the energies of structural components such as ligand and the binding site residues. As a consequence, the deviations from experiment in the relative binding enthalpies represent small differences between these large numbers and hence may be particularly susceptible to error, due, for example, to approximations in the force field. We also computed first-order estimates of changes in configurational entropy on binding. These too are, arguably, paradoxical, as they tend to favor binding of the flexible ligands. The paradox is explained in part by the fact that the more rigid constrained ligands reduce the entropy of binding site residues more than their flexible analogs do, at least in the simulations. This result offers a rather general counterargument to the expectation that preorganized ligands should be associated with more favorable binding entropies, other things being equal.
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While the path-based PMF approach appears more tractable, it is still difficult to obtain converged free energy estimates for large biomolecules with complex geometries.
“While the path-based PMF approach appears more tractable, it is still difficult to obtain converged free energy estimates for large biomolecules with complex geometries.53,62−68”
From Assessment of the Topology and Oligomerisation States of Coiled Coils Using Metadynamics with Conformational Restraints (2025) · cites this paper as [68]
Cites
Berman, H. M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.235 · Cited by 40,196 · cited 1× · see citing works
“The structures of these ligands in complex with the Grb2 SH2 domain were previously solved [11] and are available in the RSCB PDB[27]: fpYNVN (3C7I) and cpYVN (2HUW); fpYQN (3IMD) and cpYQN (3IN7).”
BackgroundComparison of simple potential functions for simulating liquid water
Jorgensen, W. L., Chandrasekhar, J., Madura, J., Impey, R., & Klein, M. (1983) · The Journal of Chemical Physics · doi:10.1063/1.445869 · Cited by 38,335 · see citing works
Development and testing of a general amber force field
Wang, J.-M., Wolf, R., Caldwell, J., Kollman, P., & Case, D. (2004) · Journal of Computational Chemistry · doi:10.1002/jcc.20035 · Cited by 18,318 · cited 3× · see citing works
“The ff12SB force field[34] was used for the protein, GAFF[35] forcefield parameters were used for HEPES, and forcefield parameters for the phosphotyrosine (PTY) residue were taken from the set determined by Steinbrecher et al[36, 37], as available in the AMBER frcmod.”
MethodAll-Atom Empirical Potential for Molecular Modeling and Dynamics Studies of Proteins
MacKerell, A. D., Bashford, D., Bellott, M., Dunbrack, R. L., Evanseck, J. D., Field, M. J., Fischer, S., Gao, J., Guo, H., Ha, S., et al. (1998) · The Journal of Physical Chemistry B · doi:10.1021/jp973084f · Cited by 14,270 · see citing works
Statistically optimal analysis of samples from multiple equilibrium states.
Shirts, M., & Chodera, J. (2008) · Journal of Chemical Physics · doi:10.1063/1.2978177 · Cited by 1,825 · see citing works
Anandakrishnan, R., Aguilar, B. H., & Onufriev, A. (2012) · Nucleic Acids Res. · doi:10.1093/nar/gks375 · Cited by 1,736 · see citing works
H++: a server for estimating pKas and adding missing hydrogens to macromolecules
Gordon, J. C., Myers, J., Folta, T., Shoja, V., Heath, L. S., & Onufriev, A. (2005) · Nucleic Acids Res. · doi:10.1093/nar/gki464 · Cited by 1,657 · see citing works
Error estimates on averages of correlated data
Flyvbjerg, H., & Petersen, H. (1989) · The Journal of Chemical Physics · doi:10.1063/1.457480 · Cited by 1,471 · cited 2× · see citing works
“Blocking analysis[42] is another approach to estimating the uncertainty of the time series of potential energies, where block-wise SEMs are computed for successively longer blocks of energies.”
MethodCurrent Status of the AMOEBA Polarizable Force Field
Ponder, J. W., Wu, C., Ren, P., Pande, V. S., Chodera, J. D., Schnieders, M. J., Haque, I., Mobley, D. L., Lambrecht, D. S., DiStasio, R. A., et al. (2010) · The Journal of Physical Chemistry B · doi:10.1021/jp910674d · Cited by 1,440 · see citing works
Molecular dynamics simulations and drug discovery
Durrant, J. D., & McCammon, J. A. (2011) · BMC Biology · doi:10.1186/1741-7007-9-71 · Cited by 1,412 · cited 1× · see citing works
“In recent years, advances in molecular simulations have opened new possibilities to study drugprotein binding in atomistic detail [14, 15, 16, 17, 18, 19].”
BackgroundRole of Molecular Dynamics and Related Methods in Drug Discovery
Vivo, M. D., Masetti, M., Bottegoni, G., & Cavalli, A. (2016) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.5b01684 · Cited by 1,330 · see citing works
Long-Time-Step Molecular Dynamics through Hydrogen Mass Repartitioning.
Hopkins, C. W., Grand, S. M. L., Walker, R. C., & Roitberg, A. (2015) · Journal of Chemical Theory and Computation · doi:10.1021/ct5010406 · Cited by 1,317 · cited 2× · see citing works
“With the multiple-GPU version of AMBER PMEMD [28], and long (4 fs) time steps made possible by hydrogen mass repartitioning [29], we were able to achieve up to 450 ns of simulation per day, and generated about 250 μs cumulative simulation time for each bound system.”
MethodThe R.E.D. tools: advances in RESP and ESP charge derivation and force field library building
Dupradeau, F., Pigache, A., Zaffran, T., Savineau, C., Lelong, R., Grivel, N., Lelong, D., Rosanski, W., & Cieplak, P. (2010) · Physical Chemistry Chemical Physics · doi:10.1039/c0cp00111b · Cited by 886 · see citing works
Vanquelef, E., Simon, S., Marquant, G., García, É., Klimerak, G., Delepine, J., Cieplak, P., & Dupradeau, F. (2011) · Nucleic Acids Res. · doi:10.1093/nar/gkr288 · Cited by 795 · see citing works
Efficient Drug Lead Discovery and Optimization
Jorgensen, W. L. (2009) · Accounts of Chemical Research · doi:10.1021/ar800236t · Cited by 651 · see citing works
Shaw, D. E., Grossman, J. P., Bank, J. A., Batson, B., Butts, J. A., Chao, J. C., Deneroff, M. M., Dror, R., Even, A., Fenton, C. H., et al. (2014) · International Conference for High Performance Computing, Networking, Storage and Analysis · doi:10.1109/sc.2014.9 · Cited by 567 · see citing works
Protein structure-based drug design: from docking to molecular dynamics.
Śledź, P., & Caflisch, A. (2018) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2017.10.010 · Cited by 534 · cited 1× · see citing works
“In recent years, advances in molecular simulations have opened new possibilities to study drugprotein binding in atomistic detail [14, 15, 16, 17, 18, 19].”
BackgroundDo enthalpy and entropy distinguish first in class from best in class?
Freire, E. (2008) · Drug Discovery Today · doi:10.1016/j.drudis.2008.07.005 · Cited by 491 · see citing works
Adding calorimetric data to decision making in lead discovery: a hot tip
Ladbury, J., Klebe, G., & Freire, E. (2010) · Nature reviews. Drug discovery · doi:10.1038/nrd3054 · Cited by 401 · cited 1× · see citing works
“It has also been argued that one should aim to design ligands whose binding is enthalpydriven, as these may be better drugs than ones whose binding is entropy-driven [8, 9].”
BackgroundHomeyer, N., Horn, A., Lanig, H., & Sticht, H. (2006) · Journal of Molecular Modeling · doi:10.1007/s00894-005-0028-4 · Cited by 384 · cited 1× · see citing works
“The ff12SB force field[34] was used for the protein, GAFF[35] forcefield parameters were used for HEPES, and forcefield parameters for the phosphotyrosine (PTY) residue were taken from the set determined by Steinbrecher et al[36, 37], as available in the AMBER frcmod.”
MethodMyers, J., Grothaus, G. A., Narayanan, S., & Onufriev, A. (2006) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.20922 · Cited by 367
Advancing Drug Discovery through Enhanced Free Energy Calculations.
Abel, R., Wang, L.-L., Harder, E. D., Berne, B., & Friesner, R. (2017) · Accounts of Chemical Research · doi:10.1021/acs.accounts.7b00083 · Cited by 315 · cited 1× · see citing works
“In recent years, advances in molecular simulations have opened new possibilities to study drugprotein binding in atomistic detail [14, 15, 16, 17, 18, 19].”
BackgroundThe future of molecular dynamics simulations in drug discovery
Borhani, D. W., & Shaw, D. E. (2012) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-011-9517-y · Cited by 313 · cited 1× · see citing works
“In recent years, advances in molecular simulations have opened new possibilities to study drugprotein binding in atomistic detail [14, 15, 16, 17, 18, 19].”
BackgroundCalorimetry and thermodynamics in drug design.
Chaires, J. (2008) · Annual Review of Biophysics · doi:10.1146/annurev.biophys.36.040306.132812 · Cited by 272 · cited 1× · see citing works
“Calorimetric studies of protein-small molecule interactions decompose the standard free energy of binding into the binding enthalpy and entropy—the so-called thermodynamic signature of binding [1, 2, 3, 4].”
BackgroundRevised AMBER parameters for bioorganic phosphates
Steinbrecher, T., Latzer, J., & Case, D. (2012) · Journal of Chemical Theory and Computation · doi:10.1021/ct300613v · Cited by 264 · cited 1× · see citing works
“The ff12SB force field[34] was used for the protein, GAFF[35] forcefield parameters were used for HEPES, and forcefield parameters for the phosphotyrosine (PTY) residue were taken from the set determined by Steinbrecher et al[36, 37], as available in the AMBER frcmod.”
MethodLevy, R., & Gallicchio, E. (1998) · Annual review of physical chemistry (Print) · doi:10.1146/annurev.physchem.49.1.531 · Cited by 220 · see citing works
Extraction of configurational entropy from molecular simulations via an expansion approximation.
Killian, B., Kravitz, J. Y., & Gilson, M. (2007) · Journal of Chemical Physics · doi:10.1063/1.2746329 · Cited by 185 · cited 2× · see citing works
“The configurational entropy, S, may be written as an expansion in terms of first-order terms, pairwise mutual informations, third-order mutual informations, and so forth[45, 46, 47].”
BackgroundSelf-citationPhysical nature of higher-order mutual information: intrinsic correlations and frustration
Matsuda, H. (2000) · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · doi:10.1103/physreve.62.3096 · Cited by 182 · cited 1×
“The configurational entropy, S, may be written as an expansion in terms of first-order terms, pairwise mutual informations, third-order mutual informations, and so forth[45, 46, 47].”
BackgroundThermodynamic Studies for Drug Design and Screening
Garbett, N., & Chaires, J. (2012) · Expert Opinion on Drug Discovery · doi:10.1517/17460441.2012.666235 · Cited by 157 · cited 1×
“These components of the free energy may provide insight into the forces driving binding [5, 6, 7].”
BackgroundA Thermodynamic Approach to the Affinity Optimization of Drug Candidates
Freire, E. (2009) · Chemical Biology and Drug Design · doi:10.1111/j.1747-0285.2009.00880.x · Cited by 139 · cited 1× · see citing works
“Calorimetric studies of protein-small molecule interactions decompose the standard free energy of binding into the binding enthalpy and entropy—the so-called thermodynamic signature of binding [1, 2, 3, 4].”
BackgroundNormal modes and essential dynamics.
Hayward, S., & de Groot, B. L. (2008) · Methods in molecular biology · doi:10.1007/978-1-59745-177-2_5 · Cited by 134 · cited 1×
“PCA is commonly used to determine the essential dynamics of a simulation [43, 44] by reducing the dimensionality of the trajectory motions.”
MethodIsothermal titration calorimetry in drug discovery.
Ward, W., & Holdgate, G. (2001) · Progress in Medicinal Chemistry · doi:10.1016/s0079-6468(08)70097-3 · Cited by 128 · cited 1× · see citing works
“These components of the free energy may provide insight into the forces driving binding [5, 6, 7].”
BackgroundDeLorbe, J. E., Clements, J. H., Teresk, M., Benfield, A., Plake, H. R., Millspaugh, L. E., & Martin, S. (2009) · Journal of the American Chemical Society · doi:10.1021/ja904698q · Cited by 125
Fenley, A. T., Muddana, H. S., & Gilson, M. (2012) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.1213180109 · Cited by 122 · cited 1× · see citing works
“On the other hand, small changes in the chemical structure of a ligand often produce large changes in the binding enthalpy and entropy that are difficult to rationalize [10].”
BackgroundSelf-citationComputational Calorimetry: High-Precision Calculation of Host–Guest Binding Thermodynamics
Henriksen, N. M., Fenley, A. T., & Gilson, M. (2015) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.5b00405 · Cited by 108 · cited 5× · see citing works
“A prior study showed that this approach does not lead to significant differences in computed binding enthalpies[23].”
BackgroundMethodInfluentialSelf-citationFalconer, R. (2016) · Journal of Molecular Recognition · doi:10.1002/jmr.2550 · Cited by 94 · cited 1× · see citing works
“These components of the free energy may provide insight into the forces driving binding [5, 6, 7].”
BackgroundFenley, A. T., Henriksen, N. M., Muddana, H. S., & Gilson, M. (2014) · Journal of Chemical Theory and Computation · doi:10.1021/ct5004109 · Cited by 91 · cited 5× · see citing works
“On the other hand, it is not trivial to obtain temperature-dependent binding free energies that are numerically precise enough to yield numerically precise binding enthalpies; and in fact, the direct approach was found to be considerably more efficient for host-guest binding systems [22] Another advantage of the direc…”
BackgroundMethodInfluentialSelf-citationDeLorbe, J. E., Clements, J. H., Whiddon, B. B., & Martin, S. (2010) · ACS Medicinal Chemistry Letters · doi:10.1021/ml100142y · Cited by 88 · see citing works
Correlating structure and energetics in protein-ligand interactions: paradigms and paradoxes.
Martin, S., & Clements, J. H. (2013) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-060410-105819 · Cited by 85 · cited 2× · see citing works
“This is physically plausible, because a more rigid ligand may constrain the binding site more, as previously suggested[11, 48].”
BackgroundRefined solution structure of the c-terminal DNA-binding domain of human immunovirus-1 integrase
Eijkelenboom, A. P. A. M., Sprangers, R., Hård, K., Lutzke, R. A. P., Plasterk, R. H. A., Boelens, R., & Kaptein, R. (1999) · Proteins Structure Function and Bioinformatics · doi:10.1002/(sici)1097-0134(19990901)36:4 · Cited by 81 · see citing works
Davidson, J. P., Lubman, O., Rose, T., Waksman, G., & Martin, S. (2002) · Journal of the American Chemical Society · doi:10.1021/ja011746f · Cited by 80 · see citing works
Conformational constraint in protein ligand design and the inconsistency of binding entropy.
Udugamasooriya, D. G., & Spaller, M. (2008) · Biopolymers · doi:10.1002/bip.20983 · Cited by 76 · cited 1×
“A better preorganized ligand is expected to binding with higher affinity, all other things being equal, due to a reduced configurational entropy penalty on binding, but calorimetric studies have yielded the opposite result [11, 12, 13].”
ResultHenriksen, N. M., & Gilson, M. (2017) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.7b00359 · Cited by 59 · see citing works
Self-citationIsothermal titration calorimetry: Application to structure-based drug design
Ladbury, J. (2001) · Thermochimica Acta · doi:10.1016/s0040-6031(01)00674-8 · Cited by 59 · cited 1× · see citing works
“Calorimetric studies of protein-small molecule interactions decompose the standard free energy of binding into the binding enthalpy and entropy—the so-called thermodynamic signature of binding [1, 2, 3, 4].”
BackgroundThermodynamic and structural analysis of phosphotyrosine polypeptide binding to Grb2-SH2.
Mcnemar, C., Snow, M. E., Windsor, W., Prongay, A., Mui, P. W., Zhang, R.-M., Durkin, J., Le, H. V., & Weber, P. C. (1997) · Biochemistry · doi:10.1021/bi9704360 · Cited by 54 · cited 1×
“Here, we use the direct enthalpy calculation method to estimate the relative binding enthalpies of constrained and flexible phosphopeptides for the SH2 domain of growth factor receptor protein 2 (Grb2) [26].”
MethodGao, K.-F., Yin, J., Henriksen, N. M., Fenley, A. T., & Gilson, M. (2015) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.5b00676 · Cited by 40 · cited 2×
“In particular, although the binding enthalpy can be challenging to compute, a straightforward direct approach has been shown to yield numerically precise (though not necessarily accurate) results for host-guest systems [20, 21, 22, 23, 24, 25].”
BackgroundSelf-citationShi, Y., Zhu, C. Z., Martin, S., & Ren, P.-Y. Y. (2012) · Journal of Physical Chemistry B · doi:10.1021/jp210265d · Cited by 38
Lu, N., Kofke, D. A., & Woolf, T. (2003) · doi:10.1021/jp027627j · Cited by 37 · cited 1×
“A number of other approaches to computing binding enthalpies have been described [52, 53, 54], of which perhaps the most common is to compute binding free energies at several different temperatures, and then use in effect the van’t Hoff equation to extract the binding enthalpy at a temperature of interest.”
MethodYin, J., Fenley, A. T., Henriksen, N. M., & Gilson, M. (2015) · Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.5b04262 · Cited by 36 · cited 1× · see citing works
“Prior studies have begun to examine the sensitivity of binding enthalpies to the choice of force field parameters[51, 25].”
BackgroundSelf-citationMolecular dynamics simulations of beta-cyclodextrin-aziadamantane complexes in water.
Sellner, B., Zifferer, G., Kornherr, A., Krois, D., & Brinker, U. H. (2008) · Journal of Physical Chemistry B · doi:10.1021/jp075493+ · Cited by 36 · cited 3×
“Relative binding enthalpies (∆∆H) were estimated by the direct method[20, 21, 22], which involves taking differences in mean (Boltzmann-averaged) potential energies for simulated systems of interest.”
BackgroundMethodAdvancements in Molecular Dynamics Simulations of Biomolecules on Graphical Processing Units
Xu, D., Williamson, M., & Walker, R. C. (2010) · doi:10.1016/s1574-1400(10)06001-9 · Cited by 29 · cited 1×
“Continued increases in computational speed, afforded by coprocessors like GPUs[55], and specialized computers like Anton 2[56], may well allow calculations like these to be converged to within 1 kcal/mol uncertainty within the next few years.”
BackgroundWyczalkowski, M., Vitalis, A., & Pappu, R. (2010) · Journal of Physical Chemistry B · doi:10.1021/jp103050u · Cited by 28 · cited 1×
“A number of other approaches to computing binding enthalpies have been described [52, 53, 54], of which perhaps the most common is to compute binding free energies at several different temperatures, and then use in effect the van’t Hoff equation to extract the binding enthalpy at a temperature of interest.”
MethodINFORMATION CONTENT OF SIGNALS USING CORRELATION FUNCTION EXPANSIONS OF THE ENTROPY
Attard, P., Jepps, O. G., & Marčelja, S. (1997) · doi:10.1103/physreve.56.4052 · Cited by 24 · cited 1×
“The configurational entropy, S, may be written as an expansion in terms of first-order terms, pairwise mutual informations, third-order mutual informations, and so forth[45, 46, 47].”
BackgroundRelative Binding Enthalpies from Molecular Dynamics Simulations Using a Direct Method
Roy, A., Hua, D. P., Ward, J. M., & Post, C. (2014) · Journal of Chemical Theory and Computation · doi:10.1021/ct500200n · Cited by 19 · cited 3× · see citing works
“Relative binding enthalpies (∆∆H) were estimated by the direct method[20, 21, 22], which involves taking differences in mean (Boltzmann-averaged) potential energies for simulated systems of interest.”
BackgroundMethodProkopczyk, I. M., Ribeiro, J., Sartori, G., Sesti-Costa, R., Silva, J., Freitas, R. F., Leitão, A., & Montanari, C. (2014) · Future Medicinal Chemistry · doi:10.4155/fmc.13.185 · Cited by 13 · cited 1× · see citing works
“Calorimetric studies of protein-small molecule interactions decompose the standard free energy of binding into the binding enthalpy and entropy—the so-called thermodynamic signature of binding [1, 2, 3, 4].”
Background
Flagged first, then by citations
3 of the 58 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Fu, H., Chen, H., Blazhynska, M., de Lacam, E. G. C., Szczepaniak, F., Pavlova, À., Shao, X., Gumbart, J. C., Dehez, F., Roux, B., et al. (2022) · Nature Protocols · doi:10.1038/s41596-021-00676-1 · Cited by 181 · see citing works
“In the Abl-SH3:p41 example, (3, 1, 1, 1, 1, 1, 5, 3) is a good choice for the number of windows for each step of the geometrical route.”
BackgroundProtein storytelling through physics
Brini, E., Simmerling, C. L., & Dill, K. A. (2020) · Science · doi:10.1126/science.aaz3041 · Cited by 77 · see citing works
“MDsimulationsarenow also giving the thermodynamic components, enthalpy and entropy, of binding, which give additional insights for storytelling about molecular recognition ( 115 , 116 ).”
BackgroundThe role of water in ligand binding.
Zsidó, B. Z., & Hetényi, C. (2020) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2020.08.002 · Cited by 59 · see citing works
Docking Screens for Drug Discovery
de Azevedo, W. (2019) · Methods in Molecular Biology · doi:10.1007/978-1-4939-9752-7 · Cited by 48
“These scoring functions permit investigating which are the optimal description of complexes, data set partition steps, regression models, and best modeling practices for the prediction of binding affinities from X-ray crystal structures of protein–ligand complexes [10].”
BackgroundMethodVan der Waals Potential in Protein Complexes.
Bitencourt-Ferreira, G., Veit-Acosta, M., & de Azevedo, W. (2019) · Methods in molecular biology · doi:10.1007/978-1-4939-9752-7_6 · Cited by 31 · see citing works
The current impact of water thermodynamics for small-molecule drug discovery
Geschwindner, S., & Ulander, J. (2019) · Expert Opinion on Drug Discovery · doi:10.1080/17460441.2019.1664468 · Cited by 29 · see citing works
Minetti, C. A. S. A., & Remeta, D. P. (2022) · Life · doi:10.3390/life12091438 · Cited by 15 · see citing works
Some Thermodynamic Effects of Varying Nonpolar Surfaces in Protein-Ligand Interactions.
Cramer, D. L., Cheng, B., Tian, J.-H., Clements, J. H., Wypych, R. M., & Martin, S. (2020) · European journal of medicinal chemistry · doi:10.1016/j.ejmech.2020.112771 · Cited by 9 · see citing works
Ramírez-Palacios, C., & Marrink, S. (2022) · QRB Discovery · doi:10.1017/qrd.2022.22 · Cited by 7 · see citing works
Notari, E., Wood, C. W., & Michel, J. (2025) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.4c01695 · Cited by 4 · see citing works
Modeling Changes in Molecular Dynamics Time Series as Wasserstein Barycentric Interpolations
Damjanovic, J., Lin, Y., & Murphy, J. M. (2023) · International Conference on Sampling Theory and Applications · doi:10.1109/sampta59647.2023.10301374 · Cited by 3 · see citing works
“MD trajectories of even large biomolecular systems showcasing phenomena on millisecond timescales are now available, providing unique insights into fundamental problems such as protein folding [4]–[6], protein– ligand binding [7], and solution structural ensembles of macro-cycles [1], [8], [9].”
BackgroundStructure-thermodynamics-relationships of hepatitis C viral NS3 protease inhibitors.
Wypych, R. M., LaPlante, S., White, P. W., & Martin, S. (2020) · European journal of medicinal chemistry · doi:10.1016/j.ejmech.2020.112195 · Cited by 3 · see citing works
Çınaroğlu, S. S., & Biggin, P. C. (2023) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.3c01041 · Cited by 3 · see citing works
Xu, R.-L., Zhu, Y., Zhang, L., Chen, Q., Hong, H.-F., Zhou, Z.-F., Wu, Z.-M., Pieters, R. J., & Shi, J. (2025) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2025.150024 · Cited by 1
Guo, N., Zhou, H., Chen, W., Su, P., Cai, W., Lv, Y., & Han, S. (2025) · Analytical Chemistry · doi:10.1021/acs.analchem.5c05650 · Cited by 2 · see citing works
Sueyoshi, S., Raimo, L. B., Coutinho, L. P., Brito, M. O. O., Giarolla, J., & Ducati, L. (2026) · ACS Omega · doi:10.1021/acsomega.6c04630
- Authors
- Li, A., & Gilson, M. K.
- Affiliations
- University of California San Diego (US)
- Corresponding author
- Gilson, Michael K.
- Venue
- The Journal of Chemical Physics
- Publisher
- AIP Publishing
- Published
- 2018-05-21
- Volume
- 149
- Issue
- 7
- Pages
- 072311-072311
- ISSN
- 0021-9606 (ISSN-L)
- 1089-7690
- PMC
- PMC5962444
- OpenAlex
- W2803899613
- Cited by
- 24
- References
- 58
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 1 · 2023: 4 · 2022: 8 · 2021: 1 · 2020: 4 · 2019: 2
- FWCI
- 1.23
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The Journal of Chemical Physics (publishedVersion)
- ChemRxiv (acceptedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Royal College of Surgeons in Ireland (submittedVersion, cc-by)
- Funders
- National Institute of General Medical Sciences (GM061300)
- Topics
- Physical Sciences › Chemistry › Physical and Theoretical Chemistry › thermodynamics and calorimetric analyses
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Keywords
- protein-ligand binding, binding enthalpy, Grb2 SH2 domain, configurational entropy, enthalpy-entropy compensation, force field accuracy, binding site residues
- MeSH terms
- Ligands, Oligopeptides, Protein Binding, Protein Conformation, Thermodynamics, Water, src Homology Domains, Principal Component Analysis, GRB2 Adaptor Protein, Molecular Dynamics Simulation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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