Molecular Biology

, Volume 52, Issue 1, pp 108–117 | Cite as

Evaluation of the Accuracy of Calculation of the Standard Binding Entropy of Molecules from their Average Mobility in Molecular Crystals

  • S. O. Garbuzynskiy
  • A. V. Finkelstein
Structural Functional Analysis of Biopolymers and Their Complexes


One of the main problems in attempts to predict the binding constants of molecules (or free energies of their binding) is the correct evaluation of configurational binding entropy. This evaluation is possible by methods of molecular dynamics simulation, but these simulations require a lot of computational time. Earlier, we have developed an alternative approach which allows the fast calculation of the binding entropy from summarizing the available data on sublimation of crystals. Our method is based on evaluating the mean amplitude of the movements that are restricted in the bound molecule, e.g., in a crystal, but are not restricted in the free state, e.g., in vapor. In this work, it is shown that the standard entropy of binding of molecules by crystals under standard conditions (1 atm, 25°C) can be assessed rather accurately from geometric and physical parameters of the molecule and the average amplitude of the molecule motions in crystals estimated in our previous work.


standard sublimation entropy binding entropy amplitude of molecular movements in a crystal sublimation enthalpy molecular crystals computational chemistry and biochemistry 


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  1. 1.
    Steinbrecher T., Labahn A. 2010. Towards accurate free energy calculations in ligand protein-binding studies. Curr. Med. Chem. 17, 767–785.CrossRefPubMedGoogle Scholar
  2. 2.
    Muzzioli E., Del Rio A., Rastelli G. 2011. Assessing protein kinase selectivity with molecular dynamics and MM-PBSA binding free energy calculations. Chem. Biol. Drug. Des. 78, 252–259.CrossRefPubMedGoogle Scholar
  3. 3.
    Shivakumar D., Harder E., Damm W., et al. 2012. Improving the prediction of absolute solvation free energies using the next generation OPLS force field. J. Chem. Theory Comput. 8, 2553–2558.CrossRefPubMedGoogle Scholar
  4. 4.
    Wang L., Wu Y., Deng Y., et al. 2015. Accurate and reliable prediction of relative ligand binding potency in prospective drug discovery by way of a modern freeenergy calculation protocol and force field. J. Am. Chem. Soc., 137, 2695–2703.CrossRefPubMedGoogle Scholar
  5. 5.
    Clark R.D., Waldman M. 2012. Lions and tigers and bears, oh my! Three barriers to progress in computeraided molecular design. J. Comput. Aided Mol. Des. 26, 29–34.CrossRefPubMedGoogle Scholar
  6. 6.
    Gumbart J.C., Roux B., Chipot C. 2013. Standard binding free energies from computer simulations: What is the best strategy? J. Chem. Theory Comput. 9, 794–802.CrossRefGoogle Scholar
  7. 7.
    Huang N., Jacobson M.P. 2007. Physics-based methods for studying protein-ligand interactions. Curr. Opin. Drug. Discov. Dev. 10, 325–331.Google Scholar
  8. 8.
    Borhani D.W., Shaw D.E. 2012. The future of molecular dynamics simulations in drug discovery. J. Comput. Aided Mol. Des. 26, 15–26.CrossRefPubMedGoogle Scholar
  9. 9.
    Krieger E., Darden T., Nabuurs S.B., et al. 2004. Making optimal use of empirical energy functions: Force field parameterization in crystal space. Proteins. 57, 678–683.CrossRefPubMedGoogle Scholar
  10. 10.
    Gao C., Park M.-S., Stern H.A. 2010. Accounting for ligand conformational restriction in calculations of protein-ligand binding affinities. Biophys. J. 98, 901–910.CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Finkelstein A.V., Ptitsyn O.B. 2016. Protein Physics. A Course of Lectures, 2nd ed., Amsterdam: Elsevier, Chapters 5–8.Google Scholar
  12. 12.
    Pereyaslavets L.B., Finkelstein A.V. 2010. Atomic force field FFsol for calculating molecular interactions in water environment. Mol. Biol. (Moscow). 44, 303–316.CrossRefGoogle Scholar
  13. 13.
    Pereyaslavets L.B., Finkelstein A.V. 2012. Development and testing of PFFsol1.1, a new polarizable atomic force field for calculation of molecular interactions in implicit water environment. J. Phys. Chem. B. 116, 4646–4654, Suppl. A1. Scholar
  14. 14.
    Finkelstein A.V., Janin J. 1989. The price of lost freedom. Protein Eng. 3, 1–3.CrossRefPubMedGoogle Scholar
  15. 15.
    Pickett S.D., Sternberg M.J. 1993. Empirical scale of side-chain conformational entropy in protein folding. J. Mol. Biol. 231, 825–839.CrossRefPubMedGoogle Scholar
  16. 16.
    Kortemme T., Baker D. 2002. A simple physical model for binding energy hot spots in protein-protein complexes. Proc. Natl. Acad. Sci. U. S. A. 99, 14116–14121.CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Lee J., Seok C. 2008. A statistical rescoring scheme for protein-ligand docking: Consideration of entropic effect. Proteins. 15, 1074–1083.Google Scholar
  18. 18.
    Wang J., Hou T. 2012. Develop and test a solvent accessible surface area-based model in conformational entropy calculations. J. Chem. Inf. Model. 25, 1199–1212.CrossRefGoogle Scholar
  19. 19.
    Chiba S., Harano Y., Roth R., et al. 2012. Evaluation of protein-ligand binding free energy focused on its entropic components. J. Comput. Chem. 15, 550–560.CrossRefGoogle Scholar
  20. 20.
    Kamisetty H., Ramanathan A., Bailey-Kellogg C., et al. 2011. Accounting for conformational entropy in predicting binding free energies of protein-protein interactions. Proteins. 79, 444–462.CrossRefPubMedGoogle Scholar
  21. 21.
    Perola E., Charifson P.S. 2004. Conformational analysis of drug-like molecules bound to proteins: An extensive study of ligand reorganization upon binding. J. Med. Chem. 47, 2499–2510.CrossRefPubMedGoogle Scholar
  22. 22.
    Garbuzynskiy S.O., Finkelstein A.V. 2016. Calculation of mobility and entropy of the binding of molecules by crystals. Mol. Biol. (Moscow). 50, 452–461.CrossRefGoogle Scholar
  23. 23.
    Garbuzynskiy S.O., Finkelstein A.V. 2017. Sublimation entropy and dissociation constants prediction by quantitative evaluation of molecular mobility in crystals. J. Phys. Chem. Lett. 8, 2758–2763.CrossRefPubMedGoogle Scholar
  24. 24.
    Landau L.D., Lifshitz E.M. 1980. A Course of Theoretical Physics, vol. 5: Statistical Physics, 3rd ed., Amsterdam: Elsevier, Chapter 3.Google Scholar
  25. 25.
    Pereyaslavets L.B., Finkelstein A.V. 2011. Database A2 on thermodynamic characteristics of molecular crystals. Appendix to [12]. Scholar
  26. 26.
    Finkelstein A.V. 2014. Extended database A2 [13] on characteristics of molecular crystals. Scholar
  27. 27.
    Allen F.H. 2002. The Cambridge Structural Database: A quarter of a million crystal structures and rising. Acta Cryst. B58, 380–388.CrossRefGoogle Scholar
  28. 28.
    Levitt M., Hirshberg M., Sharon R., et al. 1995. Potential energy function and parameters for simulations of the molecular dynamics of proteins and nucleic acids in solution. Comput. Phys. Commun. 91, 215–231.CrossRefGoogle Scholar

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© Pleiades Publishing, Inc. 2018

Authors and Affiliations

  1. 1.Institute of Protein ResearchRussian Academy of SciencesPushchino, Moscow oblastRussia

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