Journal of Computer-Aided Molecular Design

, Volume 31, Issue 1, pp 29–44 | Cite as

A combined treatment of hydration and dynamical effects for the modeling of host–guest binding thermodynamics: the SAMPL5 blinded challenge

  • Rajat Kumar Pal
  • Kamran Haider
  • Divya Kaur
  • William Flynn
  • Junchao Xia
  • Ronald M Levy
  • Tetiana Taran
  • Lauren Wickstrom
  • Tom Kurtzman
  • Emilio Gallicchio
Article

Abstract

As part of the SAMPL5 blinded experiment, we computed the absolute binding free energies of 22 host–guest complexes employing a novel approach based on the BEDAM single-decoupling alchemical free energy protocol with parallel replica exchange conformational sampling and the AGBNP2 implicit solvation model specifically customized to treat the effect of water displacement as modeled by the Hydration Site Analysis method with explicit solvation. Initial predictions were affected by the lack of treatment of ionic charge screening, which is very significant for these highly charged hosts, and resulted in poor relative ranking of negatively versus positively charged guests. Binding free energies obtained with Debye–Hückel treatment of salt effects were in good agreement with experimental measurements. Water displacement effects contributed favorably and very significantly to the observed binding affinities; without it, the modeling predictions would have grossly underestimated binding. The work validates the implicit/explicit solvation approach employed here and it shows that comprehensive physical models can be effective at predicting binding affinities of molecular complexes requiring accurate treatment of conformational dynamics and hydration.

Keywords

SAMPL5 Hydration Site Analysis (HSA) Debye–Hückel Salt effects AGBNP2 BEDAM 

Notes

Acknowledgments

E.G. and R.K.P. acknowledge support from the National Science Foundation (SI2-SSE 1440665). R.M.L. acknowledges support from the National Institutes of Health (GM30580 and P50 GM103368). T.K. acknowledges support from the National Institutes of Health (1R01GM100946 and 5SC3GM095417). L.W. acknowledges support from PSC-CUNY (68457-00 46). REMD simulations were carried out on the Supermic cluster of XSEDE (supported by TG-MCB150001), and BOINC distributed networks at Temple University and Brooklyn College of the City University of New York. The authors acknowledge invaluable technical support from Gene Mayro, Jaykeen Holt, Zachary Hanson-Hart from the IT department at Temple University, and James Roman, and John Stephen at Brooklyn College.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Rajat Kumar Pal
    • 1
    • 5
  • Kamran Haider
    • 2
  • Divya Kaur
    • 6
  • William Flynn
    • 4
    • 7
  • Junchao Xia
    • 4
  • Ronald M Levy
    • 4
  • Tetiana Taran
    • 3
  • Lauren Wickstrom
    • 3
  • Tom Kurtzman
    • 2
    • 5
    • 6
  • Emilio Gallicchio
    • 1
    • 5
    • 6
  1. 1.Department of ChemistryBrooklyn CollegeBrooklynUSA
  2. 2.Department of Chemistry, Lehman CollegeThe City University of New YorkNew YorkUSA
  3. 3.Borough of Manhattan Community College, Department of ScienceThe City University of New YorkNew YorkUSA
  4. 4.Center for Biophysics and Computational Biology, Institute of Computational Molecular Science and Department of ChemistryTemple UniversityPhiladelphiaUSA
  5. 5.Ph.D. Program in BiochemistryThe Graduate Center of the City University of New YorkNew YorkUSA
  6. 6.Ph.D. Program in ChemistryThe Graduate Center of the City University of New YorkNew YorkUSA
  7. 7.Department of Physics and AstronomyRutgers UniversityPiscatawayUSA

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