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Journal of Computer-Aided Molecular Design

, Volume 29, Issue 4, pp 315–325 | Cite as

BEDAM binding free energy predictions for the SAMPL4 octa-acid host challenge

  • Emilio Gallicchio
  • Haoyuan Chen
  • He Chen
  • Michael Fitzgerald
  • Yang Gao
  • Peng He
  • Malathi Kalyanikar
  • Chuan Kao
  • Beidi Lu
  • Yijie Niu
  • Manasi Pethe
  • Jie Zhu
  • Ronald M. Levy
Article

Abstract

The binding energy distribution analysis method (BEDAM) protocol has been employed as part of the SAMPL4 blind challenge to predict the binding free energies of a set of octa-acid host–guest complexes. The resulting predictions were consistently judged as some of the most accurate predictions in this category of the SAMPL4 challenge in terms of quantitative accuracy and statistical correlation relative to the experimental values, which were not known at the time the predictions were made. The work has been conducted as part of a hands-on graduate class laboratory session. Collectively the students, aided by automated setup and analysis tools, performed the bulk of the calculations and the numerical and structural analysis. The success of the experiment confirms the reliability of the BEDAM methodology and it shows that physics-based atomistic binding free energy estimation models, when properly streamlined and automated, can be successfully employed by non-specialists.

Keywords

Binding energy distribution analysis method Implicit solvation Analytic generalized Born plus non-polar model Blind prediction 

Notes

Acknowledgments

This work has been supported in part by research grants from the National Institute of Health (GM30580) and the National Science Foundation Cyber-enabled Discovery and Innovation Award (CHE-1125332). The calculations reported in this work have been performed at the BioMaPS High Performance Computing Center at Rutgers University funded in part by the NIH shared instrumentation Grants No. 1 S10 RR022375. We gratefully acknowledge Lauren Wickstrom for helpful discussion during the preparation of the manuscript.

Supplementary material

10822_2014_9795_MOESM1_ESM.zip (47 kb)
Supplementary material 1 (zip 47 KB)

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Emilio Gallicchio
    • 1
  • Haoyuan Chen
    • 2
  • He Chen
    • 2
  • Michael Fitzgerald
    • 2
  • Yang Gao
    • 2
  • Peng He
    • 3
    • 4
  • Malathi Kalyanikar
    • 2
  • Chuan Kao
    • 2
  • Beidi Lu
    • 2
  • Yijie Niu
    • 2
  • Manasi Pethe
    • 2
  • Jie Zhu
    • 2
  • Ronald M. Levy
    • 3
    • 4
  1. 1.Department of ChemistryCUNY Brooklyn CollegeBrooklynUSA
  2. 2.Department of Chemistry and Chemical BiologyRutgers the State University of New JerseyPiscatawayUSA
  3. 3.Center for Biophysics and Computational Biology, Institute of Computational Molecular ScienceTemple UniversityPhiladelphiaUSA
  4. 4.Department of ChemistryTemple UniversityPhiladelphiaUSA

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