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Absolute binding free energy calculations of CBClip host-guest systems in the SAMPL5 blind challenge

Cited 11 time in Web of Science Cited 12 time in Scopus
Authors

Lee, Ju Yong; Tofoleanu, Florentina; Pickard, Frank C.; Konig, Gerhard; Huang, Jing; Damjanovic, Ana; Baek, Minkyung; Seok, Chaok; Brooks, Bernard R.

Issue Date
2017-01
Publisher
Kluwer Academic Publishers
Citation
Journal of Computer-Aided Molecular Design, Vol.31 No.1, pp.71-85
Abstract
Herein, we report the absolute binding free energy calculations of CBClip complexes in the SAMPL5 blind challenge. Initial conformations of CBClip complexes were obtained using docking and molecular dynamics simulations. Free energy calculations were performed using thermodynamic integration (TI) with soft-core potentials and Bennett's acceptance ratio (BAR) method based on a serial insertion scheme. We compared the results obtained with TI simulations with soft-core potentials and Hamiltonian replica exchange simulations with the serial insertion method combined with the BAR method. The results show that the difference between the two methods can be mainly attributed to the van der Waals free energies, suggesting that either the simulations used for TI or the simulations used for BAR, or both are not fully converged and the two sets of simulations may have sampled difference phase space regions. The penalty scores of force field parameters of the 10 guest molecules provided by CHARMM Generalized Force Field can be an indicator of the accuracy of binding free energy calculations. Among our submissions, the combination of docking and TI performed best, which yielded the root mean square deviation of 2.94 kcal/mol and an average unsigned error of 3.41 kcal/mol for the ten guest molecules. These values were best overall among all participants. However, our submissions had little correlation with experiments.
ISSN
0920-654X
URI
https://hdl.handle.net/10371/201528
DOI
https://doi.org/10.1007/s10822-016-9968-2
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  • Graduate School of Convergence Science & Technology
  • Dept. of Molecular and Biopharmaceutical Sciences
Research Area AI models for drug discovery, Free energy calculation, Molecular dynamics, 분자동역학, 신약개발을 위한 AI 모델, 자유에너지 계산

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