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Journal of Computer-Aided Molecular Design

, Volume 32, Issue 10, pp 1059–1073 | Cite as

Prediction of CB[8] host–guest binding free energies in SAMPL6 using the double-decoupling method

  • Kyungreem Han
  • Phillip S. Hudson
  • Michael R. Jones
  • Naohiro Nishikawa
  • Florentina Tofoleanu
  • Bernard R. Brooks
Article

Abstract

This study reports the results of binding free energy calculations for CB[8] host–guest systems in the SAMPL6 blind challenge (receipt ID 3z83m). Force-field parameters were developed specific for each of host and guest molecules to improve configurational sampling. We used quantum mechanical (QM) implicit solvent calculations and QM force matching to determine non-bonded (partial atomic charges) and bonded terms, respectively. Free energy calculations were carried out using the double-decoupling method (DDM) combined with Hamiltonian replica exchange method (HREM) and Bennett acceptance ratio (BAR) method. The root mean square error (RMSE) of the predicted values using DDM with respect to the experimental results was 4.32 kcal/mol. The coefficient of determination (R2) and Kendall rank coefficient (τ) were 0.49 and 0.52, respectively, highest of all submissions. In addition, these were compared to the results obtained by umbrella sampling (US) and weighted histogram analysis method (WHAM). Overall, DDM achieved a higher prediction accuracy than the US method. Results are discussed in terms of parameterization and free energy simulations.

Keywords

Binding free energy Double-decoupling Hamiltonian replica exchange Bennett acceptance ratio Umbrella sampling Weighted histogram analysis 

Notes

Acknowledgements

The authors would like to thank Gerhard König, Xiongwu Wu, Qiao Zheng and Daniel R. Roe for helpful advice and discussion. We extend our appreciation to Richard M. Venable, Andrew C. Simmonett, John Legato, Andrea Rizzi, Minkyung Baek and Chaok Seok for valuable comment and technical support. Kyungreem Han wishes to express his deepest gratitude to Richard W. Pastor. This work was partially supported by the intramural research program of the National Heart, Lung and Blood Institute (NHLBI) of the National Institutes of Health and employed the high-performance computational capabilities of the LoBoS and Biowulf Linux clusters at the National Institutes of Health (http://www.lobos.nih.gov and http://biowulf.nih.gov). Kyungreem Han’s research was partially supported by a Grant from the KRIBB Research Initiative Program (Korean Biomedical Scientist Fellowship Program), Korea Research Institute of Bioscience and Biotechnology, Republic of Korea.

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Authors and Affiliations

  1. 1.Laboratory of Computational Biology, National Heart, Lung and Blood InstituteNational Institutes of HealthBethesdaUSA

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