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Independent-Trajectory Thermodynamic Integration: A Practical Guide to Protein-Drug Binding Free Energy Calculations Using Distributed Computing

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Computational Drug Discovery and Design

Part of the book series: Methods in Molecular Biology ((MIMB,volume 819))

Abstract

The Independent-Trajectory Thermodynamic Integration (IT-TI) approach for free energy calculation with distributed computing is described. IT-TI utilizes diverse conformational sampling obtained from multiple, independent simulations to obtain more reliable free energy estimates compared to single TI predictions. The latter may significantly under- or over-estimate the binding free energy due to finite sampling. We exemplify the advantages of the IT-TI approach using two distinct cases of protein–ligand binding. In both cases, IT-TI yields distributions of absolute binding free energy estimates that are remarkably centered on the target experimental values. Alternative protocols for the practical and general application of IT-TI calculations are investigated. We highlight a protocol that maximizes predictive power and computational efficiency.

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Acknowledgement

The authors thank the members of the McCammon group for useful discussions. This work was supported, in part, by the National Institutes of Health, the National Science Foundation, the National Biomedical Computational Resource, and the Howard Hughes Medical Institute. We thank the Center for Theoretical Biological Physics (NSF Grant PHY-0822283), and the Texas Advanced Computer Center (grant TG-MCA93S013) for distributed computing resources. We also thank Dr. Ross C. Walker at the San Diego Supercomputing Center for additional computational resources.

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Authors and Affiliations

  1. Department of Chemistry and Biochemistry, Center for Theoretical Biological Physics, University of California, San Diego, La Jolla, CA, USA

    Morgan Lawrenz & Yi Wang

  2. Department of Medicinal Chemistry, College of Pharmacy, The Henry Eyring Center for Theoretical Chemistry, University of Utah, Salt Lake City, UT, USA

    Riccardo Baron

  3. Howard Hughes Medical Institute, Departments of Chemistry and Biochemistry and Pharmacology, Center for Theoretical Biological Physics, University of California, San Diego, La Jolla, CA, USA

    J. Andrew McCammon

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  1. Morgan Lawrenz
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  2. Riccardo Baron
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  3. Yi Wang
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  4. J. Andrew McCammon
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Corresponding authors

Correspondence to Morgan Lawrenz or Riccardo Baron .

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Editors and Affiliations

  1. University of Utah, 30 South 2000 East Rm 307, Salt Lake City, 84112-5820, California, USA

    Riccardo Baron

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Lawrenz, M., Baron, R., Wang, Y., McCammon, J.A. (2012). Independent-Trajectory Thermodynamic Integration: A Practical Guide to Protein-Drug Binding Free Energy Calculations Using Distributed Computing. In: Baron, R. (eds) Computational Drug Discovery and Design. Methods in Molecular Biology, vol 819. Springer, New York, NY. https://doi.org/10.1007/978-1-61779-465-0_27

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  • DOI: https://doi.org/10.1007/978-1-61779-465-0_27

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