The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Interaction Entropy: A New Paradigm for Highly Efficient and Reliable Computation of Protein–Ligand Binding Free Energy
Abstract
Efficient and reliable calculation of protein-ligand binding free energy is a grand challenge in computational biology and is of critical importance in drug design and many other molecular recognition problems. The main challenge lies in the calculation of entropic contribution to protein-ligand binding or interaction systems. In this report, we present a new interaction entropy method which is theoretically rigorous, computationally efficient, and numerically reliable for calculating entropic contribution to free energy in protein-ligand binding and other interaction processes. Drastically different from the widely employed but extremely expensive normal mode method for calculating entropy change in protein-ligand binding, the new method calculates the entropic component (interaction entropy or -TΔS) of the binding free energy directly from molecular dynamics simulation without any extra computational cost. Extensive study of over a dozen randomly selected protein-ligand binding systems demonstrated that this interaction entropy method is both computationally efficient and numerically reliable and is vastly superior to the standard normal mode approach. This interaction entropy paradigm introduces a novel and intuitive conceptual understanding of the entropic effect in protein-ligand binding and other general interaction systems as well as a practical method for highly efficient calculation of this effect.
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gmx_MMPBSA: A New Tool to Perform End-State Free Energy Calculations with GROMACS
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“95,97,98 In a recent study of Sun et al., 97 entropy effects on the performance of endpoint methods of over 1,500 protein – ligand systems were assessed.”
BackgroundMethodCong, Y., Feng, Y., Ni, H., Zhi, F., Miao, Y., Fang, B., Zhang, L., & Zhang, J. Z. H. (2021) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.1c00241 · Cited by 40
Self-citation
Metadata
- Authors
- Duan, L., Liu, X., & Zhang, J. Z. H.
- Venue
- Journal of the American Chemical Society
- Publisher
- American Chemical Society (ACS)
- Published
- 2016-04-20
- Volume
- 138
- Issue
- 17
- Pages
- 5722-5728
- ISSN
- 0002-7863 (ISSN-L)
- 1520-5126
- OpenAlex
- W2325034207
- Cited by
- 465
- References
- 28
- FWCI
- 23.22
- Type
- journal article
- Language
- en
- Open access
- closed
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