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Sigmoid Accelerated Molecular Dynamics: An Efficient Enhanced Sampling Method for Biosystems
College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, China, Zhejiang.
College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, China, Zhejiang; CarbonSilicon AI Technology Company, Ltd., Hangzhou 310018, Zhejiang, China, Zhejiang.
College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, China, Zhejiang; CarbonSilicon AI Technology Company, Ltd., Hangzhou 310018, Zhejiang, China, Zhejiang.
College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, China, Zhejiang.
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2023 (English)In: The Journal of Physical Chemistry Letters, E-ISSN 1948-7185, Vol. 14, no 4, p. 1103-1112Article in journal (Refereed) Published
Abstract [en]

Gaussian accelerated molecular dynamics (GaMD) is recognized as a popular enhanced sampling method for tackling long-standing challenges in biomolecular simulations. Inspired by GaMD, Sigmoid accelerated molecular dynamics (SaMD) is proposed in this work by adding a Sigmoid boost potential to improve the balance between the highest acceleration and accurate reweighting. Compared with GaMD, SaMD extends the accessible time scale and improves the computational efficiency as tested in three tasks. In the alanine dipeptide task, SaMD can produce the free energy landscape with better accuracy and efficiency. In the chignolin folding task, the estimated Gibbs free energy difference can converge to the experimental value ∼30% faster. In the protein-ligand binding task, the bound conformations are closer to the crystal structure with a minimal ligand root-mean-square deviation of 1.7 Å. The binding of the ligand XK263 to the HIV protease is reproduced by SaMD in ∼60% less simulation time.

Place, publisher, year, edition, pages
American Chemical Society (ACS) , 2023. Vol. 14, no 4, p. 1103-1112
National Category
Physical Chemistry
Identifiers
URN: urn:nbn:se:kth:diva-330043DOI: 10.1021/acs.jpclett.2c03688ISI: 000926643500001PubMedID: 36700836Scopus ID: 2-s2.0-85147163951OAI: oai:DiVA.org:kth-330043DiVA, id: diva2:1775421
Note

QC 20230627

Available from: 2023-06-27 Created: 2023-06-27 Last updated: 2024-07-04Bibliographically approved

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Tu, Yaoquan

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