Adaptive ensemble simulations of biomolecules

Kasson, Peter M.; Jha, Shantenu

doi:10.1016/j.sbi.2018.09.005

Title: Adaptive ensemble simulations of biomolecules

Journal Article · 25 September 2018 · Current Opinion in Structural Biology

DOI: https://doi.org/10.1016/j.sbi.2018.09.005 · OSTI ID:1491694

Kasson, Peter M. ^[1]; Jha, Shantenu ^[2]

Univ. of Virginia, Charlottesville, VA (United States); Uppsala Univ., Uppsala (Sweden)
Rutgers Univ., Piscataway, NJ (United States); Brookhaven National Lab. (BNL), Upton, NY (United States)

Recent advances in both theory and computational power have created opportunities to simulate biomolecular processes more efficiently using adaptive ensemble simulations. Ensemble simulations are now widely used to compute a number of individual simulation trajectories and analyze statistics across them. Adaptive ensemble simulations offer a further level of sophistication and flexibility by enabling highlevel algorithms to control simulations-based on intermediate results. We review some of the adaptive ensemble algorithms and software infrastructure currently in use and outline where the complexities of implementing adaptive simulation have limited algorithmic innovation to date. In conclusion, we describe an adaptive ensemble API to overcome some of these barriers and more flexibly and simply express adaptive simulation algorithms to help realize the power of this type of simulation.

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Research Organization:: Brookhaven National Laboratory (BNL), Upton, NY (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Advanced Scientific Computing Research (SC-21)

Grant/Contract Number:: SC0012704

OSTI ID:: 1491694

Report Number(s):: BNL-210893-2019-JAAM

Journal Information:: Current Opinion in Structural Biology, Vol. 52, Issue C; ISSN 0959-440X

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 18 works

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