Literature DB >> 34592698

Modeling biomolecular kinetics with large-scale simulation.

Peter M Kasson1.   

Abstract

The molecular details of biomolecular kinetics present a challenging estimation problem because the identities of relevant intermediates and the rates of exchange between them must be determined. These can be derived from prior knowledge, but in recent years, great advances have been made in the development and application of methods to systematically determine states and rates using biomolecular simulation. Doing this for biological systems of reasonable complexity requires substantial computational power, and contemporary methods leverage distributed computing or leadership-class computing resources to accomplish this. The result has been substantial insight into pressing contemporary problems, including structural activation of pandemic viruses. Here, we highlight recent developments in both methodology and exciting applications.
Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.

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Year:  2021        PMID: 34592698      PMCID: PMC9476681          DOI: 10.1016/j.sbi.2021.08.009

Source DB:  PubMed          Journal:  Curr Opin Struct Biol        ISSN: 0959-440X            Impact factor:   7.786


  39 in total

1.  Error analysis and efficient sampling in Markovian state models for molecular dynamics.

Authors:  Nina Singhal; Vijay S Pande
Journal:  J Chem Phys       Date:  2005-11-22       Impact factor: 3.488

2.  The "weighted ensemble" path sampling method is statistically exact for a broad class of stochastic processes and binning procedures.

Authors:  Bin W Zhang; David Jasnow; Daniel M Zuckerman
Journal:  J Chem Phys       Date:  2010-02-07       Impact factor: 3.488

Review 3.  Principles of protein structural ensemble determination.

Authors:  Massimiliano Bonomi; Gabriella T Heller; Carlo Camilloni; Michele Vendruscolo
Journal:  Curr Opin Struct Biol       Date:  2017-01-05       Impact factor: 6.809

4.  Complete protein-protein association kinetics in atomic detail revealed by molecular dynamics simulations and Markov modelling.

Authors:  Nuria Plattner; Stefan Doerr; Gianni De Fabritiis; Frank Noé
Journal:  Nat Chem       Date:  2017-06-05       Impact factor: 24.427

Review 5.  Weighted Ensemble Simulation: Review of Methodology, Applications, and Software.

Authors:  Daniel M Zuckerman; Lillian T Chong
Journal:  Annu Rev Biophys       Date:  2017-03-01       Impact factor: 12.981

6.  Thermodynamically reversible paths of the first fusion intermediate reveal an important role for membrane anchors of fusion proteins.

Authors:  Yuliya G Smirnova; Herre Jelger Risselada; Marcus Müller
Journal:  Proc Natl Acad Sci U S A       Date:  2019-01-30       Impact factor: 11.205

7.  Rapid exploration of configuration space with diffusion-map-directed molecular dynamics.

Authors:  Wenwei Zheng; Mary A Rohrdanz; Cecilia Clementi
Journal:  J Phys Chem B       Date:  2013-08-07       Impact factor: 2.991

8.  VAMPnets for deep learning of molecular kinetics.

Authors:  Andreas Mardt; Luca Pasquali; Hao Wu; Frank Noé
Journal:  Nat Commun       Date:  2018-01-02       Impact factor: 14.919

9.  Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation.

Authors:  Daniel Wrapp; Nianshuang Wang; Kizzmekia S Corbett; Jory A Goldsmith; Ching-Lin Hsieh; Olubukola Abiona; Barney S Graham; Jason S McLellan
Journal:  Science       Date:  2020-02-19       Impact factor: 47.728

10.  SARS-CoV-2 simulations go exascale to predict dramatic spike opening and cryptic pockets across the proteome.

Authors:  Maxwell I Zimmerman; Justin R Porter; Michael D Ward; Sukrit Singh; Neha Vithani; Artur Meller; Upasana L Mallimadugula; Catherine E Kuhn; Jonathan H Borowsky; Rafal P Wiewiora; Matthew F D Hurley; Aoife M Harbison; Carl A Fogarty; Joseph E Coffland; Elisa Fadda; Vincent A Voelz; John D Chodera; Gregory R Bowman
Journal:  Nat Chem       Date:  2021-05-24       Impact factor: 24.427

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