TY - JOUR
T1 - The ugly, bad, and good stories of large-scale biomolecular simulations
AU - Gupta, Chitrak
AU - Sarkar, Daipayan
AU - Tieleman, D. Peter
AU - Singharoy, Abhishek
N1 - Funding Information:
Work in DPT's group is supported by the Natural Sciences and Engineering Research Council (Canada) and the Canadian Institutes for Health Research. Further support came from the Canada Research Chairs Program. AS acknowledges start-up funds from the SMS and CASD at Arizona State University, CAREER award by NSF-MCB 1942763. Many thanks to Lorenzo Casalino and Rommie Amaro (UCSD), Karissa Sanbonmatsu (LANL) and John Vant (ASU) for contributing unpublished images to Figure 1. We also thank the Biophysics community on Twitter, particularly Syma Khalid, Mathieu Chavent and Viola Vogele for valuable suggestions.
Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/4
Y1 - 2022/4
N2 - Molecular modeling of large biomolecular assemblies exemplifies a disruptive area holding both promises and contentions. Propelled by peta and exascale computing, several simulation methodologies have now matured into user-friendly tools that are successfully employed for modeling viruses, membranous nano-constructs, and key pieces of the genetic machinery. We present three unifying biophysical themes that emanate from some of the most recent multi-million atom simulation endeavors. Despite connecting molecular changes with phenotypic outcomes, the quality measures of these simulations remain questionable. We discuss the existing and upcoming strategies for constructing representative ensembles of large systems, how new computing technologies will boost this area, and make a point that integrative modeling guided by experimental data is the future of biomolecular computations.
AB - Molecular modeling of large biomolecular assemblies exemplifies a disruptive area holding both promises and contentions. Propelled by peta and exascale computing, several simulation methodologies have now matured into user-friendly tools that are successfully employed for modeling viruses, membranous nano-constructs, and key pieces of the genetic machinery. We present three unifying biophysical themes that emanate from some of the most recent multi-million atom simulation endeavors. Despite connecting molecular changes with phenotypic outcomes, the quality measures of these simulations remain questionable. We discuss the existing and upcoming strategies for constructing representative ensembles of large systems, how new computing technologies will boost this area, and make a point that integrative modeling guided by experimental data is the future of biomolecular computations.
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U2 - 10.1016/j.sbi.2022.102338
DO - 10.1016/j.sbi.2022.102338
M3 - Review article
C2 - 35245737
AN - SCOPUS:85125436208
SN - 0959-440X
VL - 73
JO - Current Opinion in Structural Biology
JF - Current Opinion in Structural Biology
M1 - 102338
ER -