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Biomolecular modeling and simulation: a field coming of age

Published online by Cambridge University Press:  12 January 2011

Tamar Schlick ,
Rosana Collepardo-Guevara ,
Leif Arthur Halvorsen ,
Segun Jung  and
Xia Xiao
Tamar Schlick*
Affiliation:
Department of Chemistry, New York University, 100 Washington Square East, Silver Building, New York, NY 10003, USA Courant Institute of Mathematical Sciences, New York University, 251 Mercer Street, New York, NY 10012, USA
Rosana Collepardo-Guevara
Affiliation:
Department of Chemistry, New York University, 100 Washington Square East, Silver Building, New York, NY 10003, USA
Leif Arthur Halvorsen
Affiliation:
Department of Chemistry, New York University, 100 Washington Square East, Silver Building, New York, NY 10003, USA
Segun Jung
Affiliation:
Department of Chemistry, New York University, 100 Washington Square East, Silver Building, New York, NY 10003, USA
Xia Xiao
Affiliation:
Department of Chemistry, New York University, 100 Washington Square East, Silver Building, New York, NY 10003, USA
*
*Author for correspondence: T. Schlick, Email: schlick@nyu.edu
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Abstract

We assess the progress in biomolecular modeling and simulation, focusing on structure prediction and dynamics, by presenting the field's history, metrics for its rise in popularity, early expressed expectations, and current significant applications. The increases in computational power combined with improvements in algorithms and force fields have led to considerable success, especially in protein folding, specificity of ligand/biomolecule interactions, and interpretation of complex experimental phenomena (e.g. NMR relaxation, protein-folding kinetics and multiple conformational states) through the generation of structural hypotheses and pathway mechanisms. Although far from a general automated tool, structure prediction is notable for proteins and RNA that preceded the experiment, especially by knowledge-based approaches. Thus, despite early unrealistic expectations and the realization that computer technology alone will not quickly bridge the gap between experimental and theoretical time frames, ongoing improvements to enhance the accuracy and scope of modeling and simulation are propelling the field onto a productive trajectory to become full partner with experiment and a field on its own right.

Type
Review Article
Information
Quarterly Reviews of Biophysics , Volume 44 , Issue 2 , May 2011 , pp. 191 - 228
Copyright
Copyright © Cambridge University Press 2011

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