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Rapid sampling of all‐atom peptides using a library‐based polymer‐growth approach
Author(s) -
Mamonov Artem B.,
Zhang Xin,
Zuckerman Daniel M.
Publication year - 2011
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.21626
Subject(s) - sampling (signal processing) , fragment (logic) , computer science , atom (system on chip) , polymer , chemistry , computational chemistry , algorithm , biological system , computational science , parallel computing , organic chemistry , filter (signal processing) , computer vision , biology
We adapted existing polymer growth strategies for equilibrium sampling of peptides described by modern atomistic forcefields with a simple uniform dielectric solvent. The main novel feature of our approach is the use of precalculated statistical libraries of molecular fragments. A molecule is sampled by combining fragment configurations—of single residues in this study—which are stored in the libraries. Ensembles generated from the independent libraries are reweighted to conform with the Boltzmann‐factor distribution of the forcefield describing the full molecule. In this way, high‐quality equilibrium sampling of small peptides (4–8 residues) typically requires less than one hour of single‐processor wallclock time and can be significantly faster than Langevin simulations. Furthermore, approximate, clash‐free ensembles can be generated for larger peptides (up to 32 residues in this study) in less than a minute of single‐processor computing. We discuss possible applications of our growth procedure to free energy calculation, fragment assembly protein‐structure prediction protocols, and to “multi‐resolution” sampling. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2011