Premium
Efficient sampling of protein conformational space using fast loop building and batch minimization on highly parallel computers
Author(s) -
Tyka Michael D.,
Jung Kenneth,
Baker David
Publication year - 2012
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.23069
Subject(s) - computer science , sampling (signal processing) , algorithm , workflow , scaling , loop (graph theory) , force field (fiction) , space (punctuation) , protein structure prediction , power (physics) , energy minimization , set (abstract data type) , computational science , parallel computing , protein structure , artificial intelligence , computational chemistry , mathematics , physics , chemistry , geometry , filter (signal processing) , nuclear magnetic resonance , combinatorics , database , quantum mechanics , computer vision , programming language , operating system
Abstract All‐atom sampling is a critical and compute‐intensive end stage to protein structural modeling. Because of the vast size and extreme ruggedness of conformational space, even close to the native structure, the high‐resolution sampling problem is almost as difficult as predicting the rough fold of a protein. Here, we present a combination of new algorithms that considerably speed up the exploration of very rugged conformational landscapes and are capable of finding heretofore hidden low‐energy states. The algorithm is based on a hierarchical workflow and can be parallelized on supercomputers with up to 128,000 compute cores with near perfect efficiency. Such scaling behavior is notable, as with Moore's law continuing only in the number of cores per chip, parallelizability is a critical property of new algorithms. Using the enhanced sampling power, we have uncovered previously invisible deficiencies in the Rosetta force field and created an extensive decoy training set for optimizing and testing force fields. © 2012 Wiley Periodicals, Inc.