Efficient sampling of protein conformational space using fast loop building and batch minimization on highly parallel computers.

TitleEfficient sampling of protein conformational space using fast loop building and batch minimization on highly parallel computers.
Publication TypeJournal Article
Year of Publication2012
AuthorsTyka, M. D., Jung K., & Baker D.
JournalJournal of computational chemistry
Volume33
Issue31
Pagination2483-91
Date Published2012 Dec 5
ISSN1096-987X
KeywordsPrimary Publication
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.

DOI10.1002/jcc.23069
Custom1

http://www.ncbi.nlm.nih.gov/pubmed/22847521?dopt=Abstract

Alternate JournalJ Comput Chem