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Time‐averaged predictions of folded and misfolded peptides using a reduced physicochemical model
Author(s) -
Clarke Oliver J.,
Parker Martin J.
Publication year - 2008
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.20879
Subject(s) - peptide , monte carlo method , amyloid fibril , sequence (biology) , computer science , set (abstract data type) , statistical physics , molecular dynamics , chemistry , protein structure , biological system , computational chemistry , physics , amyloid β , mathematics , biochemistry , biology , medicine , statistics , disease , pathology , programming language
Energy‐based methods for calculating time‐averaged peptide structures are important for rational peptide design, for defining local structure propensities in large protein chains, and for exploring the sequence determinants of amyloid formation. High‐end methods are currently too slow to be practicable, and will remain so for the foreseeable future. The challenge is to create a method that runs quickly on limited computer resources and emulates reality sufficiently well. We have developed a simplified off‐lattice protein model, incorporating semi‐empirical physicochemical potentials, and combined it with an efficient Monte Carlo method for calculating time‐averaged peptide structures. Reasonably accurate predictions are found for a set of small α‐helical and β‐hairpin peptides, and we demonstrate a potential application in measuring local structure propensities in protein chains. Time‐averaged structures have also been calculated for a set of small peptides known to form β‐amyloid fibrils. The simulations were of three interacting peptides, and in each case the time‐averaged structure describes a three‐stranded β‐sheet. The performance of our method in measuring the propensities of small peptides to self‐associate into possible prefibrillar species compares favorably with more detailed and CPU‐intensive approaches. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2008