RT Journal Article
SR Electronic
T1 A Unified De Novo Approach for Predicting the Structures of Ordered and Disordered Proteins
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.01.30.925636
DO 10.1101/2020.01.30.925636
A1 John J. Ferrie
A1 E. James Petersson
YR 2020
UL http://biorxiv.org/content/early/2020/01/31/2020.01.30.925636.abstract
AB As recognition of the abundance and relevance of intrinsically disordered proteins (IDPs) continues to grow, demand increases for methods that can rapidly predict the conformational ensembles populated by these proteins. To date, IDP simulations have largely been dominated by molecular dynamics (MD) simulations, which require significant compute times and/or complex hardware. Recent developments in MD have afforded methods capable of simulating both ordered and disordered proteins, yet to date accurate fold prediction from sequence has been dominated by Monte-Carlo (MC) based methods such as Rosetta. To overcome the limitations of current approaches in IDP simulation using Rosetta while maintaining its utility for modeling folded domains, we developed PyRosetta-based algorithms that allow for the accurate de novo prediction of proteins across all degrees of foldedness along with structural ensembles of disordered proteins. Our simulations have an accuracy comparable to state-of-the-art MD with vastly reduced computational demands.