SHARPEN-Systematic Hierarchical Algorithms for Rotamers and Proteins on an Extended Network

Ilya V. Loksha, James R. Maiolo, Cheng W. Hong, Albert Ng, Christopher D. Snow

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


Algorithms for discrete optimization of proteins play a central role in recent advances in protein structure prediction and design. We wish to improve the resources available for computational biologists to rapidly prototype such algorithms and to easily scale these algorithms to many processors. To that end, we describe the implementation and use of two new open source resources, citing potential benefits over existing software. We discuss CHOMP, a new object-oriented library for macromolecular optimization, and SHARPEN, a framework for scaling CHOMP scripts to many computers. These tools allow users to develop new algorithms for a variety of applications including protein repacking, protein-protein docking, loop rebuilding, or homology model remediation. Particular care was taken to allow modular energy function design; protein conformations may currently be scored using either the OPLSaa molecular mechanical energy function or an all-atom semiempirical energy function employed by Rosetta. © 2009 Wiley Periodicals, Inc.
Original languageEnglish (US)
Pages (from-to)999-1005
Number of pages7
JournalJournal of Computational Chemistry
Issue number6
StatePublished - Apr 30 2009
Externally publishedYes


Dive into the research topics of 'SHARPEN-Systematic Hierarchical Algorithms for Rotamers and Proteins on an Extended Network'. Together they form a unique fingerprint.

Cite this