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An efficient parallel algorithm for accelerating computational protein design.


ABSTRACT:

Motivation

Structure-based computational protein design (SCPR) is an important topic in protein engineering. Under the assumption of a rigid backbone and a finite set of discrete conformations of side-chains, various methods have been proposed to address this problem. A popular method is to combine the dead-end elimination (DEE) and A* tree search algorithms, which provably finds the global minimum energy conformation (GMEC) solution.

Results

In this article, we improve the efficiency of computing A* heuristic functions for protein design and propose a variant of A* algorithm in which the search process can be performed on a single GPU in a massively parallel fashion. In addition, we make some efforts to address the memory exceeding problem in A* search. As a result, our enh

SUBMITTER: Zhou Y 

PROVIDER: S-EPMC4058937 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

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