Parallel, stochastic measurement of molecular surface area

Biochemists often wish to compute surface areas of proteins. A variety of algorithms have been developed for this task, but they are designed for traditional single-processor architectures. The current trend in computer hardware is towards increasingly parallel architectures for which these algorith...

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Bibliographic Details
Published in:Journal of molecular graphics & modelling Vol. 27; no. 1; pp. 82 - 87
Main Authors: Juba, Derek, Varshney, Amitabh
Format: Journal Article
Language:English
Published: United States Elsevier Inc 01.08.2008
Subjects:
Algorithms
Databases, Protein
GPU
Models, Molecular
Molecular surface
Parallel
Progressive
Proteins - chemistry
Quasi-random
Stochastic
Stochastic Processes
Surface Properties
Time Factors
Progressive
Molecular surface
Parallel
Stochastic
GPU
Quasi-random
ISSN:1093-3263, 1873-4243, 1873-4243
Online Access:Get full text
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Summary:Biochemists often wish to compute surface areas of proteins. A variety of algorithms have been developed for this task, but they are designed for traditional single-processor architectures. The current trend in computer hardware is towards increasingly parallel architectures for which these algorithms are not well suited. We describe a parallel, stochastic algorithm for molecular surface area computation that maps well to the emerging multi-core architectures. Our algorithm is also progressive, providing a rough estimate of surface area immediately and refining this estimate as time goes on. Furthermore, the algorithm generates points on the molecular surface which can be used for point-based rendering. We demonstrate a GPU implementation of our algorithm and show that it compares favorably with several existing molecular surface computation programs, giving fast estimates of the molecular surface area with good accuracy.
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ISSN:1093-3263
1873-4243
1873-4243
DOI:10.1016/j.jmgm.2008.03.001