Conformational searching using a population-based incremental learning algorithm

Long, Stephen M., Tran, Tran T., Adams, Peter, Darwen, Paul and Smythe, M. L. (2011) Conformational searching using a population-based incremental learning algorithm. Journal of Computational Chemistry, 32 8: 1541-1549. doi:10.1002/jcc.21732

Author Long, Stephen M.
Tran, Tran T.
Adams, Peter
Darwen, Paul
Smythe, M. L.
Title Conformational searching using a population-based incremental learning algorithm
Journal name Journal of Computational Chemistry   Check publisher's open access policy
ISSN 0192-8651
Publication date 2011-06
Sub-type Article (original research)
DOI 10.1002/jcc.21732
Volume 32
Issue 8
Start page 1541
End page 1549
Total pages 9
Place of publication Hoboken, NJ, U.S.A.
Publisher John Wiley & Sons
Collection year 2012
Language eng
Formatted abstract
A new population-based incremental learning algorithm for conformational searching of molecules is presented. This algorithm is particularly effective at determining, by relatively small number of energy minimizations, global energy minima of large flexible molecules. The algorithm is also able to find a large set of low energy conformations of more rigid small molecules. The performance of the algorithm is relation to other algorithm is examined via the test molecules: C18H38, C39H80, cycloheptadecane and a set of five drug-like molecules.
Keyword Conformational search
Global minimum
Population-based incremental learning
Computational chemistry
Molecular mechanics
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2012 Collection
School of Physical Sciences Publications
Institute for Molecular Bioscience - Publications
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Citation counts: TR Web of Science Citation Count  Cited 4 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 3 times in Scopus Article | Citations
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Created: Tue, 24 Jan 2012, 14:00:25 EST by Susan Allen on behalf of Institute for Molecular Bioscience