Powerful simulated-annealing algorithm locates global minimum of protein-folding potentials from multiple starting conformations
dc.contributor.author | Snow, Mark E. | en_US |
dc.date.accessioned | 2006-04-28T16:50:16Z | |
dc.date.available | 2006-04-28T16:50:16Z | |
dc.date.issued | 1992-06 | en_US |
dc.identifier.citation | Snow, Mark E. (1992)."Powerful simulated-annealing algorithm locates global minimum of protein-folding potentials from multiple starting conformations." Journal of Computational Chemistry 13(5): 579-584. <http://hdl.handle.net/2027.42/38286> | en_US |
dc.identifier.issn | 0192-8651 | en_US |
dc.identifier.issn | 1096-987X | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/38286 | |
dc.description.abstract | Protein-folding potentials, designed with the explicit goal that the global energy minimum correspond to crystallographically observed conformations of protein molecules, may offer great promise toward calculating native protein structures. Achieving this promise, however, depends on finding an effective means of dealing with the multiple-minimum problem inherent in such potentials. In this study, a protein-folding-potential test system has been developed that exhibits the properties of general protein-folding potentials yet has a unique well-defined global energy minimum corresponding to the crystallographically determined conformation of the test molecule. A simulated-annealing algorithm is developed that locates the global minimum of this potential in four of eight test runs from random starting conformations. Exploration of the energy-conformation surface of the potential indicates that it contains the numerous local minima typical of protein-folding potentials and that the global minimum is not easily located by conventional minimization procedures. When the annealing algorithm is applied to a previously developed actual folding potential to analyze the conformation of avian pancreatic polypeptide, a new conformer is located that is lower in energy than any conformer located in previous studies using a variety of minimization techniques. | en_US |
dc.format.extent | 564476 bytes | |
dc.format.extent | 3118 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | John Wiley & Sons, Inc. | en_US |
dc.subject.other | Computational Chemistry and Molecular Modeling | en_US |
dc.subject.other | Biochemistry | en_US |
dc.title | Powerful simulated-annealing algorithm locates global minimum of protein-folding potentials from multiple starting conformations | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Chemical Engineering | en_US |
dc.subject.hlbsecondlevel | Chemistry | en_US |
dc.subject.hlbsecondlevel | Materials Science and Engineering | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.subject.hlbtoplevel | Science | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | University of Michigan, Scientific Computation Group, 535 W. William St., Ann Arbor, Michigan 48103–4943 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/38286/1/540130507_ftp.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1002/jcc.540130507 | en_US |
dc.identifier.source | Journal of Computational Chemistry | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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