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Powerful simulated-annealing algorithm locates global minimum of protein-folding potentials from multiple starting conformations

dc.contributor.authorSnow, Mark E.en_US
dc.date.accessioned2006-04-28T16:50:16Z
dc.date.available2006-04-28T16:50:16Z
dc.date.issued1992-06en_US
dc.identifier.citationSnow, 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.issn0192-8651en_US
dc.identifier.issn1096-987Xen_US
dc.identifier.urihttps://hdl.handle.net/2027.42/38286
dc.description.abstractProtein-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.extent564476 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherJohn Wiley & Sons, Inc.en_US
dc.subject.otherComputational Chemistry and Molecular Modelingen_US
dc.subject.otherBiochemistryen_US
dc.titlePowerful simulated-annealing algorithm locates global minimum of protein-folding potentials from multiple starting conformationsen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelChemical Engineeringen_US
dc.subject.hlbsecondlevelChemistryen_US
dc.subject.hlbsecondlevelMaterials Science and Engineeringen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumUniversity of Michigan, Scientific Computation Group, 535 W. William St., Ann Arbor, Michigan 48103–4943en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/38286/1/540130507_ftp.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1002/jcc.540130507en_US
dc.identifier.sourceJournal of Computational Chemistryen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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