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Conformational analysis of proteins: Algorithms and data structures for array processing
53
Citations
7
References
1980
Year
Structural BioinformaticsBiomolecular Structure PredictionProtein AnalysisMolecular BiologyPeptide ScienceAnalytical UltracentrifugationEnergy MinimizationData StructuresPrime 350Protein FoldingComputational BiochemistryConformational AnalysisBiophysicsNative StructureBiochemistryConformational StudyProtein ModelingProtein Structure PredictionProtein BioinformaticsStructural BiologyArray ProcessingNatural SciencesComputational BiologyMedicine
Abstract Current efforts to determine the nature of the interactions that influence protein folding involve, among other things, minimization of an appropriate empirical conformational energy function (ECEPP, Emprical Conformational Energy Program for Peptides) to obtain the native structure. Because of the prohibitive cost of such a massive computational project, either on a conventional large‐scale machine at a self‐supporting installation or on a dedicated minicomputer, an alternative computer hardware system has been developed to aid in the conformational analysis of proteins. It consists of a Floating Point Systems AP‐120B array processor and a Prime 350 minicomputer host. A version of ECEPP has been adapted to run on the AP‐120B. The data structures and algorithms chosen for this version reflect the highly unusual parallel architecture of this machine. Benchmark comparisons with BPTI (Bovine Pancreatic Trypsin Inhibitor), a protein of 58 residues and a known structure, have been carried out on this system as well as on an IBM 370/168. They show a significant advantage in speed for the AP‐120B/Prime 350 system as well as a substantially lower cost. An energy minimization of BPTI with 154 variable dihedral angles is reported, an effort heretofore prohibited by the computer costs involved.
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