Journal of Computational Chemistry
Ab initio Tertiary Structure Prediction of Proteins
Journal of Global Optimization
Molecular conformation of n-alkanes using terrain/funneling methods
Journal of Global Optimization
Enhanced bounding techniques to reduce the protein conformational search space
Optimization Methods & Software - GLOBAL OPTIMIZATION
Journal of Global Optimization
On potential energy models for ea-based ab initio protein structure prediction
Evolutionary Computation
A network flow model for biclustering via optimal re-ordering of data matrices
Journal of Global Optimization
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A deterministic global optimization method is described for identifying the global minimum potential energy conformation of oligopeptides. The ECEPP/3 detailed potential energy model is utilized for describing the energetics of the atomic interactions posed in the space of the peptide dihedral angles. Based on previous work on the microcluster and molecular structure determination [21, 22, 23, 24], a procedure for deriving convex lower bounding functions for the total potential energy function is developed. A procedure that allows the exclusion of domains of the (ø, ψ) space based on the analysis of experimentally determined native protein structures is presented. The reduced disjoint sub-domains are appropriately combined thus defining the starting regions for the search. The proposed approach provides valuable information on (i) the global minimum potential energy conformation, (ii) upper and lower bounds of the global minimum energy structure and (iii) low energy conformers close to the global minimum one. The proposed approach is illustrated with Ac-Ala4-Pro-NHMe, Met-enkephalin, Leu-enkephalin, and Decaglycine.