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For the successful identification and docking of new ligands to a protein target by virtual screening, the essential features of the protein and ligand surfaces must be captured and distilled in an efficient representation. Since the running time for docking increases exponentially with the number of points representing the protein and each ligand(More)
Statistical pattern recognition techniques classify objects in terms of a representative set of features. The selection of features to measure and include can have a significant effect on the cost and accuracy of an automated classifier. Our previous research has shown that a hybrid between a k-nearest-neighbors (knn) classifier and a genetic algorithm (GA)(More)
Peptides have the potential for targeting vaccines against pre-specified epitopes on folded proteins. When polyclonal antibodies against native proteins are used to screen peptide libraries, most of the peptides isolated align to linear epitopes on the proteins. The mechanism of cross-reactivity is unclear; both structural mimicry by the peptide and induced(More)
Water-mediated ligand interactions are essential to biological processes, from product displacement in thymidylate synthase to DNA recognition by Trp repressor, yet the structural chemistry influencing whether bound water is displaced or participates in ligand binding is not well characterized. Consolv, employing a hybrid k-nearest-neighbors(More)
While it may seem intuitive that using an ensemble of multiple conformations of a receptor in structure-based virtual screening experiments would necessarily yield improved enrichment of actives relative to using just a single receptor, it turns out that at least in the p38 MAP kinase model system studied here, a very large majority of all possible(More)
The accessory subunit of the heterodimeric mtDNA polymerase (polgamma) from Drosophila embryos is required to maintain the structural integrity or catalytic efficiency of the holoenzyme. cDNAs for the accessory subunit from Drosophila, man, mouse, and rat have been identified, and comparative sequence alignment reveals that the C-terminal region of about(More)
Our research focuses on developing computational techniques for understanding the relationship between structure and function in proteins. Of particular interest is molecular recognition, the process by which proteins bind only a small, specific subset of the tens of thousands of molecules they encounter in their biological environments. We analyze several(More)
Computational ligand screening is an approach to identify potential protein ligands efficiently using computational rather than experimental techniques. One approach is to test for the ability to identify and dock true ligands from a large number of molecular structures. Using this approach as implemented in our software SLIDE(1), screenings of 100,000-plus(More)
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