SBIR-STTR Award

Conventional docking tests take a long time because of the many degrees of freedom. Additionally, large libraries of small molecules are tested without adequately using feedback about their suitability as inhibitors from previous tests. We propose a rapid initial screen that can computationally evaluate large numbers of small molecules so that a subset may be selected for further computational analysis. We test docking using an ingenious biophysics approach that reduces the degrees of freedom, involving topological transformation of the electrostatic and geometric properties of the macromolecule's surface such that the small molecule is tested against surface features without having to calculate the approach. We also use the better inhibitors from previous tests to help choose small molecules for the subsequent tests using a multi-criterial evolutionary distributed computing approach. We also offer the user an interactive graphical environment for trading off the various properties of different inhibitors: efficacy, specificity, etc. Our inhibitor-protein approach can be generalized to the question of finding small molecules that bind to large ones. Our rapid, intelligent search and evaluation within the enormous number of candidate ligands forms the foundation of a more fruitful screen, improving the speed by which the best candidates are discovered

Conventional computational docking typically takes a long time because it has a six-dimensional problem to solve - ligand orientation and ligand position - as well as conformational aspects. Reducing the dimensionality of the problem offers the opportunit

Keywords:
Drug Design, High Throughput, Screening, Computational, Optimization, Docking, Flatworld, Ligand