Strategies for Fast Conformational Searching

University Of California San Francisco, San Francisco CA

Investigators

Abstract

Global optimization plays an important role in computational molecular biology. In computational protein folding and docking with direct applications to drug design, for example, a principal problem is that current conformational search methods are not efficient enough at finding the deep low-energy states on the energy landscapes. The recently developed general Convex Global Underestimator (CGU) method provides dynamic and flexible under-fitting of the energy landscape. It is not hindered by kinetic traps in its search speed, and has been proved successful on docking. Based on all-atom model energy landscapes, we propose new conformational search strategies that combine the general CGU with a physics-based "zipper method" for folding. Our search methods can be efficiently applied to a wide variety of energy profiles. We will test the new search strategies on some small proteins to see if and how often the native states can be reached in all-atom models.