Drug Designing: Open Access
Open Access

Identifying neuraminidase residues likely to mutate with molecular mechanics free energy

International Conference and Exhibition on Computer Aided Drug Design & QSAR

October 29-31, 2012 DoubleTree by Hilton Chicago-North Shore, USA

Kelly M. Thayer and Konstantin B. Zeldovich

Scientific Tracks Abstracts: Drug Design

Abstract :

An algorithm for identifying residues of neuraminidase which, from an energetic perspective, are highly mutable has been developed. Such residues near the active site are especially interesting because they could potentially confer drug resistance. We began with computing the Gibbs free energy for every possible point mutation in NA using a molecular mechanics based approach which entails finding the optimal conformation of a mutation and all other residues by repacking the side chains of the entire protein using a library of possible side chain conformations. We developed a local energy scoring scheme in which the contributions of the mutated residue and those within two solvation shells are used to compute the energy difference score to mitigate artifactual contributions resulting from the approximation of a fixed backbone. We were then able to compare different positions of the protein with the same wild type residue to identify those which were especially amenable to accommodating mutations. We then investigated such residues further at a higher level of resolution. Our algorithm has blindly identified the well characterized drug resistance sites R292 and H274 in addition to predicting position S246. This novel site is roughly as close to the active site as the known mutations, suggesting its potential importance. Distal mutable sites could be of interest as permissive mutation sites, and several such residues also have been identified. We further explored these sites of interest to elucidate how these readily accessible mutations could affect the binding pocket. The authors acknowledge the support of DARPA (Prophecy Program) and the contributions of all the members of the ALiVE working group.

Biography :

Kelly M. Thayer completed her Ph.D in the area of computational molecular biophysics from Wesleyan University, Middletown, CT in 2004. She subsequently conducted postdoctoral studies at Northwestern University, Massachusetts Insititue of Technology, and Univeresity of Massachusetts Medical School of Worcester. She currently holds a position as a bioinformatician in the Bioinformatics and Integrative Biology program at UMass.