Skip to main content
eScholarship
Open Access Publications from the University of California

UC San Diego

UC San Diego Electronic Theses and Dissertations bannerUC San Diego

Molecular Simulation to Explore Targets in Context

  • Author(s): Kochanek, Sarah Elizabeth
  • Advisor(s): Amaro, Rommie E
  • McCammon, James A
  • et al.
No data is associated with this publication.
Abstract

As the field of computer-aided drug discovery matures, it has become evident that viewing a molecular target independent of its biological context is often an oversimplification. To this end, our lab has developed an all-atom model of an influenza virus particle. In this dissertation, I present analysis of molecular dynamics simulations of this virus particle by Markov state modeling. I begin with the analysis of influenza neuraminidase, which includes construction of a Markov state model to characterize the catalytic site dynamics. This Markov state model provides a quantitative framework for comparison to dynamics of isolated influenza neuraminidase simulations to validate the virus particle model. Next, I identify the probable group 1 influenza hemagglutinin binding site for the antiviral Arbidol. Here, a Markov state model is constructed from the virus particle simulations to characterize the dynamics of the proposed binding site. Finally, I conclude with a recent review outlining multiscale simulation approaches to drug-protein binding, for which Markov state modeling is included.

Main Content

This item is under embargo until January 8, 2022.