"I am humbled every day by discoveries that increase our understanding of life and disease. I feel fortunate to work with others in developing these discoveries into medicines."
I joined the Computational Drug Discovery group at Genentech in 2009. My role involves developing computational tools and modeling of potential drugs as part of therapeutic project teams. My background is also a mix of software engineering and science; I developed computer-aided design software for several years at Autodesk, Inc. before diving into protein modeling in the Jacobson lab at UCSF. Genentech is a fantastic, collaborative environment that values risk-taking and basic science.
I am very excited to co-mentor a unique Genentech-Stanford University post-doc with Professor Vijay Pande. We aim to identify alternative protein conformations using ultra-large scale simulations that will be useful for drug-discovery and biological understanding.
J Chem Inf Model. 2017 Jun 26;57(6):1265-1275.
I am primarily interested in the development and refinement of physics-based methods for predicting protein-ligand interactions. My work has included analysis of limitations in industry force fields relative to quantum calculations and development of methods for understanding pi-pi interactions. I have also combined fast, statistics-based methods with physics-based rescoring. Ongoing, I am interested in increasing industry use of molecular dynamics and free-energy calculations.