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Computer simulation of bio-molecules has become a valuable tool for the pharmaceutical industry, promising not only the potential to predict binding affinities for trial drugs, but also the ability to probe molecular interactions in ways that lab experiments cannot. This seminar will present one of the most significant challenges in computer-aided drug design: How to model the effects of solvent molecules on the binding reaction between a trial drug and the target. Our research focuses on advancing numerical methods for simulating solute-solvent interactions using implicit solvent models, which capture solvent effects in an average sense. I will present the essential details of the techniques we have developed. One theme permeates our work: developing efficient numerical algorithms depends critically on understanding the underlying structure of the mathematical model. For example, one important question in drug design is whether a given drug is optimized for its target. By carefully studying the mathematical formulation of this question, we have been able to design a coupled simulation-optimization technique that dramatically reduces the computational requirements for these type of questions.

Jaydeep Bardhan received his S.B. in Electrical Engineering from MIT in June 2000. In June 2001, he received his M. Eng., studying optical MEMS devices with Professor Steve Senturia. He is currently a PhD candidate in the EE department at MIT, advised by Professors Jacob White and Bruce Tidor. He is the recipient of a DOE Computational Science Graduate Fellowship. Jay's thesis focuses on specializing circuit simulation techniques for computational drug design. His current research interests include modeling techniques for bio-molecule electrostatics, biological signaling networks, and solvation processes.

If you reference this work in a publication, please cite as follows:

• Bardhan, Jaydeep (2005), "Computer-Aided Analysis and Design of Bio-molecules," http://www.nanohub.org/resources/183/.

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1. nano/bio
2. research seminar