个人简介

A.B. Harvard University, 1999 Ph.D. Stanford University, 2005

研究领域

Drug design/protein adhesion and transport/molecular simulation methodology/statistical mechanics

Computer simulations of molecular phenomena are increasingly successful aids to chemical engineering, bioengineering, and materials science. In most cases, experiments will be superior to simulations for answering molecular questions. However, simulation is particularly suited for (1) providing all-atom insight that is inaccessible through experiment and for (2) investigating large numbers of chemical entities and conditions that are expensive or difficult to physically create. As computer power continues to increase exponentially, atomistic simulation will become an even more important tool in the scientific and engineering arsenal. Some of the specific problems that my research group focuses on are: Overcoming drug resistance using quantitative ligand binding simulations. One of the biggest challenges in antiviral drug design is overcoming acquired drug resistance. Most traditional informatics based methods are insufficiently sensitive to identify molecular variants that can effectively act against a diverse viral mutants. Atomistic simulations are approaching the point where they can be used to as an effective tool for rapidly prototyping useful new drugs. We are interested in physically based molecular modeling to solve a range of problems in the design and formulation as drugs, including determining ligand binding affinities and understanding the thermodynamics of the crystal form of drugs. Developing novel simulation algorithms for improved simulations. Physics based simulations at the molecular level are extremely computationally intensive. For condensed phase materials, it is often very difficult to observe the time scales of many molecular phenomena of interest. As we begin to functionalize materials at the nanoscale, there is a great need for improved algorithms and methods to study molecular systems, using improved hardware, software, and theory. We are particularly interested in understanding how to best approximate complex molecular systems with atomistic models with sufficiently high fidelity to make quantitative predictions for molecular design and engineering. Designing nonnatural heteropolymers for biological and materials applications. The wide physical and chemical diversity of biological processes, achieved with a very limited set of chemical building blocks, suggests that the possibilities for introducing novel function in human-engineered materials are far beyond our current capabilities. Designed materials can draw from a much larger range of chemical structure and functionality than exists biologically. If we can add significant chemical diversity to Nature’s already impressive toolkit, what else can be created

近期论文

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J. I. Monroe and M. R. Shirts. Converging free energies of binding in cucurbit[7]uril and octa-acid host-guest systems from SAMPL4 using expanded ensemble simulations, J. Comput. Aid. Mol. Des., 28(4), 401-415 (2014) link L. N. Naden, T. T. Pham, and M. R. Shirts. Linear Basis Function Approach to Efficient Alchemical Free Energy Calculations. 1. Removal of Uncharged Atomic Sites, J. Chem. Theory Comput., 10(3), 1128-1149 (2014) link J. I. Monroe, W. G. El-Nahal and M. R. Shirts, Investigating the mutation resistance of non-nucleoside inhibitors of HIV-RT using multiple microsecond atomistic simulations. Proteins, 82(1), 130-144 (2014) link H. Paliwal and M. R. Shirts, Multistate reweighting and configuration mapping together accelerate the efficiency of thermodynamic calculations as a function of molecular geometry by orders of magnitude. J. Chem. Phys , 138(15), 154108 (2013) link S. Pronk, S. Pali, R. Schulz, P. Larsson, P. Bjelkmar, R. Apostolov, M. R. Shirts, J. C. Smith, P. M. Kasson, D. van der Spoel, B. Hess, E. Lindahl, GROMACS 4.5: A high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics, 29(7), 845-854 (2013) link