Benoît Roux: Using Computer Simulations to Advance our Understanding of Biological Systems at the Atomic Level
Classical molecular dynamics (MD) simulations based on atomic models play an increasingly important role in a wide range of applications in physics, biology and chemistry. The approach consists of constructing detailed atomic models of the macromolecular system and, having described the microscopic forces with a potential function, using Newton's classical equation, F=MA, to literally "simulate" the dynamical motions of all the atoms as a function of time. The calculated trajectory, though an approximation to the real world, provides detailed information about the time course of the atomic motions, which is impossible to access experimentally. While great progress has been made, producing genuine knowledge about biological systems using MD simulations remains enormously challenging. Among the most difficult problems is the characterization of large conformational transitions occurring over long time scales. Issues of force field accuracy, the neglect of induced polarization, in particular, are also a constant concern. A powerful paradigm for mapping the conformational landscape of biomolecular systems is to combine free energy methods, transition pathway techniques, and stochastic Markov State Model-based massively distributed simulations. These concepts will be illustrated with a few recent computational studies of Src tyrosine kinases, K+ channels, and the P-type ion pumps.
Classical molecular dynamics (MD) simulations based on atomic models play an increasingly important role in a wide range of applications in physics, biology and chemistry. The approach consists of constructing detailed atomic models of the macromolecular system and, having described the microscopic forces with a potential function, using Newton's classical equation, F=MA, to literally "simulate" the dynamical motions of all the atoms as a function of time. The calculated trajectory, though an approximation to the real world, provides detailed information about the time course of the atomic motions, which is impossible to access experimentally. While great progress has been made, producing genuine knowledge about biological systems using MD simulations remains enormously challenging. Among the most difficult problems is the characterization of large conformational transitions occurring over long time scales. Issues of force field accuracy, the neglect of induced polarization, in particular, are also a constant concern. A powerful paradigm for mapping the conformational landscape of biomolecular systems is to combine free energy methods, transition pathway techniques, and stochastic Markov State Model-based massively distributed simulations. These concepts will be illustrated with a few recent computational studies of Src tyrosine kinases, K+ channels, and the P-type ion pumps.
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