The objective of my research is to investigate the structure, dynamics, and function of complex macromolecular biological systems using computational methods. My efforts are aimed at understanding the fundamental processes involving the cell membrane, such as permeation, excitability, signaling, and fusion. The specific questions we focus on are: What are the microscopic mechanisms by which channels achieve a high conductivity and remain selective? What is the molecular basis for the specificity and gating of an ion channel? Which specific amino acids are responsible for the selectivity to potassium, sodium, chloride and calcium ions? What is the molecular basis for the voltage gating of an ion channel? How can one use limited information from experiments to deduce the structure of membrane proteins?

Advances in X-ray crystallography, high resolution NMR and solid state NMR provide atomic resolution structures of membrane proteins, giving fresh impetus to efforts directed at an improved understanding of the mechanism involved in the function of the cell membrane. Knowledge of the 3D structure of proteins is key for understanding their function. However, the complexity of macromolecular biological systems is such that relating a structure to a function remains a great challenge. Macromolecular systems cannot be understood in term of a static atomic structure. The problems arise because the underlying microscopic process may involve hidden energetic factors, or may be governed by a chain of events that has an intrinsic dynamical character, and the influence of the surrounding environment may be difficult to evaluate. The need to consider dynamics is well exemplified in the case of membrane transport systems, where computational models have proven valuable for understanding ion permeation, selectivity and channel gating.

The computational approach called "molecular dynamics" (MD) is central to my work. It 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. MD, however, is not sufficient and we also use other computational approaches at different levels of approximation. Those include continuum electrostatics based on the Poisson-Boltzmann (PB) equation, stochastic Brownian dynamics, and mean-field models based on statistical mechanical integral equations.

e-mail: benoit.roux@med.cornell.edu

Further Information:
http://physiology.med.cornell.edu/faculty/roux/index.html