We use theoretical and computational methods to advance our understanding of the structure, dynamics and function of biological macromolecular systems at the atomic level.
Research Interests:
The computational approach, called "molecular dynamics" (MD), is central to our 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 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 nearly impossible to access experimentally. We use such all-atom MD simulations to rigorously compute conformational free energies, and binding free energies. We are particularly interested in understanding the function of biomolecular systems. We are also developing new computational approaches (polarizable force field, solvent boundary potentials, efficient sampling methods) for studying biological macromolecular systems. Here are a few area of active research in my group.
Sampling methods
Hybrid algorithms combining nonequilibrium molecular dynamics and Monte Carlo (neMD/MC) offer a powerful avenue for improving the sampling efficiency of computer simulations of complex systems. We developed a novel hybrid sampling propagator combining Metropolis-Hastings Monte Carlo (MC) with proposed moves generated by non-equilibrium MD (neMD). Illustrative tests with specific biomolecular systems indicate that the method can yield a significant speedup (Suh et al., 2018).We also used the neMD/ MC to develop a computational strategy that enables simulations with spontaneous changes in protonation states under conditions of constant pH (Radak et al., 2017). The sampling efficiency can be adaptively improved on the fly by adjusting algorithmic parameters during the simulation. Illustrative examples emphasizing medium- and large-scale applications on next-generation supercomputing architectures are provided.
Polarizable force field
Molecular mechanics force fields that explicitly account for induced polarization represent the next generation of physical models for molecular dynamics simulations. Several methods exist for modeling induced polarization. We have initiated the development of a polarizable force field based on classical Drude oscillators, in which electronic degrees of freedom are modeled by charged particles attached to the nuclei of their core atoms by harmonic springs (Lamoureux et al., 2003). This force field has now been extended to cover ion solvation, phospholipids, and proteins. The Drude polarizable force field is computationally tractable and available in a wide range of simulation packages (CHARMM, NAMD, OPENMM, GROMACS), it is anticipated that use of these more complex physical models will lead to new and important discoveries of the physical forces driving a range of chemical and biological phenomena (Lemkul et al., 2016).
Ion channels and membrane proteins
Our goal is to establish the fundamental physical principles that govern the function of the physiologically critical ion channels and integral membrane proteins. The determination of ion channels structures to high resolution has provided the opportunity to address issues of permeation and selectivity with computations (Bernèche and Roux, 2001; Noskov et al., 2004). We challenged the traditional and widely held view that ion selectivity is derived from nearly rigid binding sites and showed that in contrast to this view, selectivity in K+ channel is controlled by the properties of the flexible carbonyl ligands that line the walls of the channel (Noskov et al., 2004). We formulated a theory showing how to rigorously incorporate asymmetric ion concentration and membrane potential in MD simulations (Roux, 2008). We are currently investigating the atomic basis of C-type inactivation in K+ channels, a process of great physiological significance (Ostmeyer et al., 2013). Recovery from inactivation is very slow, yet, the structural differences between the conductive and inactivated filter are believed to be very small.
Tyrosine kinases inhibitors
Proteins kinases are critically important therapeutic targets. For this reason, the discovery of kinase-specific inhibitors is intensely pursued within the pharmaceutical industry. However, it is increasingly apparent that protein kinases can adopt multiple conformational states, and the relative propensity of those states affects the binding affinity and modality of inhibitors. Even when multiple X-ray structures for a selected target are available, our knowledge of all the relevant conformations remains limited. We use computational methods and Markov State Models (MSM) to resolve these issues, which are important in the rational design and optimization of targeted covalent inhibitors (Shukla et al., 2014; Meng et al., 2018).
Selected References
S. Bernèche and B. Roux. "Energetics of ion conduction through the K+ channel." Nature 414(6859), 73-77 (2001). https://www.nature.com/articles/35102067
G. Lamoureux, A. D. Mackerell, Jr. and B. Roux. "A simple polarizable model of water based on classical Drude oscillators." J. Chem. Phys. 119(10), 5185-5197 (2003). https://aip.scitation.org/doi/10.1063/1.1598191
J. A. Lemkul, J. Huang, B. Roux and A. D. MacKerell, Jr. "An Empirical Polarizable Force Field Based on the Classical Drude Oscillator Model: Development History and Recent Applications." Chem. Rev. 116(9), 4983-5013 (2016). https://pubs.acs.org/doi/abs/10.1021/acs.chemrev.5b00505
Y. Meng, C. Gao, D. K. Clawson, S. Atwell, M. Russell, M. Vieth and B. Roux. "Predicting the Conformational Variability of Abl Tyrosine Kinase using Molecular Dynamics Simulations and Markov State Models." J. Chem. Theo. Comp. 14(5), 2721-2732 (2018). https://pubs.acs.org/doi/abs/10.1021/acs.jctc.7b01170
S. Y. Noskov, S. Bernèche and B. Roux. "Control of ion selectivity in potassium channels by electrostatic and dynamic properties of carbonyl ligands." Nature 431(7010), 830-834 (2004). https://www.nature.com/articles/nature02943
J. Ostmeyer, S. Chakrapani, A. C. Pan, E. Perozo and B. Roux. "Recovery from Slow Inactivation in K+ Channels Controlled by Water Molecules." Nature 501, 121-124 (2013). https://www.nature.com/articles/nature12395
B. K. Radak, C. Chipot, D. Suh, S. Jo, W. Jiang, J. C. Phillips, K. Schulten and B. Roux. "Constant-pH Molecular Dynamics Simulations for Large Biomolecular Systems." J. Chem. Theo. Comp. 13(12), 5933-5944 (2017). https://pubs.acs.org/doi/full/10.1021/acs.jctc.7b00875
B. Roux. "The membrane potential and its representation by a constant electric field in computer simulations." Biophys J 95(9), 4205-4216 (2008).https://www.sciencedirect.com/science/article/pii/S0006349508785606?via%3Dihub
D. Shukla, Y. Meng, B. Roux and V. S. Pande. "Activation pathway of Src kinase reveals intermediate states as targets for drug design." Nat Commun 5, 3397 (2014).https://www.nature.com/articles/ncomms4397
D. Suh, B. K. Radak, C. Chipot and B. Roux. "Enhanced configurational sampling with hybrid non-equilibrium molecular dynamics-Monte Carlo propagator." J. Chem. Phys. 148(1), 014101 (2018).https://aip.scitation.org/doi/full/10.1063/1.5004154