My focus is thermodynamics and statistical mechanics of biomolecules, addressed theoretically and through computer simulations. A fundamental component of my work is the development of efficient computer algorithms to tackle biological and biomedical problems.

Our goal is to understand and quantify the physical mechanisms underlying the function of biomolecules at increasing levels of complexity. These include macromolecules (e.g., proteins and nucleic acid chains) and smaller organic molecules (e.g., drugs, hormones, neurotransmitters, and other chemical species). Their collective and cooperative interactions inside and outside the cell are fundamental for the function of all living organisms, and perturbations of the delicate balance of these interactions may lead to disease. Understanding how these molecules interact with each other and with the surrounding medium is a basic goal of our work.

Specifically, our work comprises three interrelated areas (click here for representative publications; or here for recent collaborations):

(a) We are interested in understanding the mechanisms of molecular association and dissociation in solutions. The aqueous medium, both in the inracellular and extracellular compartments, controls all the properties of biomolecules, from chemical reactions of small organic compounds to the structure and thermodynamic of macromolecules. In particular, the solvent plays an important role in the dynamics of molecular encounters, ultimately controlling the kinetics of biochemical pathways, macromolecular complexation, and aggregation.

An important component of this work is the development of computationally efficient methods for biomolecular simulations. We are interested in describing interactions at the microscopic (atomistic), mesoscopic, and macroscopic (thermodynamic and hydrodynamic) levels. Our long-term goal is to connect these different levels of description in a common picture, thus providing for a smooth transition between different length scales and time regimes, which in biology span several orders of magnitude. We use atomistic simulations to better understand the underlying forces operating on these systems, and use the insight gained from these 'experiments' as guidelines for the development of simplified computational and theoretical models.

(b) Development and application of computational methods (including Monte Carlo and Molecular Dynamics) to specific problems of biological interest, including applications in structural biology. We use classical molecular mechanics (MM) force fields and quantum mechanics/molecular mechanics (QM/MM) techniques. MM methods are used to study the thermodynamics and structure of macromolecules, and QM/MM to study problems where a higher level of theory is needed to describe chemical reactions.

(c) Understanding the molecular basis of self-organization and pattern formation in nonequilibrium, many-body systems. Specifically, we are interested in the microscopic origin (i.e., at the level of individual units) of macroscopic organization and formation of spatial and temporal structures in biological systems. Although this is a basic problem that concerns many systems in nature, in biology its relevance spans a broad spectrum of phenomena, ranging from complex molecular processes, such as the self-assembly of virus capsids, to macroscopic cellular processes, such as those involved in the cell cycle, to events at the level of organisms, to natural selection and the evolution of species. Mathematical modeling and computer simulations are useful to address these issues, which may help to rationally controlling biological processes and ultimately fight disease.