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Theory of Biomolecular and Cellular Activity

Research Summary

J. Andrew McCammon develops theoretical and computational methods for studying the function of biological molecules. By modeling the structure and dynamics of assemblies of these molecules, McCammon's group develops insights that help in the discovery of new pharmaceuticals.

Molecular movement underlies all cellular processes. Substrates and hormones must diffuse to enzymes and receptors, respectively, to initiate catalytic and signaling events. The binding of such molecules to one another generally requires internal motions, analogous to the fitting of a hand into a glove. The interactions of these molecules have to be highly selective to maintain order in the heavy molecular traffic in and around cells. Our group studies biomolecular and cellular activity, largely by the simulation and analysis of molecular and supramolecular motion on computers.

Molecular Dynamics Simulations
Molecular dynamics simulations are one of our key tools. In a typical simulation, the atoms of a biological molecule—and often those in its solvent surroundings—are represented explicitly in a computer model, and Newton's equations of motion are applied to generate representative trajectories of the atoms. Our recent work has focused on characterizing the motions of such molecules that are of functional importance and on analyzing trajectories to obtain thermodynamic data related to binding specificity. For example, we have identified possible modes of access to the active site of acetylcholinesterase that were not obvious from the x-ray crystallographic structure. In the area of binding specificity, we introduced a rigorous approach based on thermodynamic cycles for using simulations to understand and predict molecular recognition, i.e., the difference in affinity of one ligand-receptor pair compared to a different pair. These methods have proved useful in structure-based drug-discovery applications, e.g., in the development of several different classes of compounds that are now used or have promise for the treatment of HIV infections. (This work is supported in part by the National Science Foundation and the National Institutes of Health.)

Electrostatics and Brownian Dynamics Simulations
Simulations of biological molecules with an explicit model for the surrounding solvent continue to be prohibitively expensive for many systems. Our group has therefore been involved in the development and application of continuum solvation models, particularly those based on the Poisson-Boltzmann electrostatics equation. Such models provide a good description of the free energies of hydration of a wide range of solutes, and of how solvent influences the interaction between pairs of solute molecules, such as an enzyme and a substrate molecule. The continuum solvation models are being exploited in our group and others to understand and predict the acid-base properties of groups in proteins and other biological molecules. This allows accurate assignments of protonation states for the analysis of biomolecular activity. By combining such implicit treatments of solvent with corresponding descriptions of solute motion (e.g., our Brownian dynamics method), it is possible to determine how electrostatic interactions speed the diffusional encounter of certain enzymes and their substrates. (This work is supported in part by the National Institutes of Health.)

Supramolecular and Cellular Activity
Our group is particularly interested in extending the theoretical and computational treatment of biomolecules to supramolecular structures. Brownian dynamics and continuum solvation models are particularly well suited for such studies. Our work has included simulations of substrate handling in enzyme complexes. We are also studying the structure and dynamics of larger assemblages of proteins, such as actin filaments and microtubules. At the largest scales, we are drawing on the increasing knowledge of the structure of cellular structures such as synapses, and of the physicochemical properties of their molecular components, to initiate simulation studies at the cellular level. In addition to the fundamental insights that such studies provide, these new models are expected to prove helpful in future research on drug discovery. (This work is supported in part by the National Institutes of Health.)

As of February 22, 2016

Scientist Profile

Dr. McCammon
University of California, San Diego
Biophysics, Computational Biology