Computational Studies of Protein-Protein Interactions

University Of Chicago, Chicago IL

Investigators

Abstract

One of the most basic questions about the protein molecules in the living cell is the manner by which they interact with one another. How proteins recognize and bind (stick) to the correct partner(s) is one of the ways information is communicated within and between the cells. This is how cells process information and make decisions at the molecular level. Atomic-level information is essential to explain the specific interactions between proteins in terms of structure and dynamics. The research project consists in developing and improving the computer-based approach of "molecular dynamics" to calculate and predict accurately how proteins bind to one another. Molecular dynamics (MD) consists of using Newton's classical equation, force = mass x acceleration, to simulate the motions of all the atoms as a function of time. The MD simulation, although an approximation to the real world, provides detailed information about the time course of the atomic motions that cannot be accessed experimentally. The approach based on atomic models and MD simulations is advantageous because it does not rely on any particular assumption about protein binding. Being able to predict the possible binding partners of a protein from computations will open the door to a much better understanding of living cells. In addition to developing methods that will be of broad utility to the scientific community, the project will provide inter-disciplinary training and mentoring to young scientists at the undergraduate and graduate level (including members of under-represented minorities), as well as outreach to high school students. The research project consists in improving the theoretical and computational methods to calculate and predict accurately how molecules bind to one another. According to the theory of statistical thermodynamics, the quantity that controls the association of molecules is the binding free energy. This mathematically well-defined quantity can be calculated using computer simulations of atomic models of the molecules of interest. Molecular dynamics (MD) simulation can help elucidate the fundamental principles governing the binding of biological molecules at the atomic level. MD consists of constructing detailed atomic models of the macromolecules and using Newton's classical equation, F=MA, to literally simulate the dynamical motions of all the atoms as a function of time. The microscopic forces (the "F" in Newton's equation) are approximated by using a potential function, also called a force field, constructed from simple analytical functions. Validating the accuracy of the force field is also an important use of computations based on MD simulations. 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. Efforts in this area are likely to have a large impact because biology is entering a quantitative era that requires an ability to predict the binding of molecules. The first specific objective of the research is the design and development of novel computational methodologies addressing the specific challenges presented by protein-protein interactions. Sampling the large number of accessible configurations of the solvated proteins is critical. Simply running longer unbiased MD is not going to lead to success, and special enhanced sampling methods are needed to achieve this. The second objective is to validate and test the computational methodology and assess the accuracy of the atomic force field on the basis of well-known protein-protein complexes. It is important to know if the results are correct for the binding free energy, the entropy and enthalpy decomposition, and the kinetic rate of association. In the last stage, the objectives are focused on testing the computational method with respect to increasingly challenging situations. This project is jointly funded by the Molecular Biophysics Cluster in the Division of Molecular and Cellular Biosciences in the Directorate for Biological Sciences and the Chemical Theory, Models, and Computational Methods Program in the Division of Chemistry in the Directorate of Mathematical and Physical Sciences.