Calculation of Protein-ligand Binding Affinity

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The goal of this research is to understand the basis of molecular recognition in biology. The overall objective is to calculate the binding constant from the structure and chemical properties of the molecules taking part in a reaction to understand the biochemical basis for high affinity binding. The research will use recent theoretical advances in the statistical mechanical treatment of binding, developments in methods for computer simulation of biomolecules, and recent experimental data on protein-ligand complexes. The basic method is to evaluate, using computer simulations, the appropriately weighted interaction free energy between protein and ligand by integrating over all the relevant degrees of freedom of the system: translational, rotational, internal and solvent, leading directly to evaluation of the binding constant. Molecular mechanics methods will be used for the first three components. Implicit solvent methods will be used to render the latter, most expensive integration, tractable. Recent algorithms for implicit solvation are, for the first time, accurate and fast enough to be used within the molecular mechanics integration step, so that the entire calculation can be done in a self-consistent way in a practical amount of computer time. Biological recognition is a fundamental property of proteins and other macromolecules. All living things contain proteins and many life processes rely on the right protein 'recognizing' the right molecule at the right time. A protein may be said to recognize another molecule when it attracts that molecule more strongly, and binds to it more tightly, than the many other molecules present. Strong attraction or binding depends on the protein being complementary in its shape and chemical properties to its binding partner. However, even if the detailed structures of the protein and its target are known, it is not enough to determine how tightly they will bind. To determine this, one would need to know all the different forces that act to attract or repel the two molecules, and sum them up accurately. Since thousands of atoms are involved, this is a formidable task. The approach is to construct a simulation of the protein and its binding partner in their environment on the computer, encoding the laws of physics and chemistry to describe how all the atoms interact, then 'run' computer simulation to determine how tightly the two bind, test the results against experiment, improve the description and repeat, iteratively making the simulation more realistic. This software for simulating protein recognition will be made available to the wider research and teaching community. Software to realistically simulate protein recognition would help researchers understand at a molecular level basic processes in living organisms, such as how cells communicate, and help train students in the principles of molecular recognition & simulation of molecules with computers. Specifically, this software will be used in the yearly course for graduates and undergraduates at the University of Pennsylvania, developed and taught by the PI entitled "Molecular modeling."