This project develops a conceptually novel theory and robust computational technologies to investigate biomolecular interactions in aqueous solutions. Such interactions influence significantly protein folding, molecular recognition, and many other biological processes. One of the crucial properties of such interactions is the capillarity evaporation or dewetting that can affect critically the solvation free energy and biomolecular structures. The goal of this project is to better understand such hydrophobic interactions in biomolecular systems and to create a state-of-the-art computational program for molecular recognition. The new variational model couples all the dispersive, non-polar, and polar interactions to local geometry in a free-energy functional. This theoretical model and the level-set numerical method can well describe the hydrophobic interaction and complex free-energy landscapes of biomolecular systems that are generally not correctly captured in established implicit-solvent models. Sophisticated numerical methods for electrostatics are developed to couple with the level-set method. Further model refinement to include solute molecular mechanics and stochastic effects can lead to a new computer program for molecular recognition that will significantly improve the existing ones whose unsatisfactory performances have been widely recognized. The success of the project will reduce the high cost for experiments and speed up the process of drug discovery. The natural collaborations among mathematics, biosciences, and pharmaceutical industry in the proposed research make it convenient to transform the mathematical research into the life-saving reality. This highly interdisciplinary project brings exciting opportunities for students and postdoctoral researchers to receive training in mathematical bioscientific research and to gain experience of working in biomedical industry. The project also provides material for an urgently needed course on mathematical and computational molecular biology.
One of the central objectives of computer-aided drug design is to dock efficiently and accurately small molecules to a target, large biomolecule in solution. This project provides a sophisticated way of such docking, and hence a better drug design program.
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