Development of computational techniques for predicting the free energetics of crystalline polymorphs and complex molecules

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Mark Tuckerman of New York University is supported by an award from the Chemical Theory, Models and Computational Methods program in the Chemistry division to develop theoretical and computational methods to address key challenges in determining accurate free energies. (1) In order to determine free energies, it is necessary to sample extensively the complex and extremely high-dimensional probability distribution of possible spatial configurations of the system. (2) Despite the extremely high dimensionality of a system, conformational free energies can often be characterized in terms of a few key variables; however, identifying such variables a priori is highly nontrivial. (3) Accurate free energies require an accurate yet computationally efficient model of the interactions between the atoms in a system. Tuckerman and his research group address these challenges through the development of novel computational techniques and apply these methods to a number of problems in biomolecular structure prediction and crystal polymorphism determination. This proposal is cofunded by the Condensed Matter and Materials Theory Program in the Division of Materials Research.The importance of theory and computation in scientific disciplines such as chemistry, materials science, and biology is now well recognized and, in fact, was recently highlighted in the White House's document on the Materials Genome Initiative, which called for a synergy between theoretical and experimental scientists and industrial engineers. The overarching goal is to accelerate the time between concept and a marketable material. The role of theory and computation will be significantly enhanced through the development of new mathematical approaches that address outstanding challenges in these areas. Efficient computational protocols of the type to be developed in this proposal allow rapid and reliable predictions to be made that could accelerate the development of novel pharmaceuticals by pre-screening compounds that form undesirable polymorphs and speed the determination of structure in biomolecules. This information could not only lead to new drug design strategies involving novel compounds, but could provide important clues about how such molecules function in healthy and unhealthy cellular environments, which will increase our understanding of how certain types of diseases, leading to new therapy targets.