COMPUTATIONAL STUDIES OF COMPLEX PROCESSES IN BIOLOGICAL MACROMOLECULAR SYSTEMS

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This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. free energy sampling simulation permeation channels kinases membranes solvation solvation Abstract: This proposal is the continuation of the projects supported by previous NRAC allocation grants. The projects exploit the advances in molecular dynamics (MD) simulations years with respect to accuracy of force fields, treatment of long-range electrostatics, efficiency of integration algorithms, parallel processing, and other technical issues. Computations based on detailed atomic models can make significant contributions to the understanding of biomolecular systems. It is, however, essential to develop special strategies to get quantitatively meaningful results that can be compared with experiments. Many questions cannot be addressed with simple ``brute force'' MD simulation methods. For example, free energy perturbation and potential of mean force (PMF) calculations with biased sampling methods along multi-dimensional reaction coordinates are an attractive method to overcome the sampling difficulties without sacrificing accuracy. The application of special strategies to large-scale motions in macromolecules remains very challenging. In the current proposal, we describe several computational projects aimed at understanding complex and diverse biological systems such as: potassium channels, tyrosine kinases of the Src family, glutamate receptor, and the development and refinement of a fully polarizable force field for biomolecular simulations using the classical Drude oscillator model. It would not be possible to make meaningful progress in these projects without access to supercomputer resources.