The Simmerling lab at Stony Brook University carries out research in the area of computational structural biology. In particular, the lab focuses on understanding how dynamic structural changes are involved in the behavior of biomolecules, such as proteins and nucleic acids. Recent advances in computer hardware and simulation algorithms have established computational methods as a robust and important component of biomolecular research. These simulations are highly complementary to experimental tools, and methods such as molecular dynamics simulation are able to provide a detailed description of the motions of individual atoms over short timescales that are typically inaccessible to experiment. Simulations are not limited to the averages over time and over large numbers of molecules that prevent crystallographic or NMR experiments from characterizing transiently populated conformations such as important intermediates in multi-step conformational changes. In additional to direct dynamics, treatment of simulation data using statistical mechanics can provide valuable thermodynamic properties such as binding affinities or the free energy profiles resulting from conformational changes.
Molecular Mechanics in Computational Chemistry: An Overview for Undergraduates
Classical molecular mechanics (MM) have become an indispensable tool for studying complex systems that are too large for efficient treatment with quantum mechanics calculations. MM calculations have the potential to complement experimental data, providing unparalleled resolution in time and space. These calculations can also provide direct information on coupling of structural and energetic changes, which are difficult to explore simultaneously using experiments. This talk will cover the basics of force fields, energy minimization and molecular dynamics, along with an introduction to explicit and implicit water models. Several examples of the validation of force fields and solvent models will be presented. The talk will also give a brief summary of an application project that draws on molecular mechanics calculations to gain insight into the complex recognition of DNA sequences by proteins during transcription, replication and repair processes.