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Most chemical reactions are carried out in solution. The solvent surroundings affect such reactions in a variety of important ways. For example, the rates of reactions between ionized molecules are often limited by the rate at which the reactants diffuse through the solvent and come into contact. Also, specific solvation effects often determine the relative free energies or stabilities of reactant, transition state, and product molecules. In our group, we study such phenomena using methods from statistical mechanics. These methods range from simulation studies, in which the equations of motion of the atoms in a model system are solved on a computer, to formal studies in which we develop and solve differential or other equations.
We also use computer models and formal techniques to examine how protein molecules function. The proteins of interest include enzymes and ligand binding proteins such as antibody molecules. The theoretical studies show, for example, how a substrate may be attracted to the active site of an enzyme by electrostatic interactions, and how the atoms within an enzyme move to participate in the catalytic transformation of a bound substrate. These methods are of practical importance in the design of new enzymes that can be synthesized by genetic engineering techniques, and in the design of new drugs that bind strongly to their receptors.
Our simulation studies benefit from the excellent computing facilities to which we have access. These facilities include parallel supercomputers and sophisticated computer graphics systems that allow for the visualization of the atomic dynamics in solutions or protein molecules by virtual reality methods.
Most chemical reactions are carried out in solution. The solvent surroundings affect such reactions in a variety of important ways. For example, the rates of reactions between ionized molecules are often limited by the rate at which the reactants diffuse through the solvent and come into contact. Also, specific solvation effects often determine the relative free energies or stabilities of reactant, transition state, and product molecules. In our group, we study such phenomena using methods from statistical mechanics. These methods range from simulation studies, in which the equations of motion of the atoms in a model system are solved on a computer, to formal studies in which we develop and solve differential or other equations.
We also use computer models and formal techniques to examine how protein molecules function. The proteins of interest include enzymes and ligand binding proteins such as antibody molecules. The theoretical studies show, for example, how a substrate may be attracted to the active site of an enzyme by electrostatic interactions, and how the atoms within an enzyme move to participate in the catalytic transformation of a bound substrate. These methods are of practical importance in the design of new enzymes that can be synthesized by genetic engineering techniques, and in the design of new drugs that bind strongly to their receptors.
Our simulation studies benefit from the excellent computing facilities to which we have access. These facilities include parallel supercomputers and sophisticated computer graphics systems that allow for the visualization of the atomic dynamics in solutions or protein molecules by virtual reality methods.
Research Interests
Papers共 1291 篇Author StatisticsCo-AuthorSimilar Experts
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Journal of chemical information and modelingno. 13 (2024): 5232-5241
Andrew Stokely,Lane Votapka,Marcus Hock,Abigail Teitgen,J Andrew McCammon, Andrew McCullough,Rommie Amaro
crossref(2024)
Bryn N K Lopez,Paulo H O Ceciliato,Yohei Takahashi, Felipe J Rangel, Evana A Salem,Klara Kernig, Kelly Chow,Li Zhang, Morgana A Sidhom,Christian G Seitz, Tingwen Zheng,Richard Sibout,
Plant physiology (2024)
Terra Sztain,Joshua C Corpuz,Thomas G Bartholow, Javier O Sanlley Hernandez,Ziran Jiang,Desirae A Mellor,Graham W Heberlig,James J La Clair,J Andrew McCammon,Michael D Burkart
bioRxiv the preprint server for biology (2023)
bioRxiv : the preprint server for biologyno. 44 (2023): 9926-9934
Biophysical journalno. 3S1 (2023): 328a-328A
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