Professor Ken Dill, Stony Brook University. Part 1. "Accelertaing atomistic simulations of proteins Bayesian inference with unreliable information." Part 2. "Cell biology is sometimes cell physics." Greater Boston Area Theoretical Chemistry Seminar.
Part I: Accelerating atomistic simulations of proteins by Bayesian inference with unreliable information Abstract: Molecular simulations give insights and quantitation to protein folding, drug discovery and the binding of ligands, and biological mechanistic actions in the cell. But, even with current sampling methods, such as Replica Exchange, physical simulations are much too slow, and don't scale well to larger proteins or larger actions. We have developed MELD, which melds together vague external knowledge to accelerate physics-based molecular simulations. I will describe proofs of principle in folding proteins in the blind prediction event called CASP, and in computing binding affinities of peptide ligands to proteins.
Part II: Cell biology is sometimes cell physics Abstract: Some behaviors of cells are not due to single proteins or pathways, but are due to the physical properties of proteomes as a whole. For example, the growth rates of bacteria as a function of temperature or salt can be explained the folding stability and diffusion rates of the proteins in the proteome. Using simple physical models, we explore physical aspects of cell mechanisms and evolution, also including cellular energy balance and proteostasis, the machinery that folds and disaggregates proteins.