Prof. Cecelia Clementi "Incorporating Experimental Data into Long Timescales Macromolecular Simulations"

Macromolecular systems are composed of a very large number of atomic degrees of freedom. There is strong evidence suggesting that structural changes occurring in large biomolecular systems at long timescale dynamics may be captured by models coarser than atomistic, although a suitable or optimal coarse-graining is a priori unknown. We propose a systematic approach to learn a coarse representation of a macromolecule from microscopic simulation data. In particular, the definition of effective coarse variables is achieved by partitioning the degrees of freedom both in the structural (physical) space and in the conformational space. Additionally, we discuss a modeling framework that allows to design simplified model to accurately reproduce experimental observables. We demonstrate the approach and we show that, when the correct resolution is used, not only do the optimized coarse models match the experimental data accurately, but additional observables not directly targeted during the optimization procedure are also reproduced.

invited by Prof. Gerhard Stock & Prof. Günter Reiter