Talks

Ligand-Perturbed Protein Dynamics Enlightened with Hierarchical Markov State Model Analysis

142
reads
Talks

Jung-Hsin Lin

2013-12-25
14:20:00 - 15:10:00

101 , Mathematics Research Center Building (ori. New Math. Bldg.)

Dynamics is a crucial part for understanding the function of a biomolecule. Although information about intramoelcular dynamics is difficult to obtain with experiments, it is rather accessible via molecular dynamics simulations. Recently, microsecond time scale for simulations of membrane proteins, namely, receptors, transporters, pumps, have become widely affordable, and it is therefore timely to ask whether molecular dynamics simulations at this time scale can already provide sufficient dynamical information ready for functional interpretation and to distinguished different functional types of ligands. Standard analyses for dynamics of biomolecules include atomic fluctuations, dynamic cross-correlation matrix (DCCM), principal component analysis, mutual information analysis, etc. However, with the substantial lengthening of time scale, these analyses should be performed with care, especially when molecule conformations are represented in cartesian coordinates. In this talk, I will present how to use a systematic coarse-graining appraoch, namely, Markov State Model Analysis, to analyze the dynamics of a G-protein coupled receptor and its kinetic states to determine the functional types of ligands. With the Markov State Model Analysis, we could reach a very comprehensive dynamic picture of how ligands of different functional types affect the conformational waves of a protein.