Lab Home | Phone | Search
Center for Nonlinear Studies  Center for Nonlinear Studies
 Home 
 People 
 Current 
 Postdocs 
 Visitors 
 Students 
 Research 
 Publications 
 Conferences 
 Workshops 
 Sponsorship 
 Talks 
 Seminars 
 Postdoc Seminars Archive 
 Quantum Lunch 
 Quantum Lunch Archive 
 P/T Colloquia 
 Archive 
 Ulam Scholar 
 
 Postdoc Nominations 
 Students 
 Student Program 
 Visitors 
 Description 
 Past Visitors 
 Services 
 General 
 
 History of CNLS 
 
 Maps, Directions 
 CNLS Office 
 T-Division 
 LANL 
 
Wednesday, September 07, 2011
11:00 AM - 12:00 PM
CNLS Conference Room (TA-3, Bldg 1690)

Postdoc Seminar

Machine Learning Approaches for Characterizing Disordered Protein Dynamics

Joshua L. Phillips
School of Engineering Center for Computational Biology University of California, Merced

Intrinsically disordered proteins undergo conformational changes that are often beyond the scope of current computational techniques used to study the dynamics of folded proteins. New approaches to define a metric for the dynamics of disordered proteins have been developed which are also readily applicable to the study of non-equilibrium globular protein dynamics. We use dimensionality reduction, dimensionality estimation and clustering techniques applied to molecular dynamics (MD) simulations of a class of entirely disordered proteins (outside of a small anchoring domain) involved in nucleocytoplasmic transport, the FG-nucleoporins (FG-nups), as well as folding simulations of several globular proteins of similar size and sequence composition to compare disordered protein dynamics to early-stage folding dynamics. Our results provide detailed maps of the protein conformation space, allow us to classify proteins based on their dynamics, and indicate that disordered protein motion is of higher-dimensionality than earlystage folding dynamics.

Host: Jianhui Tian, T-6: THEORETICAL BIOLOGY AND BIOPHYSICS, tianj@lanl.gov