William G. Noid

Statistical mechanics of unfolded proteins

Recently there has been renewed interest in understanding the physical properties of partially unfolded proteins.  Somewhat surprisingly, recent experimental evidence suggests that “intrinsically disordered” proteins play a vital role in many critical cellular processes.  Even more significantly, research now indicates that many compact globular proteins will, under appropriate circumstances, partially unfold and aggregate to form insoluble fibrils similar to those observed in debilitating amyloid diseases such as Alzheimer’s and Parkinson’s diseases.

The Noid group combines powerful theories from statistical mechanics with modern computational methods to investigate the physical properties of partially unfolded and intrinsically disordered proteins.  This highly interdisciplinary work evolves at the exciting interface of chemistry, biology, physics, computer science, and applied mathematics.  Moreover, our work promises fruitful collaboration with experimentalists in physical and biological chemistry.

In particular, our group develops and employs new theories for developing low-resolution coarse-grained models from experimental as well as simulation data.  Coarse-grained models are highly computationally efficient and can be used for investigating relatively slow biological processes, such as protein folding.  Moreover, these theories provide new interpretation of experimental results by quantifying the physical properties that stabilize certain structural motifs in partially unfolded proteins.  Additionally our group employs novel quantum-classical correspondence principles for modeling and interpreting modern nonlinear vibrational spectroscopies to gain new insight into the equilibrium structure and dynamics of peptides.

Postdoctoral position available

Our group is currently seeking researchers with doctoral degrees in physical/theoretical chemistry, physics, applied mathematics, biophysics, or computer science.  In particular, those with a solid background in statistical mechanics and applied mathematics are especially encouraged to apply.  Previous experience with computer programming and/or MD simulations will be helpful but is not necessary for applicants.  Available research projects involve deriving and implementing new statistical mechanical theories for (1) “knowledge-based” coarse-grained models that incorporate experimental data; (2) classical nonlinear response theory for molecular systems; and (3) other applications of statistical mechanics for problems in structural biology.  Postdoctoral research in the group will involve some combination of analytic theory, numerical programming and computation, and MD simulation, based upon individual interests and background.  Competitive benefits will be provided.  Interested applicants should submit a CV along with the names of three references via email to Will Noid (wnoid @ chem.psu.edu).