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Eberly College of Science Department of Chemistry
William G. Noid

William G. Noid

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  • Associate Professor of Chemistry
Office:
528 Chemistry Building
University Park, PA 16802
Email:
(814) 867-2387

Education:

  1. B.S. University of Tennessee, Knoxville 2000.
  2. Ph.D. Cornell University, 2005.

Honors and Awards:

  1. Camille Dreyfus Teacher-Scholar Award 2012
  2. NSF Career Award 2011
  3. Alfred P. Sloan Foundation Research Fellow 2011
  4. Penn State Institute for CyberScience Faculty Fellow 2011
  5. HP Outstanding Junior Faculty Award from the ACS Division of Computers in Chemistry 2010
  6. NIH Ruth L. Kirschstein NRSA postdoctoral fellow 2006-2007
  7. Tunis Wentink Prize (co-recipient) 2005
  8. Wachter award in Theoretical/Physical Chemistry 2003
  9. NSF Graduate Research Fellow 2002-2005
  10. NSF IGERT Fellow in nonlinear dynamics and complex systems 2000-2002

Selected Publications:

Christopher R. Ellis, Buddhadev Maiti, and W. G. Noid.  "Specific and Nonspecific Effects of Glycosylation."  J. Am. Chem. Soc. 134 8184-93 (2012).

Joseph F. Rudzinski and W. G. Noid "The Role of Many-Body Correlations in Determining Potentials for Coarse-Grained Models of Equilibrium Structure" J. Phys. Chem. B DOI: 10.1021/jp3002004 (2012).

Joseph F. Rudzinski and W. G. Noid "Coarse-graining entropy, forces, and structures." J. Chem. Phys. 135 214101 (2011).

Christopher Wostenberg, Sushant Kumar, W. G. Noid, and Scott A. Showalter. "Atomistic simulations reveal structural disorder in RAP74-FCP1 complex." J. Phys. Chem. B 115 13731-9 (2011).

Christopher R. Ellis, Joseph F. Rudzinski, and W. G. Noid "Generalized-Yvon-Born-Green model of toluene." Macromol. Sim. Theory 20 478-95 (2011).

J.W. Mullinax and W.G. Noid.  “Recovering physical potentials from a model protein databank.”  Proc. Natl. Acad. Sci. USA  107 (46) 19867-72. (2010)

C. Wostenberg, W.G. Noid, S.A. Showalter .  “MD simulations of the dsRBP DGCR8 reveal correlated motions that may aid pri-miRNA binding.”  Biophys. J 99 248-56.  (2010)

 J. W. Mullinax and W. G. Noid, “Generalized-Yvon-Born-Green theory for determining coarse-grained interaction potentials.” J. Phys. Chem. C 114 (12) 5661–5674.  (2010)

J. W. Mullinax and W. G. Noid, “Generalized Yvon-Born-Green theory for molecular systems.” Phys. Rev. Lett. 103 198104 (2009).

 J. W. Mullinax and W. G. Noid, “Extended ensemble approach for deriving transferable coarse-grained potentials.” J. Chem. Phys. 131 104110 (2009).

Information:

Theories of statistical mechanics applied to investigate structural biology and, in particular, the physical properties of unfolded and intrinsically disordered proteins; theories for coarse-grained modeling of peptides; ‘knowledge-based’ coarse-grained models; cooperativity in protein folding; classical and quantum mechanical theories for modeling nonlinear vibrational spectroscopy.

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.

Research Interests:

Biological

Theories of statistical mechanics applied to investigate structural biology

Computational / Theoretical

Statistical mechanics of unfolded proteins

Physical

Theories of statistical mechanics applied to investigate structural biology

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