Biophysics
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Key Documents

Vijay Pande

Academic Appointments

  • Associate Professor, Chemistry
  • Associate Professor (By courtesy), Structural Biology
  • Associate Professor (By courtesy), Computer Science
  • Member, Bio-X

Contact Information

  • Academic Offices
    Administrative Contact
    Terri Fedelin Administrative Associate

Professional Snapshot

Administrative Appointments

  • Director, Folding@home Distributed Computing Project (2000 - present)
  • Chair, Biophysics Program, Stanford University (2008 - 2014)

Honors and Awards

  • Irving Sigal Young Investigator Award, Protein Society (2006)
  • Teacher-Scholar Award, Dreyfus Foundation (2003)
  • Terman Fellow, Stanford University (2002)
  • TR100, MIT Technology Review (2002)
  • Global Indus Technovators Award, IBC@MIT (2004)

Professional Education

BA: Princeton University, Physics (1992)
PhD: MIT, Physics (1995)

Scientific Focus

Research Interests

The central theme of our research is to develop and apply novel theoretical methods to understand the physical properties of biological molecules, such as proteins, nucleic acids, and lipid membranes, and to apply this understanding to design novel synthetic systems, including small molecule therapeutics. In particular, we are interested in the self-assembly properties of biomolecules: for example, how do protein and RNA molecules fold? How do proteins misfold and aggregate and how can we use our understanding of this process to tackle misfolding related diseases, such as Alzheimer's or Huntington's Disease? How can we design or discover novel small molecules to inhibit this process?

As these phenomena are complex, spanning from the molecular to mesoscopic length scales and the nanosecond to millisecond timescales, our research employs a variety of methods, including statistical mechanical analytic models, Markov State Models, and statistical and informatic methods, as well as Monte Carlo, Langevin dynamics, and molecular dynamics computer simulations on workstations and massively parallel supercomputers, superclusters, and large-scale worldwide distributed computing (see http://folding.stanford.edu). Our work also touches closely in parts with applications of Bayesian statistics to statistical mechanics, as well as novel means for computational small molecule (drug) design (such as novel methods for docking and free energy calculation).

For example, we are currently investigating the nature of protein folding and misfolding, relevant for diseases such as Alzheimer’s and Huntington’s Disease. We have performed simulations of these processes, in all-atom detail on experimentally relevant timescales (milliseconds to seconds), yielding specific predictions of the structural and physical chemical nature of protein aggregation involved in these diseases. These simulation results have then fed into novel computational small molecule drug design methods,...

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