Vijay Pande
Academic Appointments
- Professor, Natural Sciences Cluster - Chemistry
- Member, Bio-X
- Professor (By courtesy), Structural Biology
- Professor (By courtesy), Computer Science
Key Documents
Contact Information
- Academic Offices
Personal Information EmailAlternate Contact Mark Piercy Email
Professional Overview
Administrative Appointments
- Director, Folding@home Distributed Computing Project (2000 - present)
- Chair, Biophysics Program, Stanford University (2008 - 2014)
Honors and Awards
- Michael and Kate Bárány Award for Young Investigators, Biophysical Society (2012)
- Keynote talk, Pacific Symposium in Biocomputing (2011)
- ACS Thomas Kuhn Paradigm Shift Award, American Chemical Society (2010)
- Fellow, American Physical Society (2008)
- Irving Sigal Young Investigator Award, Protein Society (2006)
- Teacher-Scholar Award, Dreyfus Foundation (2003)
Graduate & Fellowship Program Affiliations
Internet Links
Industry Relationships
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Scientific Focus
Current 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 Alzheimers and Huntingtons 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, yielding novel chemical entities with important and interesting impact.
Since such problems are extremely computationally demanding, we have developed distributed computing projects for protein folding dynamics ("Folding@Home": http://folding.stanford.edu) which has attracted over 4,000,000 PCs since the project's beginning in October 1, 2000 and today is recognized as the most powerful supercomputer/supercluster in the world. Such enormous computational resources have allowed us to simulate unprecedented folding timescales (microseconds to milliseconds) and statistical precision and accuracy (such as very accurate and precise free energy calculations). For more details, please see http://pande.stanford.edu.
Publications
- Simulations of the role of water in the protein-folding mechanism. Proc Natl Acad Sci U S A. 2004; (17): 6456-61
- Structural correspondence between the alpha-helix and the random-flight chain resolves how unfolded proteins can have native-like properties. Nat Struct Biol. 2003; (11): 955-61
- Absolute comparison of simulated and experimental protein-folding dynamics. Nature. 2002; (6911): 102-6
- To milliseconds and beyond: challenges in the simulation of protein folding. Curr Opin Struct Biol. 2013; (1): 58-65
- Simbios: an NIH national center for physics-based simulation of biological structures. J Am Med Inform Assoc. 2012 Mar-Apr; (2): 186-9
- A-site residues move independently from P-site residues in all-atom molecular dynamics simulations of the 70S bacterial ribosome. PLoS One. 2012; (1): e29377
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