Pande group research interests

Theoretical Chemistry: Breaking fundamental barriers in molecular simulation

New paradigms for supercomputing: world-wide distributed computing

Current atomistic simulations are greatly limited by the available computational power. In order to even attempt a direct comparison to experiment, many simulations would need to be run for thousands of years. Distributed computing opens the door to new possibilities. Using 100,000 CPUs distributed throughout the world (“Folding@Home” and well-designed algorithms, one can turn 100,000 CPU days (= 300 years!) into one day of simulation.

Long timescale kinetics: MD simulations of millisecond events in all-atom detail

While the fastest proteins fold in tens of microseconds to milli-seconds, atomistic simulations are limited to the nanosecond regime. How can we break this fundamental impasse? While using many 100,000 CPUs with distributed com-puting can give the raw “horsepower,” clearly well-designed algorithms are needed to efficiently use distributed computing. Indeed, just as 100,000 grad students can’t work together finish 300 years of work in one day, folding simulations must be designed in order to be parallelized to this scale. By taking advantage of the nature of folding kinetics (single ex-ponential behavior of single domain proteins), one can devise natural ways to speed folding simulation 100,000x using distributed computing. This allows us to simulate folding on the millisecond timescale.

Sampling algorithms for more precise free energy calculation

Another great challenge in physical chemistry simulation is the ability to calculate free energies to chemical accuracy and precision (eg to 1 kcal/mol). With such capabilities, one could use simulation in drug lead discovery and refinement. We are devel-oping novel means to use distributed computing to make a fundamental advance, with a 1kcal/mol accuracy in absolute ΔG calculation as our goal.

Biophysical Chemistry: Studying biophysical questions using model systems

Protein folding

For several decades, understanding how proteins self-assemble (or “fold”) has been a challenging problem in physical chemistry with important ramifications for structural biology and nanotechnology. Moreover, understanding protein folding is an important paradigm for many other difficult problems in structural biology and physical chemistry. Our goals have been to develop novel computational methods for greatly pushing the envelope in folding simulation, with a goal of directly and quantitatively predicting all possible experimental observables. Using novel algorithms and the power of Folding@Home, we have been able to, for the first time, simulate folding dynamics directly from the sequence.

RNA folding

RNA folding presents many additional challenges in understanding molecular self-assembly, when compared with protein folding. In particular, RNA molecules are considerably larger, electrostatics plays a much more domi-nant and complex role and the nature of tertiary interactions is considerably more subtle. By combining a tight coupling with experimental col-laborators, we are examining RNA folding on many scales, from atomistic simulations of small RNA motifs to simulations of the entire Tetrahymena ribozyme.

Role of water and co-solvents in protein kinetics and thermodynamics

Water and other co-solvents (such as urea) play an active role on bio-molecular self-assembly. Indeed, the hydrophobic effect is a dominant driving force. How does water influence the nature of biomolecular structure formation and does it play a structural (rather than general continuum) role? Using full-atomistic simulation with quantitative comparison to experiment, we can now start to detail the answers to these questions.

Chemical Biology: Applications to biologically and biomedically important systems

p53 tetramer

Roughly ˝ of all known cancers are due to a mutation in p53. Thus, understanding the nature of this molecule is one of the great challenges of structural biology. Our interests lie primarily in the tetramerization (tet) domain. This domain is both an important part of p53 as well as a fascinating model system for protein folding and oligomerization. Indeed, each monomer in the tet domain is small (~30 resi-dues) and the monomers do not fold in isolation. Thus, folding is an integral part of dimerization.

Collagen folding

Collagen is a surprisingly interest-ing and important molecule. Roughly half of our body’s weight in protein is collagen and it plays a fundamental role in many structural aspects in biology. There are many highly detrimen-tal single point mutations in this very long (~1000 residue) triple helix. We are working with collaborators in Stanford Medical School to connect the nature of these mutations to the structural pheno-type. These results could have an impact on diseases, such as Osteogenesis Im-perfecta (shown on the left).

Alzheimer's Disease (AD)

AD is result of the undesired aggregation of Aβ peptides. Surprisingly, the toxic element is the small oligomers (4-16 monomers) of Aβ. Since Aβ itself is small (42 res), simulation approaches using our advanced methodology for kinetics and thermodynamics should be able to shed light on the nature of the structure and stability of these oligomers.

Folding in vivo

While understanding the nature of folding in vitro is a challeng-ing biophysical question, understanding fold-ing in vivo is the dominant biological question. In collaboration with several experimental groups, we are now performing simulations of folding in biologically relevant conditions and with the important biochemical machinery. While these simulations will be extremely demanding, they should shed insight in ways that were previously impossible.