Statistical sampling in protein folding
Samuel Kou (Department of Statistics, Harvard University)
(March 25, 2013 3:00 PM - 3:50 PM)
Predicting the native structure of a protein from its amino acid sequence is a long standing problem. A significant bottleneck of computational prediction is the lack of efficient sampling algorithms to explore the configuration space of a protein. In this talk we will introduce a sequential Monte Carlo method to address this challenge: fragment regrowth via energy-guided sequential sampling (FRESS). The FRESS algorithm combines statistical learning (namely, learning from the protein data bank) with sequential sampling to guide the computation, resulting in a fast and effective exploration of the configurations. We will illustrate the FRESS algorithm through examples.