Samuel Wong (University of Florida): Sequential Monte Carlo methods in protein folding

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 with both lattice protein model and real proteins.

Joint work with Kevin Bartz, Samuel Kou, Jun Liu, Jinfeng Zhang