FALCON: Zero in on the Native Protein Structure


Friday, February 1, 2008, 15:30pm - Friday, February 1, 2008, 16:30pm

325b ITE

algorithms, bioinformatics

Protein structure prediction has been a heuristic science. From homology modeling, threading, to Monte Carlo fragment assembly, decoy clustering, selection, refinement, and consensus, there is no unified model or theory governing the complete process.

We believe the protein structure prediction problem will only be solved by a simple computational model. We wish to find a single and simple mathematical model that encompasses all of above paradigms and that takes a sequence and converges to a near-native protein structure. We propose such a theory, integrating ideas from fragment assembly, hidden Markov model sampling, and Ramachandran basins. Our initial implementation, FALCON, of this theory converges to near-native structures on short benchmark protein sequences, and produces significantly better protein structures than the best programs in this field.

Joint work with: Shuaicheng Li, Dongbo Bu, and Jinbo Xu.

Yaacov Yesha

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