Protein structure prediction using fold templates


The current BCL::Fold protein structure prediction method uses a pure de novo algorithm.  Secondary structure elements (SSEs) are assembled in a Monte Carlo fashion and scored based on coarse knowledge-based potentials.  The probability of generating meaningful SSE placements can be enhanced by using structures known to occur in nature.  Fold templates that describe SSE orientations were directly derived from protein structures in the PDB.  Assembling protein models using these fold templates should both speed up the algorithm and improve accuracy of the predicted final models.

Current Project Members: Axel Fischer , Marcin J. Skwark
Alumni Project Members: Brian Weiner