Prof. Yang Zhang

Protein structure prediction aims to determine the spatial location of every atom in protein molecules from the amino acid sequence by computational simulations, while protein design is a reverse procedure of structure prediction which aims to engineer novel protein sequences that have desirable structure and function. In this talk, we first review recent progress in computer-based protein structure prediction and show that new approaches combining ab initio folding and contact-map prediction can break though the barrier of physics-based protein folding, which resulted in the successful folding of proteins larger than 150 residues in the community-wide blind CASP experiments. Next, we introduce an evolutionary approach to design new functional XIAP (X-linked Inhibitor of Apoptosis Protein) BIR3 domains that bind Smac peptide but do not inhibit caspase-9 proteolytic activity in vitro, representing a new therapeutic potential to change the caspase-9 initiated apoptosis pathway through computer-based de novo protein design

Dr. Yang Zhang is a Professor in the Department of Computational Medicine and Bioinformatics, Department of Biological Chemistry and Department of Biophysics, University of Michigan, Ann Arbor. Research in his lab focuses on protein structure and function prediction, and protein design and engineering. The I-TASSER developed in his lab was ranked as the No. 1 most accurate method for automated structure prediction in the last six CASPs (CASP7-12 from 2006-2016). QUARK was ranked at the top for ab initio structure prediction in CASP9-12. COFACTOR was ranked as the best for protein function prediction in CASP9, and COACH was ranked consistently at the top in the live-bench function prediction experiment (CAMEO). Of note, the I-TASSER server is one of the most widely used resources for protein structure and function predictions, serving for over 100,000 registered users from 139 countries. He received many honors/awards including Alexander von Humboldt Fellowship, Promising Inventor Award at University of Buffalo, Alfred P. Sloan Fellowship Award, NSF Career Award, and Dean’s Basic Science Research Award at University of Michigan, has been selected as the Thomson Reuters Highly Cited Researcher from 2015-2017. He has published 150+ papers in scientific journals and received 22,000+ citations.