Philip, University of Toronto
Method to generate highly stable D-amino acid analogs of bioactive helical peptides using a mirror image of the entire PDB
Using D-amino acids as the building blocks for bioactive peptides can dramatically increase their potency. However, simply swapping regular levorotary amino acids for dextrorotary (D)-amino acids alters the peptide surface topology and function is lost. Current methods to overcome this are not generally applicable and exclude the majority of therapeutic targets. By creating a mirror image of all 111,867 protein structures in the Protein Data Bank (PDB), we convert this repository into a D-peptide database with 2.8 million D-peptide structures. This D-PDB can be searched to find therapeutically active topologies, demonstrated here by the discovery of D-peptide GLP1R and PTH1R agonists. Evaluation of D-PDB coverage suggests that it holds candidates for most therapeutic targets and, thus, potentially contains hundreds of potent drug leads.
Philip M. Kim is an Associate Professor at Donnelly Centre at the University of Toronto. He leads a research laboratory that integrates both “dry” (computational) and “wet” (experimental) methods for biomedical sciences and drug discovery. Before to setting up his lab at the University of Toronto in 2009, he was a postdoctoral fellow at Yale University where he pioneered structural analyses of protein interactions networks and an associate with McKinsey & Co. He holds a Ph.D. from the Massachusetts Institute of Technology and a B.S. in Biochemistry and Physics from the University of Tuebingen.