Fellowship in Computational Drug Discovery

Philip E. Bourne

Fellowship Director
Philip E. Bourne, Ph.D.
Professor of Pharmacology
Associate Director Protein Data Bank
Editor in Chief PLoS Computational Biology
UCSD Department of Pharmacology
UCSD Skaggs School of Pharmacy and Pharmaceutical Sciences

Research Background

Dr. Bourne is a Professor of Pharmacology at UCSD with a thirty year history in software design, an expert in computational biology and protein structure and founder of four companies.

Dr. Bourne's Laboratory focuses on using macromolecular structure en masse to further our understanding of living systems. Recent research has focused on finding off-target binding sites for major pharmaceuticals and new chemical entities to better understand possible side effects and opportunities for repositioning these compounds. At the heart of our work are new and efficient algorithms for ligand binding site searching, which have:

  1. Established the possible cause of side effects of the class of drugs known as Select Estrogen Receptor Modulators (SERMs) that includes tamoxifen;
  2. Repositioned the Parkinson disease drugs Tolcapone and Entacapone which are COMT inhibitors as suitable leads to treat extreme drug resistant tuberculosis;
  3. Led to the application of systems biology through metabolic, regulatory and signaling networks to explain the side effects of the recently withdrawn cholesterol controlling drug Torcetrapib;
  4. Led to our attempt to understand the positive effects of the protease inhibitor Nelfinavir against certain cancer cell types.

Other relevant areas of research include epitope prediction, the evolutionary history of protein kinases, protein motion, protein-protein interactions, and protein-protein global and local comparison. Dr. Bourne's group maintains the RCSB Protein Data Bank (PDB) as part of collaboration with Rutgers University. They also contribute to the Immune Epitope Database as part of a collaboration with the La Jolla Institute for Allergy and Immunology. More information, including relevant publications is available at: http://www.sdsc.edu/pb/

Fellowship Program Objectives

  • Discover Off-Target Effects of Commercial Pharmaceuticals and NCEs to either improve safety or provide new indications.
  • Provide training in polypharmacology through the application of structural bioinformatics, cheminformatics and systems biology

Coursework and training in:

  • Introduction to computer aided drug design
  • Docking and analysis
  • Protein structure modeling
  • Application of biological networks
  • Structural bioinformatics as applied to drug
    discovery
  • Algorithm development
  • Modeling protein function -Predicting protein-protein and protein-ligand interactions
  • Database development

Unique skills fellows will acquire during the program:

  • Principles of data management and analysis – use of ontologies, metalanguages etc.
  • Data visualization
  • Application of systems biology to drug discovery
  • Advanced programming
  • Advanced algorithm development

Time allocation: Two years