Recorded CDD Webinar: Structure-Activity Relationships and Additivity — Going Beyond Conventional Wisdom
Structure Activity Relationships and Additivity — Going Beyond Conventional Wisdom
Recorded live September 19, 2019
Watch our webinar featuring Drs. James “Guy” Breitenbucher, from the Institute for Neurodegenerative Diseases at UCSF and Peter Gedeck, Research Informatics Senior Scientist at CDD to hear what’s new with theory, experiments, and technologies to grow your understanding of additivity (and non-additivity).
Medicinal chemistry structure-activity relationships have been optimized for decades. So, there is nothing new under the sun — right? Wrong.
Our assumptions about additivity are sometimes correct, but not always. In fact, what one assumes would be the best compound for activity sometimes is not.
Even when optimizing for activities versus a single target-property, unexpected events happen. Proteins, small molecules, and water all move — and all can move in different ways for different compounds.
- See where SAR broke the traditional additivity rules (with experimental co-crystal structure evidence).
- See what frameworks are most practical for understanding different types of underlying SAR patterns.
- And lastly, see new technologies to more rapidly traverse SAR fragment lattices just invented.
Featuring these leading scientists...
James Guy Breitenbucher, Ph.D.
Professor, Department of Neurology, Institute for Neurodegenerative Diseases at UCSF
Dr. Breitenbucher joined the faculty of the IND at UCSF in 2018 with 23 years of experience as a medicinal chemist in the pharmaceutical industry. Guy received his BS and MS in chemistry from California State University, Long Beach, and received his PhD from UC Riverside, where he worked on the synthesis of alkaloid natural products in the labs of Prof. Steve Angle. After receiving his PhD, Guy continued his studies as a postdoctoral fellow with Prof. Clayton Heathcock at UC Berkeley, working on the total synthesis of the anticancer natural product, Discodermolide. Dr. Breitenbucher then joined the medicinal chemistry department at Bristol Myers Squibb in Connecticut, where he worked on antagonists of neuropeptide receptors for the treatment of obesity and diabetes. Later, Guy joined Axys Pharmaceuticals and worked in the department of combinatorial chemistry making significant contributions to drug discovery programs to treat cancer and osteoporosis.
In 1999, Guy joined Johnson & Johnson (J&J) Pharmaceutical Research and Development in San Diego, CA. At J&J, he took on roles as the head of Hit-to-Lead chemistry, and later as Director of Chemistry for the Pain Therapeutic area. Dr. Breitenbucher led numerous drug discovery projects at J&J, resulting in the notable discovery of J&J’s first clinical TRPV1 antagonist for pain and J&J's first clinical FAAH inhibitor for the treatment of PTSD. In 2010, Guy moved to Dart NeuroScience (DNS) to become Senior Director of Discovery Chemistry. In this role, Guy managed all aspects of DNS’s chemistry efforts. Guy’s DNS teams discovered and developed four compounds currently in clinical trials for stroke, cognitive impairment associated with schizophrenia (CIAS), and Parkinson’s disease. Dr. Breitenbucher’s work is documented in over 50 peer-reviewed scientific publications and 45 patents.
At the IND, Dr. Breitenbucher manages the drug-discovery chemistry effort of the institute focused on the discovery of novel therapeutics for the treatment of neurodegenerative disease.
Peter Gedeck, Ph.D.
Senior Scientist, Research Informatics Group, Collaborative Drug Discovery
Dr. Gedeck joined Collaborative Drug Discovery in 2018 as a Senior Scientist in the Research Informatics group. His specialty is the development of machine learning algorithms to support data analysis in pharmaceutical research. He applies his expertise to improve CDD Vault and BioAssayExpress with novel scientific methodologies.
Prior to CDD, he worked for twenty years as a computational chemist in drug discovery at Novartis in the United Kingdom, Switzerland, and Singapore. His research interests include the application of statistical and machine learning methods to problems in drug discovery and cheminformatics.
He holds a PhD in Chemistry from the University of Erlangen-Nürnberg and published his work in over 50 peer-reviewed articles. He is also a co-author of Data Mining for Business Analytics — Using Python (Wiley) and Practical Statistics for Data Scientists (2nd edition, O'Reilly).