The 19th Annual Symposium of the Institute of Chemical Biology and Drug Discovery (ICB&DD) at Stony Brook University focused on the intersection of drug discovery and artificial intelligence. The event, titled “Drug Discovery & AI: Advances and New Directions,” brought together a multidisciplinary audience to discuss how AI is influencing the field.
Organized by Ivet Bahar, director of the Laufer Center for Physical and Quantitative Biology, and co-chair Dima Kozakov, professor of Applied Mathematical Sciences, the symposium was held at the Charles B. Wang Center. Sponsors included the Office of the Vice President for Research, Renaissance School of Medicine, College of Arts and Sciences Department of Chemistry, Hoffman and Baron LLP, and Chembio Diagnostics Systems Inc.
In her opening remarks, Bahar provided a brief history of artificial intelligence in science. Stony Brook Executive Vice President and Provost Carl Lejuez addressed attendees as well, stating: “The importance of multidisciplinary entities on campus such as ICB&DD and its long-lasting record of attracting some of the best faculty to the SBU scientific community.” Iwao Ojima, director of ICB&DD and distinguished professor in the Department of Chemistry, gave an overview of the institute’s mission.
Speakers discussed how AI is beginning to accelerate computer-aided drug discovery. Chris Sander from Harvard Medical School described tools developed in his lab that are changing molecular biology research. These include EVcouplings for linking sequence coevolutionary relations to structural connectivity and CancerRiskNet for identifying cancer risk using machine learning.
Nikolay Dokyolyan from University of Virginia presented YuelDesign, an AI-guided platform for de novo drug design that merges physics-based modeling with AI methods. Marta Filizola from Icahn School of Medicine at Mount Sinai showed how combining AI with high-resolution GPCR structures can refine therapeutics targeting these receptors.
David Koes from University of Pittsburgh highlighted advances in deep learning methods for virtual screening campaigns through tools like Pharmit and Gnina. Maria Wendt from Sanofi explained their Biologics x AI Moonshot program which uses protein language models in R&D efforts.
Patrick Walters from OpenADMET discussed active learning techniques to evaluate binding free energies between drugs and proteins efficiently. Dima Kozakov spoke about bridging atomic scale modeling with proteome-scale interaction networks to identify new therapeutic targets. David LeBard from OpenEye described workflows that detect cryptic pockets for drug binding.
A poster session chaired by Anupam Banerjee featured 83 posters covering medicinal chemistry, structural biology, computational biology, among other topics. Six judges evaluated submissions based on scientific merit, creativity, and clarity.
Awards were given in three categories:
– Computational Biology: Xiaowei Bogetti (Laufer Center) for work on protein conformational dynamics.
– Medicinal Chemistry: Anushka Ojha (Department of Pathology) for research on Gemcitabine-modified miRNA-15a in resistant colorectal cancer.
– Structural Biology: Archana Sudevan (Department of Chemistry) for studying nitric oxide sensing proteins in Burkholderia Thailandensis.
The symposium highlighted ongoing research activity at Stony Brook University related to drug discovery using artificial intelligence approaches.
