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Posted: Monday, November 18, 2024Chemistry Department Seminar: 'Artificial Intelligence-Powered Discovery of Small Molecules Inhibiting CTLA-4 in Cancer' - November 21
The Chemistry Department will host a graduate student seminar, “Artificial Intelligence–Powered Discovery of Small Molecules Inhibiting CTLA-4 in Cancer,” presented by Alyssa Heisler, a graduate student in the M.S. forensic science program, on Thursday, November 21, during Bengal Pause (12:15–1:30 p.m.) in Science and Mathematics Complex 173. Donuts and coffee will be served.
Abstract
The development of small molecules targeting immune checkpoint proteins, such as cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), has revolutionized cancer immunotherapy. CTLA-4, an inhibitory receptor on T cells, plays a critical role in downregulating immune responses, and its blockade or inhibition has proved effective in enhancing anti-tumor immunity; however, discovering small molecules that specifically inhibit CTLA-4 remains a complex and intensive process. Recent advancements in artificial intelligence (AI) have significantly affected drug discovery, especially in targeting immune checkpoint proteins like CTLA-4.
AI techniques—including machine learning, deep learning, and predictive modeling—are transforming the landscape of drug discovery by enabling faster, more efficient identification and optimization of promising therapeutic drug candidates. AI models can rapidly analyze large datasets that include chemical libraries, protein structures, and biological assays, allowing them to predict molecular interactions with target proteins such as CTLA-4. AI algorithms are advantageous in screening vast chemical spaces, identifying lead compounds that might be challenging to discover using conventional methods.
The ability of AI to integrate diverse data types provides a deeper understanding of how these inhibitors may interact with the immune system and the molecular mechanisms underlying CTLA-4 inhibition. This progress paves the way for more targeted and personalized therapies. As AI technologies continue to evolve, their role in drug discovery is expected to expand, offering opportunities to accelerate the development of novel small-molecule therapies for cancer immunotherapy and beyond.
