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SUMMARY:AI-Guided Molecular Design: From Biological Programming to Drug Discovery
DESCRIPTION:Sponsored by ACS Webinars and ACS Publications\n8:00 am-9:30 am\, Online\, Free\, Registration required\n\n\n\nArtificial intelligence is transforming chemistry from analyzing molecules to designing them with unprecedented precision. Join three leading researchers as they explore how AI\, molecular simulations\, and advanced computational workflows are accelerating the discovery of biologics\, therapeutics\, and next-generation antimicrobial inhibitors. \nPranam Chatterjee of the University of Pennsylvania will discuss how generative AI models are enabling the design of programmable biologics\, including peptides\, proteins\, mRNAs\, and metal-sequestering molecules optimized for target binding\, safety\, and efficacy. He will also highlight emerging approaches for controlling protein folding and cell-state transitions. \nShozeb Haider of University College London will examine how molecular recognition dynamics can inform the fight against antibiotic resistance. By combining simulations\, machine learning\, and structural biology\, his team uncovered mechanisms of β-lactamase inhibitor binding that led to the design of N11\, a potent next-generation inhibitor. \nAlexey Zakharov of the National Center for Advancing Translational Sciences at NIH will present an AI-driven framework for hit identification and lead optimization\, demonstrating how machine learning and open-source workflows can efficiently uncover novel\, synthetically accessible drug candidates from ultra-large chemical spaces. \nRegister now to learn how AI-guided design is reshaping molecular discovery\, from programming biological systems and understanding target recognition to identifying and optimizing therapeutic candidates. \nThis ACS Webinar is moderated by Jon Stokes of McMaster University and co-produced with ACS Publications. Join the American Chemical Society this September as we continue to celebrate our 150th Anniversary and feature events that highlight lifelong learning by advancing STEM education\, inclusivity\, professional development\, and mentorship for chemists at every career stage. \n\n\n\n\nWhat You Will Learn\n\nHow generative AI and protein language models are enabling the design of therapeutically ready biologics and programmable molecular systems\nHow molecular simulations\, kinetics\, and machine learning can uncover hidden mechanisms of target recognition and guide rational inhibitor design\nHow qHTS-driven machine learning\, reaction-based SAR modeling\, and scaffold-centric exploration can accelerate hit identification and lead optimization\nHow to navigate ultra-large chemical spaces to discover potent\, synthetically accessible candidates for challenging therapeutic targets\nHow integrating AI across biologics\, small molecules\, and antimicrobial research is transforming the future of drug discovery and molecular engineering\n\n\n\n\n\nEvent Details\n\nWednesday\, September 16\, 2026 @ 11:00am-12:30pm ET\nFree to attend\nSlides will be available on day of the webinar\n\n\n\n\n\nCo-Produced With\n\n\n\n\nACS Publications
URL:https://www.siliconvalleyacs.org/event/ai-guided-molecular-design-from-biological-programming-to-drug-discovery/
LOCATION:Virtual
CATEGORIES:ACS Webinars
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