To register, sign in using your ACS ID.
Log InDon't have an ACS ID? It's free and easy to create one »
Artificial 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.
Pranam 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.
Shozeb 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.
Alexey 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.
Register 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.
This 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.
What You Will Learn
- How generative AI and protein language models are enabling the design of therapeutically ready biologics and programmable molecular systems
- How molecular simulations, kinetics, and machine learning can uncover hidden mechanisms of target recognition and guide rational inhibitor design
- How qHTS-driven machine learning, reaction-based SAR modeling, and scaffold-centric exploration can accelerate hit identification and lead optimization
- How to navigate ultra-large chemical spaces to discover potent, synthetically accessible candidates for challenging therapeutic targets
- How integrating AI across biologics, small molecules, and antimicrobial research is transforming the future of drug discovery and molecular engineering
Event Details
- Wednesday, September 16, 2026 @ 11:00am-12:30pm ET
- Free to attend
- Slides will be available on day of the webinar
Co-Produced With
BECAUSE PEOPLE
LIKE YOU CREATE
GREAT CHEMISTRY
You Belong Here
