AI-ACCELERATED DRUG DISCOVERY
Once a peptide hit has been identified, deciding what to modify next is often the hardest part.
Peptide design is rarely a matter of improving affinity alone. Each modification can affect the peptide’s binding mode, selectivity, physicochemical properties, and developability. Yet many approaches do not fully account for the 3D binding mode, offer limited systematic exploration of amino-acid substitutions, or cannot effectively incorporate non-canonical chemistry and constrained topologies.
Experimental screening can identify binders, including stronger variants, without revealing where or how they bind. Without this structural context, subsequent optimization remains largely unguided.In this webinar, we will discuss how our platform addresses these problems.
Dr. Tomi Sawyer, PDHC Founder and Peptide Discovery advisor to Receptor.AI, will discuss where conventional peptide design approaches reach their practical limits. Dr. Semen Yesylevskyy, CSO of Receptor.AI, will present our structure-guided design framework, benchmark results, and real-world discovery outcomes in which target-aware design succeeded.
Dr. Alan Nafiev, CEO of Receptor.AI, will conclude with how discovery teams can apply and evaluate this approach in their own active peptide programmes.
Watch our presentation from the recent PDHC De Novo Design Webinar
