The Art and Science of Cyclic Peptide Drug Design: From Experimental Discovery to AI-Driven Computation and the Road Ahead

Cyclic peptides have a special power in the therapeutic space — they're larger and more specific than small molecules, and more permeable and cost-effective than antibodies. These qualities enable them to conquer two of the biggest challenges in modern drug development: prosecuting flat intracellular protein-protein interactions (PPIs) and achieving oral bioavailability for demanding targets.

With over 40 FDA-approved drugs, a global market projected to top $260 billion by 2030, and breakthrough oral agents (JNJ-2113, MK-0616), the field has never been more exciting yet technically demanding. This includes the challenge of translating AI-designed peptides into real-world validated molecules, requiring emerging experimental strategies for rapid synthesis and validation.

This webinar will provide a structured, methodical deep dive into the current cyclic peptide discovery and optimization landscape. What you'll learn:

What you will learn:

The fundamental design principles of cyclic peptides: why macrocyclization confers superior affinity, protease resistance, and membrane permeability

Ways to critically assess computational approaches and AI output, from Rosetta-based GenKIC anchor extension to diffusion-model-based de novo design to physics-informed AI

How dominant experimental discovery platforms differ, and how to level up lead optimization through conformational entropy control, rational potency improvement, and strategies for permeability and metabolic stability

How AI-designed peptides are validated through direct-to-biology (D2B) high-throughput synthesis and rapid no-purification screening

How integrated peptide platforms support end-to-end translation from design to IND-enabling development

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Speakers:

Dongdong Wang, Ph.D.

Co-President of Drug Discovery

Atombeat

Fengping Xiao, Ph.D.

Vice President, Head of Peptide Platform

BioDuro