Harnessing AI & Computational Chemistry: Accelerating Peptide Discovery from Hit Identification to Clinical Candidates
1:01 pm - Tuesday 1st December 2026
Are your AI-driven discovery workflows accelerating innovation, or simply generating more noise?
With AI rapidly transforming peptide discovery, how can you separate genuinely impactful technologies from overhyped solutions? Which computational approaches are delivering measurable improvements in hit identification, optimisation and candidate selection? And how can researchers overcome the limitations of current AI models when designing peptides with non-canonical amino acids and increasingly complex modalities?
This workshop will gather experts to discuss:
- Distinguish between AI tools that deliver real value versus overhyped solutions that waste resources and time
- Master co-folding methods like AlphaFold for identifying binders against challenging targets with non-canonical amino acids
- Learn how molecular dynamics simulations can test and refine co-folding predictions by capturing how peptides behave in motion
- Learn how to combine AI predictions, molecular dynamics simulations and experimental data generation with informed model training for superior hit discovery
- Discover which AI-driven design approaches work for macrocyclic peptides versus structured mini-binders.
