Designing therapeutic peptides that adhere to a range of target product profile criteria is a multiparameter optimization, MPO, problem that is challenging to solve when programs are restricted to a relatively limited number of design ideas.

This talk will address advances in the development and cloud-based deployment of atomistic physics-based computational approaches, which are having an increasing impact on drug discovery in the biopharmaceutical industry. Combining these methods with broader access to experimental ligand-bound structures and computational protein structure models has enabled advances in understanding structure-function relationships and the design of peptide therapeutics for a range of molecular targets from GPCRs to protein-protein interactions. Small-molecule therapeutics have benefited from the availability of accurate computational methods that predict the binding mode and affinity of ligands to their protein targets and other physics-based properties.

With increasing focus on the development of peptide-based therapeutics, including peptidomimetics and macrocycles, which are usually larger and more conformationally flexible than traditional drug-like molecules, atomistic physics-based and structure-based approaches can be applied or adapted for use in the identification and optimization of peptide ligands for proteins. These include molecular docking, relative binding free energy predictions, conformational searches, and structural refinement. For example, refined high- resolution cryogenic-electron microscopy, cryoEM, structures of active-state GPCRs in complex with G-proteins and ligands complemented by molecular dynamics simulations and binding or functional assay data provide key insights into ligand recognition and receptor activation to inform structure-based peptide design.