Computational macrocycle design with drug-like properties for targeted therapeutics
Patrick Salveson
VP Research and Discovery, Vilya
Macrocycles have long held the promise of bridging the gap between the membrane permeability of small molecules and the specificity and affinity of large biologics, yet that promise has largely been unrealized. While many library display technologies enable identifying high-affinity binders from this chemical space, downstream optimization of these hits for other drug-like features, chiefly membrane permeability, remains a herculean challenge. At Vilya, we are leveraging recent advances in structure prediction, machine learning, deep learning, and molecular design to surmount this challenge.