אירועים והרצאות בפקולטה למדעי המחשב ע"ש הנרי ומרילין טאוב

Drug development is a long and costly process consisting of several stages that can take many years to complete. One of the early stage's goals is to optimize a novel chemical compound to be active against a target protein associated with the disease. The goal of molecule optimization is, given an input molecule, to produce a new molecule that is chemically similar to the input molecule but with an improved property. In this work, we present a novel approach for optimizing molecules. We propose to represent a molecule by breaking it into two disjoint substructures that we call: the molecule chains and the molecule core. We train a model to generate the molecule chains with the desired properties for optimization, which are then attached to the molecule core to construct a novel molecule with high similarity to the input molecule. We then show how to extend this approach to tasks where data is scarce, such as when attempting to target a drug to a novel protein.