*JACQUES CORBEIL

Computational and machine learning approaches to improve design and screening of peptides in drug discovery

Challenge: Protein-protein interactions (PPI) are well recognized as promising therapeutic targets. Although interfering peptides capable of inhibiting PPIs are receiving increased attention, the identification of those that possess high biological activity is very challenging due to their enormous diversity. There is thus a need to use bioinformatics and machine learning to effectively predict if a compound could be efficacious, which … Read More

*ENRICO PURISIMA

Novel in silico-assisted Platform to Rapidly Enhance Specificity and Affinity of Therapeutic Antibodies Against Their Targets

Challenge: The design of superior biologic therapeutics such as monoclonal antibodies, single-domain antibodies, and engineered proteins requires optimizing their ability to bind to disease targets. Antibodies offer many advantages over small molecules in treating diseases, but the process for generating them is complex, expensive and often requires further steps of affinity maturation to achieve the desired level of potency. Molecular … Read More

*RAFAEL NAJMANOVICH

Detection of Molecular Interaction Field Similarities for the Rational Drug Design of Multi-Functional Inhibitors

Challenge: Binding promiscuity plays a major role in medicine as promiscuous drug interactions may lead to undesirable cross-reactivity effects. This represents a considerable challenge for the pharmaceutical industry. Drugs act by modulating the function of target proteins. However, additional off-site non-target proteins may also be affected due to similarities between binding sites. This unintentional effect may lead to the serendipitous … Read More