Xavier Morelli
Papers
1
Total Citations
72
H-Index
1
About
Xavier Morelli is a leading figure in computational drug discovery, whose work sits at the intersection of structural biology, cheminformatics, and artificial intelligence. His primary research focuses on developing innovative strategies for hit-to-lead optimization, a critical bottleneck in early-stage drug development. Morelli is best known for pioneering the Diversity-Oriented-Target-Focused-Synthesis (DOTFS) approach, an integrated strategy that automates and accelerates the lead optimization process by combining fragment growing with targeted chemical synthesis. His landmark 2018 paper on this methodology, which has garnered over 70 citations, provides a time- and cost-efficient framework that has reshaped how researchers navigate the complex journey from initial fragment hits to viable drug leads. Beyond this core contribution, Morelli’s work often integrates machine learning models to predict protein-ligand interactions, enhancing the precision of virtual screening. His research has had a tangible impact on the design of novel therapeutics, particularly in oncology and rare diseases. As a sought-after collaborator and mentor, Morelli continues to push the boundaries of rational drug design, making him a pivotal voice in the next generation of computational pharmacology.
Research Focus
Key Achievements
Top Papers
- 1