MolOptimizer: A Molecular Optimization Toolkit for Fragment-Based Drug Design

Adam Soffer, Samuel Joshua Viswas, Shahar Alon, Nofar Rozenberg, Amit Peled, Daniel Piro,Dan Vilenchik,Barak Akabayov

MOLECULES(2024)

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Abstract
MolOptimizer is a user-friendly computational toolkit designed to streamline the hit-to-lead optimization process in drug discovery. MolOptimizer extracts features and trains machine learning models using a user-provided, labeled, and small-molecule dataset to accurately predict the binding values of new small molecules that share similar scaffolds with the target in focus. Hosted on the Azure web-based server, MolOptimizer emerges as a vital resource, accelerating the discovery and development of novel drug candidates with improved binding properties.
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Key words
cheminformatics,fragment screening,hit-to-lead optimization
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