Learning Molecular Representations for Medicinal Chemistry
Kangway V. Chuang, Laura M. Gunsalus, Michael J. Keiser
Abstract
molecular representations directly from data. In this review, we discuss how active research in molecular deep learning can address limitations of current descriptors and fingerprints while creating new opportunities in cheminformatics and virtual screening. We provide a concise overview of the role of representations in cheminformatics, key concepts in deep learning, and argue that learning representations provides a way forward to improve the predictive modeling of small molecule bioactivities and properties.
Topics & Concepts
CheminformaticsVirtual screeningMolecular descriptorDrug discoveryRepresentation (politics)ChemistryArtificial intelligenceData scienceInformaticsDeep learningQuantitative structure–activity relationshipComputer scienceKey (lock)Property (philosophy)Machine learningComputational chemistryEpistemologyEngineeringPolitical scienceBiochemistryPhilosophyPoliticsElectrical engineeringLawComputer securityComputational Drug Discovery MethodsMachine Learning in Materials ScienceProtein Structure and Dynamics