Anna KapeliukhaPOEM — A New Approach for Hit Identification for Challenging TargetsIdentifying druggable pockets or binding sites on target proteins is a crucial aspect of drug discovery, as it directly influences the…Aug 26Aug 26
Anna KapeliukhaNMR-based chemical representation for molecular properties predictionPrediction of molecular properties is probably one of the most popular uses of machine learning in chemistry. As the quality of the…Jul 21Jul 21
Anna KapeliukhaCost-aware prioritization of molecules for synthesis with SPARROWEfficient prioritization of compounds for synthesis conJul 141Jul 141
Anna KapeliukhaFragGrow: A Web Server for Fragment Growing within ConstraintsExploring new promising approaches to fragment growing,Jun 15Jun 15
Anna KapeliukhaCollecting Human Feedback for Generative Models — Metis User InterfaceThoughts on how de novo molecule generation can benefit from integrating feedback from real chemists.Jun 2Jun 2
Anna KapeliukhaProspective de novo drug design with deep interactome learningOverview of K. Atz et. al introduced a new computational approach — DRAGONFLY, that utilizes interactome-based deep learning for generating…May 18May 18
Anna KapeliukhaREAL Fragment Library — Efficient fragment growing inside Enamine REALFind out more about how you can grow your fragments inside Enamine REAL using the REAL Fragment Library…Apr 4Apr 4
Anna KapeliukhaADMET-AI: A machine learning ADMET prediction platform. Article reviewWith the rapidly increasing amounts of chemical data, it is still a huge problem to characterize it and be able to predict the properties…Jan 21Jan 21
