Fig. 3: Workflow for computational molecular property prediction.
From: A data science roadmap for open science organizations engaged in early-stage drug discovery
Computational workflow for predicting molecular properties, starting with molecular structure encoding, followed by model selection and assessment, and concluding with the application of models to virtually screen libraries and rank these molecules for potential experimental validation. The process can be cyclical, allowing iterative refinement of models based on empirical data. ADMET: absorption, distribution, metabolism, and excretion–toxicity. ECFP: Extended Connectivity Fingerprints. CDDD: Continuous Data-Driven Descriptor, a type of molecular representation derived from SMILES strings. Entropy: Shannon entropy descriptors50,51.
