Jiménez-Luna2021 - Coloring molecules for plasma protein binding prediction

By combining a Message-Passing Graph Neural Network (MPGNN) and a Forward fully connected Neural Network (FNN) with an integrated gradients explainable artificial intelligence (XAI) method, the authors developed MolGrad and tested it on a number of ADME predictive tasks such as plasma protein binding prediction as the case for this model. MolGrad incorporates explainable features to facilitate interpretation of the predictions. In this model, they train MolGrad with data from a Plasma-protein binding assay (PPB) to predict the fraction bound in plasma of small molecules. Model Type: Predictive machine learning model. Model Relevance: Fraction of protein bound in plasma. Model Encoded by: Miquel Duran-Frigola (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos6ao8