Delta Machine Learning to Improve Scoring-Ranking-Screening Performances of Protein-Ligand Scoring Functions
Sign Up to like & getrecommendations! Published in 2022 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.2c00485
Abstract: Protein-ligand scoring functions are widely used in structure-based drug design for fast evaluation of protein-ligand interactions, and it is of strong interest to develop scoring functions with machine-learning approaches. In this work, by expanding the… read more here.
Keywords: scoring ranking; ligand scoring; scoring functions; machine learning ... See more keywords
XLPFE: A Simple and Effective Machine Learning Scoring Function for Protein–Ligand Scoring and Ranking
Sign Up to like & getrecommendations! Published in 2022 at "ACS Omega"
DOI: 10.1021/acsomega.2c01723
Abstract: Prediction of protein–ligand binding affinities is a central issue in structure-based computer-aided drug design. In recent years, much effort has been devoted to the prediction of the binding affinity in protein–ligand complexes using machine learning… read more here.
Keywords: scoring ranking; xlpfe; machine learning; protein ligand ... See more keywords
The development of a scoring and ranking strategy for a patient-tailored adverse drug reaction prediction in polypharmacy
Sign Up to like & getrecommendations! Published in 2020 at "Scientific Reports"
DOI: 10.1038/s41598-020-66611-8
Abstract: Only few applications are currently dealing with personalized adverse drug reactions (ADRs) prediction in case of polypharmacy. The study aimed to develop a patient-tailored ADR web application, considering characteristics from 734 drugs and relevant patient… read more here.
Keywords: patient tailored; severity; scoring ranking; adverse drug ... See more keywords