New York University (NYU) Reports Findings in Machine Learning (Delta Machine Learning to Improve Scoring-Ranking-Screening Performances of Protein-Ligand Scoring Functions)

摘要

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is the subject of a report. According to news originating from New York City, New York, by NewsRx correspondents, research stated, “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 training set, developing physically meaningful features, employing our recently developed linear empirical scoring function Lin_F9 (Yang, C. 2021, 61, 4630-4644) as the baseline, and applying extreme gradient boosting (XGBoost) with D-machine learning, we have further improved the robustness and applicability of machine-learning scoring functions.”