Jan 2019 Methods in molecular biology (Clifton, N.J.)

Building Machine-Learning Scoring Functions for Structure-Based Prediction of Intermolecular Binding Affinity.

Auteurs

Wójcikowski M, Siedlecki P, Ballester PJ

Résumé

Molecular docking enables large-scale prediction of whether and how small molecules bind to a macromolecular target. Machine-learning scoring functions are particularly well suited to predict the strength of this interaction. Here we describe how to build RF-Score, a scoring function utilizing the machine-learning technique known as Random Forest (RF). We also point out how to use different data, features, and regression models using either R or Python programming languages.

Lire l‘article