Supervised Machine Learning Methods Applied to Predict Ligand- Binding Affinity

Volume: 24, Issue: 23
Published: Sep 11, 2017
Abstract
Background: Calculation of ligand-binding affinity is an open problem in computational medicinal chemistry. The ability to computationally predict affinities has a beneficial impact in the early stages of drug development, since it allows a mathematical model to assess protein-ligand interactions. Due to the availability of structural and binding information, machine learning methods have been applied to generate scoring functions with good...
Paper Details
Title
Supervised Machine Learning Methods Applied to Predict Ligand- Binding Affinity
Published Date
Sep 11, 2017
Volume
24
Issue
23
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