The Impact of CrystallographicData for the Development of Machine Learning Models to Predict Protein-Ligand Binding Affinity.

CONCLUSION: The rapid increase in the number of crystal structures of protein-ligand complexes created a favorable scenario for developing machine learning models to predict binding affinity. These models rely on experimental data from two sources, the structural and the affinity data. The combination of experimental data generates computational models that outperform classical scoring functions.
PMID: 33568025 [PubMed - as supplied by publisher]

Source: Current Medicinal Chemistry - February 10, 2021 Category: Chemistry Authors: Veit-Acosta M, de Azevedo Junior WF Tags: Curr Med Chem Source Type: research