Deep learning in modelling the protein–ligand interaction: new pathways in drug development

Abstract

The deep learning technologies have become the driver of the revolutionary changes in scientific research in various fields. The AlphaFold-2 neural network software development that has solved the semicentennial problem of 3D protein structure prediction based on primary amino acid sequence is the most obvious example of using such technologies in structural biology and biomedicine. The use of deep learning methods for the prediction of protein–ligand interactions can considerably simplify predicting, speed up the development of new effective pharmaceuticals and change the concept of drug design.