Pre-Training on Large-Scale Generated Docking Conformations with HelixDock to Unlock the Potential of Protein-ligand Structure Prediction Models

arXiv:2310.13913v3 Announce Type: replace
Abstract: Protein-ligand structure prediction is an essential task in drug discovery, predicting the binding interactions between small molecules (ligands) and target proteins (receptors). Recent advances have incorporated deep learning techniques to improve the accuracy of protein-ligand structure prediction. Nevertheless, the experimental validation of docking conformations remains costly, it raises concerns regarding the generalizability of these deep learning-based methods due to the limited training data. In this work, we show that by pre-training on a large-scale docking …

abstract accuracy advances arxiv cs.ce cs.lg deep learning deep learning techniques discovery drug discovery generated interactions ligands molecules potential prediction prediction models pre-training protein proteins q-bio.bm replace scale small training type