Do deep learning models really outperform traditional approaches in molecular docking?
Molecular docking, given a ligand molecule and a ligand binding site (called``pocket'') on a
protein, predicting the binding mode of the protein-ligand complex, is a widely used …
protein, predicting the binding mode of the protein-ligand complex, is a widely used …
Diffdock: Diffusion steps, twists, and turns for molecular docking
Predicting the binding structure of a small molecule ligand to a protein--a task known as
molecular docking--is critical to drug design. Recent deep learning methods that treat …
molecular docking--is critical to drug design. Recent deep learning methods that treat …
Machine-learning methods for ligand–protein molecular docking
K Crampon, A Giorkallos, M Deldossi, S Baud… - Drug discovery today, 2022 - Elsevier
Artificial intelligence (AI) is often presented as a new Industrial Revolution. Many domains
use AI, including molecular simulation for drug discovery. In this review, we provide an …
use AI, including molecular simulation for drug discovery. In this review, we provide an …
Deep learning for flexible and site-specific protein docking and design
M McPartlon, J Xu - BioRxiv, 2023 - biorxiv.org
Protein complexes are vital to many biological processes and their understanding can lead
to the development of new drugs and therapies. Although the structure of individual protein …
to the development of new drugs and therapies. Although the structure of individual protein …
Progress in molecular docking
J Fan, A Fu, L Zhang - Quantitative Biology, 2019 - Springer
Background In recent years, since the molecular docking technique can greatly improve the
efficiency and reduce the research cost, it has become a key tool in computer-assisted drug …
efficiency and reduce the research cost, it has become a key tool in computer-assisted drug …
Fabind: Fast and accurate protein-ligand binding
Modeling the interaction between proteins and ligands and accurately predicting their
binding structures is a critical yet challenging task in drug discovery. Recent advancements …
binding structures is a critical yet challenging task in drug discovery. Recent advancements …
Guiding conventional protein–ligand docking software with convolutional neural networks
The high-performance computational techniques have brought significant benefits for drug
discovery efforts in recent decades. One of the most challenging problems in drug discovery …
discovery efforts in recent decades. One of the most challenging problems in drug discovery …
Deep learning in drug design: protein-ligand binding affinity prediction
Computational drug design relies on the calculation of binding strength between two
biological counterparts especially a chemical compound, ie, a ligand, and a protein …
biological counterparts especially a chemical compound, ie, a ligand, and a protein …
Deep learning model for efficient protein–ligand docking with implicit side-chain flexibility
MR Masters, AH Mahmoud, Y Wei… - Journal of Chemical …, 2023 - ACS Publications
Protein–ligand docking is an essential tool in structure-based drug design with applications
ranging from virtual high-throughput screening to pose prediction for lead optimization. Most …
ranging from virtual high-throughput screening to pose prediction for lead optimization. Most …
DeepBSP—a machine learning method for accurate prediction of protein–ligand docking structures
J Bao, X He, JZH Zhang - Journal of chemical information and …, 2021 - ACS Publications
In recent years, machine-learning-based scoring functions have significantly improved the
scoring power. However, many of these methods do not perform well in distinguishing the …
scoring power. However, many of these methods do not perform well in distinguishing the …