[HTML][HTML] Binding affinity prediction for protein–ligand complex using deep attention mechanism based on intermolecular interactions

S Seo, J Choi, S Park, J Ahn - BMC bioinformatics, 2021 - Springer
Background Accurate prediction of protein–ligand binding affinity is important for lowering
the overall cost of drug discovery in structure-based drug design. For accurate predictions …

CAPLA: improved prediction of protein–ligand binding affinity by a deep learning approach based on a cross-attention mechanism

Z Jin, T Wu, T Chen, D Pan, X Wang, J Xie… - …, 2023 - academic.oup.com
Motivation Accurate and rapid prediction of protein–ligand binding affinity is a great
challenge currently encountered in drug discovery. Recent advances have manifested a …

[HTML][HTML] Scoring functions for protein-ligand binding affinity prediction using structure-based deep learning: A review

R Meli, GM Morris, PC Biggin - Frontiers in bioinformatics, 2022 - frontiersin.org
The rapid and accurate in silico prediction of protein-ligand binding free energies or binding
affinities has the potential to transform drug discovery. In recent years, several deep learning …

[HTML][HTML] AK-score: accurate protein-ligand binding affinity prediction using an ensemble of 3D-convolutional neural networks

Y Kwon, WH Shin, J Ko, J Lee - International journal of molecular …, 2020 - mdpi.com
Accurate prediction of the binding affinity of a protein-ligand complex is essential for efficient
and successful rational drug design. Therefore, many binding affinity prediction methods …

DeepDTAF: a deep learning method to predict protein–ligand binding affinity

K Wang, R Zhou, Y Li, M Li - Briefings in Bioinformatics, 2021 - academic.oup.com
Biomolecular recognition between ligand and protein plays an essential role in drug
discovery and development. However, it is extremely time and resource consuming to …

DLSSAffinity: protein–ligand binding affinity prediction via a deep learning model

H Wang, H Liu, S Ning, C Zeng, Y Zhao - Physical Chemistry Chemical …, 2022 - pubs.rsc.org
Evaluating the protein–ligand binding affinity is a substantial part of the computer-aided drug
discovery process. Most of the proposed computational methods predict protein–ligand …

[HTML][HTML] SE-OnionNet: a convolution neural network for protein–ligand binding affinity prediction

S Wang, D Liu, M Ding, Z Du, Y Zhong, T Song… - Frontiers in …, 2021 - frontiersin.org
Deep learning methods, which can predict the binding affinity of a drug–target protein
interaction, reduce the time and cost of drug discovery. In this study, we propose a novel …

MGPLI: exploring multigranular representations for protein–ligand interaction prediction

J Wang, J Hu, H Sun, MD Xu, Y Yu, Y Liu… - …, 2022 - academic.oup.com
Motivation The capability to predict the potential drug binding affinity against a protein target
has always been a fundamental challenge in silico drug discovery. The traditional …

Deep scoring neural network replacing the scoring function components to improve the performance of structure-based molecular docking

L Yang, G Yang, X Chen, Q Yang, X Yao… - ACS Chemical …, 2021 - ACS Publications
Accurate prediction of protein–ligand interactions can greatly promote drug development.
Recently, a number of deep-learning-based methods have been proposed to predict protein …

[HTML][HTML] CSConv2d: a 2-D structural convolution neural network with a channel and spatial attention mechanism for protein-ligand binding affinity prediction

X Wang, D Liu, J Zhu, A Rodriguez-Paton, T Song - Biomolecules, 2021 - mdpi.com
The binding affinity of small molecules to receptor proteins is essential to drug discovery and
drug repositioning. Chemical methods are often time-consuming and costly, and models for …