DeepAtom: A framework for protein-ligand binding affinity prediction
The cornerstone of computational drug design is the calculation of binding affinity between
two biological counterparts especially a chemical compound, ie a ligand, and a protein …
two biological counterparts especially a chemical compound, ie a ligand, and a protein …
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 …
DeepDTAF: a deep learning method to predict protein–ligand binding affinity
Biomolecular recognition between ligand and protein plays an essential role in drug
discovery and development. However, it is extremely time and resource consuming to …
discovery and development. However, it is extremely time and resource consuming to …
CAPLA: improved prediction of protein–ligand binding affinity by a deep learning approach based on a cross-attention mechanism
Motivation Accurate and rapid prediction of protein–ligand binding affinity is a great
challenge currently encountered in drug discovery. Recent advances have manifested a …
challenge currently encountered in drug discovery. Recent advances have manifested a …
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 …
discovery process. Most of the proposed computational methods predict protein–ligand …
DeepCDA: deep cross-domain compound–protein affinity prediction through LSTM and convolutional neural networks
Motivation An essential part of drug discovery is the accurate prediction of the binding affinity
of new compound–protein pairs. Most of the standard computational methods assume that …
of new compound–protein pairs. Most of the standard computational methods assume that …
Binding affinity prediction for protein–ligand complex using deep attention mechanism based on intermolecular interactions
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 …
the overall cost of drug discovery in structure-based drug design. For accurate predictions …
Atomic convolutional networks for predicting protein-ligand binding affinity
Empirical scoring functions based on either molecular force fields or cheminformatics
descriptors are widely used, in conjunction with molecular docking, during the early stages …
descriptors are widely used, in conjunction with molecular docking, during the early stages …
Onionnet: a multiple-layer intermolecular-contact-based convolutional neural network for protein–ligand binding affinity prediction
Computational drug discovery provides an efficient tool for helping large-scale lead
molecule screening. One of the major tasks of lead discovery is identifying molecules with …
molecule screening. One of the major tasks of lead discovery is identifying molecules with …
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 …
interaction, reduce the time and cost of drug discovery. In this study, we propose a novel …