Contact and support
Need help, have a question, or want to contact the ResearchHub team?
© 2026 ResearchHub. Built for responsible scholarly connection.
Privacy-aware community infrastructureResearch graph
References from Addressing docking pose selection with structure-based deep learning: Recent advances, challenges and opportunities. Local targets link to admitted publications; unresolved targets remain external evidence.
Ensemble of structure and ligand-based classification models for hERG liability profiling
10.3389/fphar.2023.1148670 · 2023 · External reference
Molecular docking: a powerful approach for structure-based drug discovery
10.2174/157340911795677602 · 2011 · External reference
10.3390/ijms20112783
10.3390/ijms20112783 · External reference
A review on applications of computational methods in drug screening and design
2020 · External reference
Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins
10.1186/1471-2105-16-s6-s3 · 2015 · External reference
Artificial intelligence in the prediction of protein-ligand interactions: recent advances and future directions
10.1093/bib/bbab476 · 2022 · External reference
Machine-learning methods for ligand–protein molecular docking
10.1016/j.drudis.2021.09.007 · 2022 · External reference
Classical scoring functions for docking are unable to exploit large volumes of structural and interaction data
10.1093/bioinformatics/btz183 · 2019 · External reference
Improving structure-based virtual screening performance via learning from scoring function components
10.1093/bib/bbaa094 · 2021 · External reference
Performance of machine-learning scoring functions in structure-based virtual screening
10.1038/srep46710 · 2017 · External reference
AQDnet: deep neural network for protein–ligand docking simulation
10.1021/acsomega.3c02411 · 2023 · External reference
Machine learning in antibacterial drug design
10.3389/fphar.2022.864412 · 2022 · External reference
Naive prediction of protein backbone phi and psi dihedral angles using deep learning
10.3390/molecules28207046 · 2023 · External reference
Machine-learning scoring functions for structure-based virtual screening
2021 · External reference
10.1021/acs.jcim.8b00545
10.1021/acs.jcim.8b00545 · External reference
PIGNet: a physics-informed deep learning model toward generalized drug-target interaction predictions
10.1039/d1sc06946b · 2022 · External reference
10.1021/ci500080q
10.1021/ci500080q · External reference
DockRMSD: An open-source tool for atom mapping and RMSD calculation of symmetric molecules through graph isomorphism
2019 · External reference
A fully differentiable ligand pose optimization framework guided by deep learning and a traditional scoring function
2023 · External reference
Boosted neural networks scoring functions for accurate ligand docking and ranking
10.1142/s021972001850004x · 2018 · External reference
Combination of pose and rank consensus in docking-based virtual screening: the best of both worlds
10.1039/d1ra05785e · 2021 · External reference
10.1021/acs.jcim.1c01250
10.1021/acs.jcim.1c01250 · External reference
Predicting drug-target interaction using a novel graph neural network with 3d structure-embedded graph representation
10.1021/acs.jcim.9b00387 · 2019 · External reference
A structure-based drug discovery paradigm
10.3390/ijms20112783 · 2019 · External reference
10.1007/s11095-016-2029-7
10.1007/s11095-016-2029-7 · External reference
10.1016/j.drudis.2018.01.039
10.1016/j.drudis.2018.01.039 · External reference
10.1080/17460441.2016.1201262
10.1080/17460441.2016.1201262 · External reference
QSAR modeling for multi-target drug discovery: designing simultaneous inhibitors of proteins in diverse pathogenic parasites
10.3389/fchem.2021.634663 · 2021 · External reference
10.1021/acs.chemrev.8b00728
10.1021/acs.chemrev.8b00728 · External reference
10.1016/j.sbi.2023.102548
10.1016/j.sbi.2023.102548 · External reference
10.1021/acs.jcim.1c01319
10.1021/acs.jcim.1c01319 · External reference
10.1002/cbic.202200776
10.1002/cbic.202200776 · External reference
10.1007/s13244-018-0639-9
10.1007/s13244-018-0639-9 · External reference
Review of image classification algorithms based on convolutional neural networks
2021 · External reference
10.1021/acs.jcim.6b00740
10.1021/acs.jcim.6b00740 · External reference
Scoring functions for protein-ligand binding affinity prediction using structure-based deep learning: a review
10.3389/fbinf.2022.885983 · 2022 · External reference
Unresolved reference
2020 · External reference
Graph neural networks: a review of methods and applications
10.1016/j.aiopen.2021.01.001 · 2020 · External reference
Unresolved reference
2017 · External reference
Graph neural networks for materials science and chemistry
10.1038/s43246-022-00315-6 · 2022 · External reference
Unresolved reference
2022 · External reference
Unresolved reference
2022 · External reference
10.1021/acs.jcim.9b00949
10.1021/acs.jcim.9b00949 · External reference
Unresolved reference
2022 · External reference
10.1038/s41598-020-79682-4
10.1038/s41598-020-79682-4 · External reference
Predicting binding from screening assays with transformer network embeddings
10.1021/acs.jcim.9b01212 · 2020 · External reference
AlphaDrug: protein target specific de novo molecular generation
10.1093/pnasnexus/pgac227 · 2022 · External reference
Deep learning in drug discovery: applications and limitations
10.54097/fcis.v3i2.7575 · 2023 · External reference
Attention is all you need
2017 · External reference
Applications of transformer-based language models in bioinformatics: a survey
10.1093/bioadv/vbad001 · 2023 · External reference
Understanding of machine learning with deep learning: architectures, workflow, applications and future directions
10.3390/computers12050091 · 2023 · External reference
Deep learning: a comprehensive overview on techniques, taxonomy, applications and research directions
10.1007/s42979-021-00815-1 · 2021 · External reference
10.1021/jm030580l
10.1021/jm030580l · External reference
10.1021/jm048957q
10.1021/jm048957q · External reference
Binding MOAD (Mother of All Databases)
10.1002/prot.20512 · 2005 · External reference
10.1016/j.jmb.2019.05.024
10.1016/j.jmb.2019.05.024 · External reference
10.1021/jm061277y
10.1021/jm061277y · External reference
CSAR benchmark exercise of 2010: selection of the protein-ligand complexes
10.1021/ci200082t · 2011 · External reference
CSAR data set release 2012: ligands, affinities, complexes, and docking decoys
10.1021/ci4000486 · 2013 · External reference
Structure-based drug discovery with deep learning*
10.1002/cbic.202200776 · 2023 · External reference
Development of a graph convolutional neural network model for efficient prediction of protein-ligand binding affinities
2021 · External reference
Three-dimensional convolutional neural networks and a crossdocked data set for structure-based drug design
10.1021/acs.jcim.0c00411 · 2020 · External reference
CSAR Benchmark Exercise of 2010: Selection of the Protein–Ligand Complexes
10.1021/ci200082t · 2011 · External reference
10.1021/ci300604z
10.1021/ci300604z · External reference
10.1002/jcc.21334
10.1002/jcc.21334 · External reference
10.1021/acs.jcim.0c00542
10.1021/acs.jcim.0c00542 · External reference
10.1021/acs.jcim.8b00905
10.1021/acs.jcim.8b00905 · External reference
DeepBSP-a machine learning method for accurate prediction of protein-ligand docking structures
10.1021/acs.jcim.1c00334 · 2021 · External reference
KDEEP: protein-ligand absolute binding affinity prediction via 3D-convolutional neural networks
10.1021/acs.jcim.7b00650 · 2018 · External reference
Pose classification using three-dimensional atomic structure-based neural networks applied to ion channel-ligand docking
2021 · External reference
10.1016/j.ymeth.2022.07.009
10.1016/j.ymeth.2022.07.009 · External reference
10.1093/bioinformatics/bty374
10.1093/bioinformatics/bty374 · External reference
10.1021/jm300687e
10.1021/jm300687e · External reference
Combining docking pose rank and structure with deep learning improves protein−ligand binding mode prediction over a baseline docking approach
10.1021/acs.jcim.9b00927 · 2020 · External reference
Predicting protein-ligand docking structure with graph neural network
10.1021/acs.jcim.2c00127 · 2022 · External reference
Empirical scoring functions for structure-based virtual screening: applications, critical aspects, and challenges
10.3389/fphar.2018.01089 · 2018 · External reference
10.1038/s42256-021-00409-9
10.1038/s42256-021-00409-9 · External reference
Boosting Protein-Ligand Binding Pose Prediction and Virtual Screening Based on Residue-Atom Distance Likelihood Potential and Graph Transformer
10.1021/acs.jmedchem.2c00991 · 2022 · External reference
10.1109/bibm55620.2022.9995694
10.1109/bibm55620.2022.9995694 · External reference
an Image Is Worth 16×16 Words: Transformers for Image Recognition At Scale
2021 · External reference
Directional message passing for molecular graphs
2020 · External reference
Aston university
1994 · External reference
Predicting or Pretending: Artificial Intelligence for Protein-Ligand Interactions Lack of Sufficiently Large and Unbiased Datasets
2020 · External reference
DiffDock: diffusion steps, twists
2022 · External reference
Deep learning model for efficient protein–ligand docking with implicit side-chain flexibility
10.1021/acs.jcim.2c01436 · 2023 · External reference
Attention-based interpretable neural network for building cooling load prediction
10.1016/j.apenergy.2021.117238 · 2021 · External reference
