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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

InteractionGraphNet: A Novel and Efficient Deep Graph Representation Learning Framework for Accurate Protein–Ligand Interaction Predictions
Dejun Jiang, Chang‐Yu Hsieh, Zhenhua Wu, et al.
Journal of Medicinal Chemistry (2021) Vol. 64, Iss. 24, pp. 18209-18232
Closed Access | Times Cited: 169

Showing 1-25 of 169 citing articles:

Accurate structure prediction of biomolecular interactions with AlphaFold 3
Josh Abramson, Jonas Adler, Jack Dunger, et al.
Nature (2024) Vol. 630, Iss. 8016, pp. 493-500
Open Access | Times Cited: 3289
On the Frustration to Predict Binding Affinities from Protein–Ligand Structures with Deep Neural Networks
Mikhail Volkov, Joseph-André Turk, Nicolas Drizard, et al.
Journal of Medicinal Chemistry (2022) Vol. 65, Iss. 11, pp. 7946-7958
Open Access | Times Cited: 130
Boosting Protein–Ligand Binding Pose Prediction and Virtual Screening Based on Residue–Atom Distance Likelihood Potential and Graph Transformer
Chao Shen, Xujun Zhang, Yafeng Deng, et al.
Journal of Medicinal Chemistry (2022) Vol. 65, Iss. 15, pp. 10691-10706
Closed Access | Times Cited: 113
Structure-based drug design with geometric deep learning
Clemens Isert, Kenneth Atz, Gisbert Schneider
Current Opinion in Structural Biology (2023) Vol. 79, pp. 102548-102548
Open Access | Times Cited: 99
TANKBind: Trigonometry-Aware Neural NetworKs for Drug-Protein Binding Structure Prediction
Wei Lu, Qifeng Wu, Jixian Zhang, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 96
Scoring Functions for Protein-Ligand Binding Affinity Prediction Using Structure-based Deep Learning: A Review
Rocco Meli, Garrett M. Morris, Philip C. Biggin
Frontiers in Bioinformatics (2022) Vol. 2
Open Access | Times Cited: 78
Geometric Interaction Graph Neural Network for Predicting Protein–Ligand Binding Affinities from 3D Structures (GIGN)
Ziduo Yang, Weihe Zhong, Qiujie Lv, et al.
The Journal of Physical Chemistry Letters (2023) Vol. 14, Iss. 8, pp. 2020-2033
Closed Access | Times Cited: 58
AttentionMGT-DTA: A multi-modal drug-target affinity prediction using graph transformer and attention mechanism
Hongjie Wu, Junkai Liu, Tengsheng Jiang, et al.
Neural Networks (2023) Vol. 169, pp. 623-636
Open Access | Times Cited: 57
PLANET: A Multi-objective Graph Neural Network Model for Protein–Ligand Binding Affinity Prediction
Xiangying Zhang, Haotian Gao, Haojie Wang, et al.
Journal of Chemical Information and Modeling (2023) Vol. 64, Iss. 7, pp. 2205-2220
Open Access | Times Cited: 49
CAPLA: improved prediction of protein–ligand binding affinity by a deep learning approach based on a cross-attention mechanism
Zhi Jin, Tingfang Wu, Taoning Chen, et al.
Bioinformatics (2023) Vol. 39, Iss. 2
Open Access | Times Cited: 46
ResGen is a pocket-aware 3D molecular generation model based on parallel multiscale modelling
Odin Zhang, Jintu Zhang, Jieyu Jin, et al.
Nature Machine Intelligence (2023) Vol. 5, Iss. 9, pp. 1020-1030
Closed Access | Times Cited: 44
Machine Learning for Sequence and Structure-Based Protein–Ligand Interaction Prediction
Yunjiang Zhang, Shuyuan Li, Kong Meng, et al.
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 5, pp. 1456-1472
Closed Access | Times Cited: 20
Narrowing the gap between machine learning scoring functions and free energy perturbation using augmented data
ísak Valsson, Matthew T. Warren, Charlotte M. Deane, et al.
Communications Chemistry (2025) Vol. 8, Iss. 1
Open Access | Times Cited: 2
Harnessing pre-trained models for accurate prediction of protein-ligand binding affinity
Jiashan Li, Xinqi Gong
BMC Bioinformatics (2025) Vol. 26, Iss. 1
Open Access | Times Cited: 2
RELATION: A Deep Generative Model for Structure-Based De Novo Drug Design
Mingyang Wang, Chang‐Yu Hsieh, Jike Wang, et al.
Journal of Medicinal Chemistry (2022) Vol. 65, Iss. 13, pp. 9478-9492
Closed Access | Times Cited: 62
Modality-DTA: Multimodality Fusion Strategy for Drug–Target Affinity Prediction
Xixi Yang, Zhangming Niu, Yuansheng Liu, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2022) Vol. 20, Iss. 2, pp. 1200-1210
Closed Access | Times Cited: 45
Organic Compound Synthetic Accessibility Prediction Based on the Graph Attention Mechanism
Jiahui Yu, Jike Wang, Hong Zhao, et al.
Journal of Chemical Information and Modeling (2022) Vol. 62, Iss. 12, pp. 2973-2986
Closed Access | Times Cited: 44
A fully differentiable ligand pose optimization framework guided by deep learning and a traditional scoring function
Zechen Wang, Liangzhen Zheng, Sheng Wang, et al.
Briefings in Bioinformatics (2022) Vol. 24, Iss. 1
Open Access | Times Cited: 39
Geometric deep learning for drug discovery
Mingquan Liu, Chunyan Li, Ruizhe Chen, et al.
Expert Systems with Applications (2023) Vol. 240, pp. 122498-122498
Closed Access | Times Cited: 36
Learning on topological surface and geometric structure for 3D molecular generation
Odin Zhang, Tianyue Wang, Gaoqi Weng, et al.
Nature Computational Science (2023) Vol. 3, Iss. 10, pp. 849-859
Closed Access | Times Cited: 33
Graph Neural Networks for Molecules
Yuyang Wang, Zijie Li, Amir Barati Farimani
Challenges and advances in computational chemistry and physics (2023), pp. 21-66
Closed Access | Times Cited: 29
A Small Step Toward Generalizability: Training a Machine Learning Scoring Function for Structure-Based Virtual Screening
Jack Scantlebury, Lucy Vost, Anna Carbery, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 10, pp. 2960-2974
Open Access | Times Cited: 28
Open-Source Machine Learning in Computational Chemistry
Alexander Hagg, Karl N. Kirschner
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 15, pp. 4505-4532
Open Access | Times Cited: 28
DDI-GCN: Drug-drug interaction prediction via explainable graph convolutional networks
Yi Zhong, Houbing Zheng, Xiaohong Chen, et al.
Artificial Intelligence in Medicine (2023) Vol. 144, pp. 102640-102640
Closed Access | Times Cited: 24
Advancing Ligand Docking through Deep Learning: Challenges and Prospects in Virtual Screening
Xujun Zhang, Chao Shen, Haotian Zhang, et al.
Accounts of Chemical Research (2024) Vol. 57, Iss. 10, pp. 1500-1509
Closed Access | Times Cited: 16
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