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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:

A brief review of protein–ligand interaction prediction
Lingling Zhao, Yan Zhu, Junjie Wang, et al.
Computational and Structural Biotechnology Journal (2022) Vol. 20, pp. 2831-2838
Open Access | Times Cited: 34

Showing 1-25 of 34 citing articles:

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: 19
Application of Mathematical Modeling and Computational Tools in the Modern Drug Design and Development Process
Md. Rifat Hasan, Ahad Amer Alsaiari, Burhan Zain Fakhurji, et al.
Molecules (2022) Vol. 27, Iss. 13, pp. 4169-4169
Open Access | Times Cited: 55
APBIO: bioactive profiling of air pollutants through inferred bioactivity signatures and prediction of novel target interactions
Eva Viesi, Ugo Perricone, Patrick Aloy, et al.
Journal of Cheminformatics (2025) Vol. 17, Iss. 1
Open Access | Times Cited: 1
Exploring Spirocyclic Isoquinoline-Piperidine Compounds in Tuberculosis Therapy: ADMET Profiling, Docking, DFT, MD Simulations, and MMGBSA Analysis
Sri Mounika Bellapukonda, Siva Singothu, Anuradha Singampalli, et al.
Computational Biology and Chemistry (2025) Vol. 118, pp. 108447-108447
Closed Access
Unveiling the Full Dynamical and Reactivity Profiles of Acetylcholinesterase: A Comprehensive All-Atom Investigation
Frédéric Célerse, Louis Lagardère, Yasmine Bouchibti, et al.
ACS Catalysis (2024) Vol. 14, Iss. 3, pp. 1785-1796
Closed Access | Times Cited: 4
Application of machine learning on understanding biomolecule interactions in cellular machinery
Rewati Dixit, Khushal Khambhati, Kolli Venkata Supraja, et al.
Bioresource Technology (2022) Vol. 370, pp. 128522-128522
Closed Access | Times Cited: 16
From Proteins to Ligands: Decoding Deep Learning Methods for Binding Affinity Prediction
Rohan Gorantla, Alžbeta Kubincová, Andrea Y. Weiße, et al.
Journal of Chemical Information and Modeling (2023) Vol. 64, Iss. 7, pp. 2496-2507
Open Access | Times Cited: 9
Toward generalizable structure‐based deep learning models for protein–ligand interaction prediction: Challenges and strategies
Seokhyun Moon, Wonho Zhung, Woo Youn Kim
Wiley Interdisciplinary Reviews Computational Molecular Science (2024) Vol. 14, Iss. 1
Closed Access | Times Cited: 3
Interplay of PROTAC Complex Dynamics for Undruggable Targets: Insights into Ternary Complex Behavior and Linker Design
Harish Kumar, M. Elizabeth Sobhia
ACS Medicinal Chemistry Letters (2024) Vol. 15, Iss. 8, pp. 1306-1318
Closed Access | Times Cited: 3
VAERHNN: Voting-averaged ensemble regression and hybrid neural network to investigate potent leads against colorectal cancer
Guanxing Chen, Xuefei Jiang, Qiujie Lv, et al.
Knowledge-Based Systems (2022) Vol. 257, pp. 109925-109925
Closed Access | Times Cited: 12
Self- and cross-attention accurately predicts metabolite–protein interactions
Pedro Alonso Campana, Zoran Nikoloski
NAR Genomics and Bioinformatics (2023) Vol. 5, Iss. 1
Open Access | Times Cited: 6
From Proteins to Ligands: Decoding Deep Learning Methods for Binding Affinity Prediction
Rohan Gorantla, Alžbeta Kubincová, Andrea Y. Weiße, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 5
TeachOpenCADD goes Deep Learning: Open-source Teaching Platform Exploring Molecular DL Applications
Michael Backenköhler, Paula Linh Kramer, Joschka Groß, et al.
(2023)
Open Access | Times Cited: 4
Understanding the Role of Activation Loop Mutants in Drug Efficacy for FLT3-ITD
Julhash U. Kazi, Lina Al Ashiri, Rituraj Purohit, et al.
Cancers (2023) Vol. 15, Iss. 22, pp. 5426-5426
Open Access | Times Cited: 4
The effect of chrysin binding on the conformational dynamics and unfolding pathway of human serum albumin
Ishita Bisaria, Chanchal Chauhan, Shivani A. Muthu, et al.
Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy (2024) Vol. 316, pp. 124332-124332
Closed Access | Times Cited: 1
Unveiling Fluorescence Spectroscopy, Molecular Docking and Dynamic Simulations: Interactions Between Protein and 2, 4-Dinitrophenylhydrazine Schiff Base
Tapan K. Rana, Patitapaban Mohanty, Pragyan P. Dash, et al.
Journal of Fluorescence (2024)
Closed Access | Times Cited: 1
ResBiGAAT: Residual Bi-GRU with attention for protein-ligand binding affinity prediction
Gelany Aly Abdelkader, Soualihou Ngnamsie Njimbouom, Tae‐Jin Oh, et al.
Computational Biology and Chemistry (2023) Vol. 107, pp. 107969-107969
Open Access | Times Cited: 3
Intelligent Protein Design and Molecular Characterization Techniques: A Comprehensive Review
Jingjing Wang, Chang Chen, Ge Yao, et al.
Molecules (2023) Vol. 28, Iss. 23, pp. 7865-7865
Open Access | Times Cited: 3
Prediction of metabolite–protein interactions based on integration of machine learning and constraint-based modeling
Fayaz Soleymani Babadi, Zahra Razaghi‐Moghadam, Fatemeh Zare‐Mirakabad, et al.
Bioinformatics Advances (2023) Vol. 3, Iss. 1
Open Access | Times Cited: 3
Quality Matters: Deep Learning-Based Analysis of Protein-Ligand Interactions with Focus on Avoiding Bias
Manuel Sellner, Markus A. Lill, Martin Smieško
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 2

Yurchenko Da, Markova Zhg, Minzhenkova Me, et al.
Вестник Российского государственного медицинского университета (2024), Iss. 2024(1)
Open Access
Exploring AI-Driven Drug Repurposing Strategies Targeting ErbB Signalling Pathway for Brain Cancer Therapy
Chi Kit Ng, Jianqiao Long, Muran Tang, et al.
(2024) Vol. 1, pp. 555-560
Closed Access
Predicting Drug–Protein Interactions through Branch-Chain Mining and multi-dimensional attention network
Zhuo Huang, Qiu Xiao, Tuo Xiong, et al.
Computers in Biology and Medicine (2024) Vol. 171, pp. 108127-108127
Closed Access
Glubokoe obuchenie v modelirovanii belok-ligandnogo vzaimodejstviya: novye puti v razrabotke lekarstvennyh preparatov
А. Д. Барыкин, Т. В. Чепурных, З. М. Осипова
Вестник Российского государственного медицинского университета (2024), Iss. 2024(1)
Open Access
Deep learning in modelling the protein–ligand interaction: new pathways in drug development
AD Barykin, TV Chepurnykh, ZM Osipova
Bulletin of Russian State Medical University (2024), Iss. 2024(1)
Open Access
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