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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:

Structure prediction of protein-ligand complexes from sequence information with Umol
Patrick Bryant, Atharva Kelkar, Andrea Guljas, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 26

Showing 1-25 of 26 citing articles:

DynamicBind: predicting ligand-specific protein-ligand complex structure with a deep equivariant generative model
Wei Lu, Jixian Zhang, Weifeng Huang, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 46
Artificial intelligence in drug development
Kang Zhang, Xin Yang, Yifei Wang, et al.
Nature Medicine (2025) Vol. 31, Iss. 1, pp. 45-59
Closed Access | Times Cited: 11
Structure-based virtual screening of vast chemical space as a starting point for drug discovery
Jens Carlsson, Andreas Luttens
Current Opinion in Structural Biology (2024) Vol. 87, pp. 102829-102829
Open Access | Times Cited: 14
Integrated structure prediction of protein–protein docking with experimental restraints using ColabDock
Shi-Hao Feng, Zhen‐Yu Chen, Chengwei Zhang, et al.
Nature Machine Intelligence (2024) Vol. 6, Iss. 8, pp. 924-935
Closed Access | Times Cited: 8
Protenix - Advancing Structure Prediction Through a Comprehensive AlphaFold3 Reproduction
Xuan-Long Chen, Yuxuan Zhang, Changli Lü, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2025)
Open Access | Times Cited: 1
AlphaFold2 enables accurate deorphanization of ligands to single-pass receptors
Niels Banhos Danneskiold‐Samsøe, Deniz Kavi, Kevin M. Jude, et al.
Cell Systems (2024) Vol. 15, Iss. 11, pp. 1046-1060.e3
Closed Access | Times Cited: 6
Structure-Based Drug Design with a Deep Hierarchical Generative Model
Jesse A. Weller, Remo Rohs
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 16, pp. 6450-6463
Open Access | Times Cited: 5
Real-World Applications and Experiences of AI/ML Deployment for Drug Discovery
William R. Pitt, Jonathan Bentley, Christophe Boldron, et al.
Journal of Medicinal Chemistry (2025)
Closed Access
Improving the Reliability of Language Model-Predicted Structures as Docking Targets through Geometric Graph Learning
Chao Shen, Xiaoqi Han, Heng Cai, et al.
Journal of Medicinal Chemistry (2025)
Closed Access
Ligand-Conditioned Side Chain Packing for Flexible Molecular Docking
Ding Luo, Xiaoyang Qu, Dexin Lu, et al.
Journal of Chemical Theory and Computation (2025)
Closed Access
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
Benchmarking HelixFold3-Predicted Holo Structures for Relative Free Energy Perturbation Calculations
Kairi Furui, Masahito Ohue
ACS Omega (2025)
Open Access
Computational tools in genomics and proteomics
Sharav Desai, Vipul Patel, Kunal Bhosle, et al.
Elsevier eBooks (2025), pp. 489-518
Closed Access
MolEM: a unified generative framework for molecular graphs and sequential orders
Hanwen Zhang, Xiong Deng, Xianggen Liu, et al.
Briefings in Bioinformatics (2025) Vol. 26, Iss. 2
Open Access
Physics-Inspired Accuracy Estimator for Model-Docked Ligand Complexes
Byeong‐Soo Bae, Jin Sun Choi, Chaok Seok, et al.
Journal of Chemical Theory and Computation (2025)
Open Access
GalaxyDock-DL: Protein–Ligand Docking by Global Optimization and Neural Network Energy
Changsoo Lee, Jonghun Won, Seongok Ryu, et al.
Journal of Chemical Theory and Computation (2024)
Closed Access | Times Cited: 3
Deep learning methods for protein structure prediction
Yiming Qin, Zihan Chen, Peng Ye, et al.
MedComm – Future Medicine (2024) Vol. 3, Iss. 3
Open Access | Times Cited: 3
An outlook on structural biology after AlphaFold: tools, limits and perspectives
Serena Rosignoli, M Pacelli, Francesca Manganiello, et al.
FEBS Open Bio (2024) Vol. 15, Iss. 2, pp. 202-222
Open Access | Times Cited: 2
SurfDock is a surface-informed diffusion generative model for reliable and accurate protein–ligand complex prediction
Duanhua Cao, Mingan Chen, Runze Zhang, et al.
Nature Methods (2024)
Closed Access | Times Cited: 2
Modeling all-type biomolecular structures with deep learning approaches
Han Li, Yipin Lei, Jianyang Zeng
National Science Review (2024) Vol. 11, Iss. 11
Open Access | Times Cited: 1
Beyond boundaries: exploring the transformative power of AI in pharmaceuticals
Gurparsad Singh Suri, Gurleen Kaur, Dheeraj Shinde
Discover Artificial Intelligence (2024) Vol. 4, Iss. 1
Open Access | Times Cited: 1
Do Deep Learning Models for Co-Folding Learn the Physics of Protein-Ligand Interactions?
Matthew R. Masters, Amr H. Mahmoud, Markus A. Lill
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Predicting the alternative conformation of a known protein structure based on the distance map of AlphaFold2
Jiaxuan Li, Zefeng Zhu, Chen Song
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Mapping kinase domain resistance mechanisms for the MET receptor tyrosine kinase via deep mutational scanning
Gabriella O. Estevam, Edmond M. Linossi, J. N. K. Rao, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
QuickBind: A Light-Weight And Interpretable Molecular Docking Model.
Wojtek Treyde, Nazim Bouatta, S Kim, et al.
arXiv (Cornell University) (2024)
Open Access
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