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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:

SPEACH_AF: Sampling protein ensembles and conformational heterogeneity with Alphafold2
Richard A. Stein, Hassane S. Mchaourab
PLoS Computational Biology (2022) Vol. 18, Iss. 8, pp. e1010483-e1010483
Open Access | Times Cited: 155

Showing 1-25 of 155 citing articles:

From nature to industry: Harnessing enzymes for biocatalysis
Rebecca Buller, Stefan Lutz, Romas J. Kazlauskas, et al.
Science (2023) Vol. 382, Iss. 6673
Open Access | Times Cited: 203
AlphaFold predictions are valuable hypotheses and accelerate but do not replace experimental structure determination
Thomas C. Terwilliger, Dorothée Liebschner, Tristan I. Croll, et al.
Nature Methods (2023) Vol. 21, Iss. 1, pp. 110-116
Open Access | Times Cited: 150
Modeling conformational states of proteins with AlphaFold
Davide Sala, Felipe Engelberger, Hassane S. Mchaourab, et al.
Current Opinion in Structural Biology (2023) Vol. 81, pp. 102645-102645
Open Access | Times Cited: 108
Improved AlphaFold modeling with implicit experimental information
Thomas C. Terwilliger, Billy K. Poon, Pavel V. Afonine, et al.
Nature Methods (2022) Vol. 19, Iss. 11, pp. 1376-1382
Open Access | Times Cited: 97
High-throughput prediction of protein conformational distributions with subsampled AlphaFold2
Gabriel Monteiro da Silva, Jennifer Y. Cui, David C. Dalgarno, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 73
Accelerating Cryptic Pocket Discovery Using AlphaFold
Artur Meller, Soumendranath Bhakat, Shahlo Solieva, et al.
Journal of Chemical Theory and Computation (2023) Vol. 19, Iss. 14, pp. 4355-4363
Open Access | Times Cited: 64
Biasing AlphaFold2 to predict GPCRs and kinases with user-defined functional or structural properties
Davide Sala, Peter W. Hildebrand, Jens Meiler
Frontiers in Molecular Biosciences (2023) Vol. 10
Open Access | Times Cited: 56
AlphaFold, allosteric, and orthosteric drug discovery: Ways forward
Ruth Nussinov, Mingzhen Zhang, Yonglan Liu, et al.
Drug Discovery Today (2023) Vol. 28, Iss. 6, pp. 103551-103551
Open Access | Times Cited: 53
From interaction networks to interfaces, scanning intrinsically disordered regions using AlphaFold2
Hélène Bret, Jinmei Gao, Diego Javier Zea, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 45
AlphaFold predictions of fold-switched conformations are driven by structure memorization
Devlina Chakravarty, Joseph W. Schafer, Ethan A. Chen, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 25
Approximating Projections of Conformational Boltzmann Distributions with AlphaFold2 Predictions: Opportunities and Limitations
Benjamin P. Brown, Richard A. Stein, Jens Meiler, et al.
Journal of Chemical Theory and Computation (2024) Vol. 20, Iss. 3, pp. 1434-1447
Open Access | Times Cited: 18
Computational drug development for membrane protein targets
Haijian Li, Xiaolin Sun, Wenqiang Cui, et al.
Nature Biotechnology (2024) Vol. 42, Iss. 2, pp. 229-242
Closed Access | Times Cited: 16
Proteins with alternative folds reveal blind spots in AlphaFold-based protein structure prediction
Devlina Chakravarty, Myeongsang Lee, Lauren L. Porter
Current Opinion in Structural Biology (2025) Vol. 90, pp. 102973-102973
Open Access | Times Cited: 7
AlphaFold prediction of structural ensembles of disordered proteins
Z. Faidon Brotzakis, Shengyu Zhang, Mhd Hussein Murtada, et al.
Nature Communications (2025) Vol. 16, Iss. 1
Open Access | Times Cited: 2
AlphaFold2 and Deep Learning for Elucidating Enzyme Conformational Flexibility and Its Application for Design
Guillem Casadevall, Cristina Duran, Sílvia Osuna
JACS Au (2023) Vol. 3, Iss. 6, pp. 1554-1562
Open Access | Times Cited: 32
Evolutionary selection of proteins with two folds
Joseph W. Schafer, Lauren L. Porter
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 30
PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins
Hamidreza Ghafouri, Tamás Lázár, Alessio Del Conte, et al.
Nucleic Acids Research (2023) Vol. 52, Iss. D1, pp. D536-D544
Open Access | Times Cited: 28
Exploring and Learning the Universe of Protein Allostery Using Artificial Intelligence Augmented Biophysical and Computational Approaches
Steve Agajanian, Mohammed Alshahrani, Fang Bai, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 5, pp. 1413-1428
Closed Access | Times Cited: 23
Recent Advances in NMR Protein Structure Prediction with ROSETTA
Julia Koehler Leman, Georg Künze
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 9, pp. 7835-7835
Open Access | Times Cited: 23
Generative artificial intelligence for de novo protein design
Adam Winnifrith, Carlos Outeiral, Brian Hie
Current Opinion in Structural Biology (2024) Vol. 86, pp. 102794-102794
Open Access | Times Cited: 14
AFsample2: Predicting multiple conformations and ensembles with AlphaFold2
Yogesh Kalakoti, Björn Wallner
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 14
Deep learning for protein structure prediction and design—progress and applications
Jürgen Jänes, Pedro Beltrão
Molecular Systems Biology (2024) Vol. 20, Iss. 3, pp. 162-169
Open Access | Times Cited: 13
AlphaFold2 Modeling and Molecular Dynamics Simulations of the Conformational Ensembles for the SARS-CoV-2 Spike Omicron JN.1, KP.2 and KP.3 Variants: Mutational Profiling of Binding Energetics Reveals Epistatic Drivers of the ACE2 Affinity and Escape Hotspots of Antibody Resistance
Nishank Raisinghani, Mohammed Alshahrani, Grace Gupta, et al.
Viruses (2024) Vol. 16, Iss. 9, pp. 1458-1458
Open Access | Times Cited: 11
Machine learning in RNA structure prediction: Advances and challenges
Sicheng Zhang, Jun Li, Shi‐Jie Chen
Biophysical Journal (2024) Vol. 123, Iss. 17, pp. 2647-2657
Closed Access | Times Cited: 9
NMR tools to detect protein allostery
Olivia Gampp, Harindranath Kadavath, Roland Riek
Current Opinion in Structural Biology (2024) Vol. 86, pp. 102792-102792
Open Access | Times Cited: 9
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