AlphaFold and the future of structural biology by Randy J. Read, Edward N. Baker, Charles S. Bond, Elspeth F. Garman, Mark J. van Raaij

“…This editorial acknowledges the transformative impact of new machine-learning methods, such as the use of AlphaFold, but also makes the case for the continuing need for experimental structural biology.…”
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AlphaFold2 Update and Perspectives by Sébastien Tourlet, Ragousandirane Radjasandirane, Julien Diharce, Alexandre G. de Brevern

“…In this context, the Protein Structure Prediction method AlphaFold2 represented a revolutionary advance in structural bioinformatics. …”
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Using AlphaFold Predictions in Viral Research by Daria Gutnik, Peter Evseev, Konstantin Miroshnikov, Mikhail Shneider

Subjects: “…AlphaFold review…”
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AlphaFold2 and its applications in the fields of biology and medicine by Zhenyu Yang, Xiaoxi Zeng, Yi Zhao, Runsheng Chen

“…Abstract AlphaFold2 (AF2) is an artificial intelligence (AI) system developed by DeepMind that can predict three-dimensional (3D) structures of proteins from amino acid sequences with atomic-level accuracy. …”
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Inferring molecular inhibition potency with AlphaFold predicted structures by Pedro F. Oliveira, Rita C. Guedes, Andre O. Falcao

“…To address this challenge, we propose an approach that integrates structural data from AlphaFold 2 predicted protein structures into machine learning models. …”
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Pyrethroids in an AlphaFold2 Model of the Insect Sodium Channel by Boris S. Zhorov, Ke Dong

“…Recent advances in protein structure prediction using the AlphaFold2 (AF2) neural network allowed us to generate a new model of the mosquito sodium channel AaNav1-1, with the activated voltage-sensing domains (VSMs) and the presumably inactivated pore domain (PM). …”
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Benchmarking the Accuracy of AlphaFold 2 in Loop Structure Prediction by Amy O. Stevens, Yi He

Subjects: “…AlphaFold 2…”
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Structure prediction of novel isoforms from uveal melanoma by AlphaFold by Zhe Zhang, Chen Li, Qian Li, Xiaoming Su, Jiayi Li, Lili Zhu, Xinhua (James) Lin, Jianfeng Shen

“…However, with the release of AlphaFold, which predicts three-dimensional models of proteins, this challenge is rapidly being overcome. …”
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Before and after AlphaFold2: An overview of protein structure prediction by Letícia M. F. Bertoline, Angélica N. Lima, Jose E. Krieger, Samantha K. Teixeira

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Solubility-Aware Protein Binding Peptide Design Using AlphaFold by Takatsugu Kosugi, Masahito Ohue

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Family-wide analysis of integrin structures predicted by AlphaFold2 by Heng Zhang, Daniel S. Zhu, Jieqing Zhu

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A strategy for Cas13 miniaturization based on the structure and AlphaFold by Feiyu Zhao, Tao Zhang, Xiaodi Sun, Xiyun Zhang, Letong Chen, Hejun Wang, Jinze Li, Peng Fan, Liangxue Lai, Tingting Sui, Zhanjun Li

“…In summary, these findings highlight a feasible strategy for generating downsized CRISPR/Cas13 systems based on structure predicted by AlphaFold2, enabling targeted degradation of RNAs and RNA editing for basic research and therapeutic applications.…”
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How good are AlphaFold models for docking-based virtual screening? by Valeria Scardino, Juan I. Di Filippo, Claudio N. Cavasotto

“…Whenever experimental structures were not available, homology modeling has been, so far, the method of choice. Recently, AlphaFold (AF), an artificial-intelligence-based protein structure prediction method, has shown impressive results in terms of model accuracy. …”
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Evaluation of Myocilin Variant Protein Structures Modeled by AlphaFold2 by Tsz Kin Ng, Jie Ji, Qingping Liu, Yao Yao, Wen-Ying Wang, Yingjie Cao, Chong-Bo Chen, Jian-Wei Lin, Geng Dong, Ling-Ping Cen, Chukai Huang, Mingzhi Zhang

Subjects: “…AlphaFold2…”
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Benchmarking AlphaFold‐enabled molecular docking predictions for antibiotic discovery by Felix Wong, Aarti Krishnan, Erica J Zheng, Hannes Stärk, Abigail L Manson, Ashlee M Earl, Tommi Jaakkola, James J Collins

Subjects: “…AlphaFold2…”
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AlphaFold Protein Structure Database for Sequence-Independent Molecular Replacement by Lawrence Chai, Ping Zhu, Jin Chai, Changxu Pang, Babak Andi, Sean McSweeney, John Shanklin, Qun Liu

Subjects: “…AlphaFold…”
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AlphaFold2: A Role for Disordered Protein/Region Prediction? by Carter J. Wilson, Wing-Yiu Choy, Mikko Karttunen

Subjects: “…AlphaFold2…”
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The Epigenetic Dimension of Protein Structure Is an Intrinsic Weakness of the AlphaFold Program by Fodil Azzaz, Nouara Yahi, Henri Chahinian, Jacques Fantini

“…We found that Robetta was generally more accurate than AlphaFold for ascribing a membrane-compatible topology. …”
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Benchmarking AlphaFold ‐enabled molecular docking predictions for antibiotic discovery by Wong, Felix, Krishnan, Aarti, Zheng, Erica J, Stärk, Hannes, Manson, Abigail L, Earl, Ashlee M, Jaakkola, Tommi, Collins, James J

“…Computational docking approaches have been widely used to predict drug binding targets; yet, such approaches depend on existing protein structures, and accurate structural predictions have only recently become available from AlphaFold2. Here, we combine AlphaFold2 with molecular docking simulations to predict protein-ligand interactions between 296 proteins spanning Escherichia coli's essential proteome, and 218 active antibacterial compounds and 100 inactive compounds, respectively, pointing to widespread compound and protein promiscuity. …”
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Topological links in predicted protein complex structures reveal limitations of AlphaFold by Yingnan Hou, Tengyu Xie, Liuqing He, Liang Tao, Jing Huang

“…Abstract AlphaFold is making great progress in protein structure prediction, not only for single-chain proteins but also for multi-chain protein complexes. …”
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