Utilization of AlphaFold2 to Predict MFS Protein Conformations after Selective Mutation by Qingjie Xiao, Mengxue Xu, Weiwei Wang, Tingting Wu, Weizhe Zhang, Wenming Qin, Bo Sun

“…The predicted structures for these mutants had small RMSD values when compared to structures obtained using X-ray crystallography, which indicates that AlphaFold2 predicts the structure of MSF transporters with high accuracy. …”
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Unique SMYD5 Structure Revealed by AlphaFold Correlates with Its Functional Divergence by Yingxue Zhang, Eid Alshammari, Jacob Sobota, Alexander Yang, Chunying Li, Zhe Yang

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Automated identification of chalcogen bonds in AlphaFold protein structure database files: is it possible? by Oliviero Carugo, Oliviero Carugo, Kristina Djinović-Carugo, Kristina Djinović-Carugo, Kristina Djinović-Carugo

Subjects: “…AlphaFold…”
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The path to solving the protein folding problem by Jenny Straiton

Subjects: “…AlphaFold…”
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Analysis of Receptor-Type Protein Tyrosine Phosphatase Extracellular Regions with Insights from AlphaFold by Lina El Badaoui, Alastair J. Barr

“…In agreement with experimental data, AlphaFold predicted structures for extracellular regions of R1, and R2B subgroup RPTPs have an extended conformation, whereas R2B RPTPs are twisted, reflecting their high flexibility. …”
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Improving AlphaFold2-based protein tertiary structure prediction with MULTICOM in CASP15 by Jian Liu, Zhiye Guo, Tianqi Wu, Raj S. Roy, Chen Chen, Jianlin Cheng

“…Abstract Since the 14th Critical Assessment of Techniques for Protein Structure Prediction (CASP14), AlphaFold2 has become the standard method for protein tertiary structure prediction. …”
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Author Correction: High-throughput prediction of protein conformational distributions with subsampled AlphaFold2 by Gabriel Monteiro da Silva, Jennifer Y. Cui, David C. Dalgarno, George P. Lisi, Brenda M. Rubenstein

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AlphaFold-multimer predicts ATG8 protein binding motifs crucial for autophagy research. by Hallvard Lauritz Olsvik, Terje Johansen

“…In this issue of PLOS Biology, Ibrahim and colleagues demonstrate how AlphaFold-multimer, an artificial intelligence-based structure prediction tool, can be used to identify sequence motifs binding to the ATG8 family of proteins central to autophagy.…”
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Development of anti-PD-L1 antibody based on structure prediction of AlphaFold2 by Kun Du, Kun Du, He Huang, He Huang

Subjects: “…AlphaFold2…”
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How accurately can one predict drug binding modes using AlphaFold models? by Masha Karelina, Joseph J Noh, Ron O Dror

“…Recently developed machine-learning methods such as AlphaFold 2 (AF2) have dramatically improved protein structure prediction, with reported accuracy approaching that of experimentally determined structures. …”
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Obtaining protein foldability information from computational models of AlphaFold2 and RoseTTAFold by Sen Liu, Kan Wu, Cheng Chen

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AlphaFold Blindness to Topological Barriers Affects Its Ability to Correctly Predict Proteins’ Topology by Pawel Dabrowski-Tumanski, Andrzej Stasiak

Subjects: “…AlphaFold…”
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Enhanced antibody-antigen structure prediction from molecular docking using AlphaFold2 by Francis Gaudreault, Christopher R. Corbeil, Traian Sulea

“…Abstract Predicting the structure of antibody-antigen complexes has tremendous value in biomedical research but unfortunately suffers from a poor performance in real-life applications. AlphaFold2 (AF2) has provided renewed hope for improvements in the field of protein–protein docking but has shown limited success against antibody-antigen complexes due to the lack of co-evolutionary constraints. …”
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Biasing AlphaFold2 to predict GPCRs and kinases with user-defined functional or structural properties by Davide Sala, Peter W. Hildebrand, Jens Meiler, Jens Meiler, Jens Meiler

Subjects: “…AlphaFold…”
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Digging into the 3D Structure Predictions of AlphaFold2 with Low Confidence: Disorder and Beyond by Apolline Bruley, Jean-Paul Mornon, Elodie Duprat, Isabelle Callebaut

“…AlphaFold2 (AF2) has created a breakthrough in biology by providing three-dimensional structure models for whole-proteome sequences, with unprecedented levels of accuracy. …”
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SpatialPPI: Three-dimensional space protein-protein interaction prediction with AlphaFold Multimer by Wenxing Hu, Masahito Ohue

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From interaction networks to interfaces, scanning intrinsically disordered regions using AlphaFold2 by Hélène Bret, Jinmei Gao, Diego Javier Zea, Jessica Andreani, Raphaël Guerois

“…Abstract The revolution brought about by AlphaFold2 opens promising perspectives to unravel the complexity of protein-protein interaction networks. …”
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AlphaFold-multimer predicts ATG8 protein binding motifs crucial for autophagy research by Hallvard Lauritz Olsvik, Terje Johansen

“…In this issue of PLOS Biology, Ibrahim and colleagues demonstrate how AlphaFold-multimer, an artificial intelligence–based structure prediction tool, can be used to identify sequence motifs binding to the ATG8 family of proteins central to autophagy. …”
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Predicting the structure of large protein complexes using AlphaFold and Monte Carlo tree search by Patrick Bryant, Gabriele Pozzati, Wensi Zhu, Aditi Shenoy, Petras Kundrotas, Arne Elofsson

“…The accuracy of AlphaFold decreases with the number of protein chains and the available GPU memory limits the size of protein complexes that can be predicted. …”
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Structural modeling of ion channels using AlphaFold2, RoseTTAFold2, and ESMFold by Phuong Tran Nguyen, Brandon John Harris, Diego Lopez Mateos, Adriana Hernández González, Adam Michael Murray, Vladimir Yarov-Yarovoy

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