Structural model of a bacterial focal adhesion complex by Christian Cambillau, Tâm Mignot

“…In this study, we utilize AlphaFold to generate models based on the known interactions and dynamics of gliding motility proteins. …”
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GTExome: Modeling commonly expressed missense mutations in the human genome. by Jill Hoffman, Henry Tan, Clara Sandoval-Cooper, Kaelyn de Villiers, Scott M Reed

“…The user can assess this information and then select from available experimental or computationally predicted structures of native proteins to create, visualize, and download a model of the mutated protein using Fast and Accurate Side-chain Protein Repacking (FASPR). For AlphaFold modeled proteins, confidence scores for native proteins are provided. …”
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Genetic Algorithm-Enhanced Direct Method in Protein Crystallography by Ruijiang Fu, Wu-Pei Su, Hongxing He

“…This method provides an effective alternative for solving structures that are difficult to predict accurately by AlphaFold3 or challenging to solve by molecular replacement and experimental phasing methods. …”
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Structure simulation-based comparison of active site variations in fungal ornithine decarboxylases by Min Jeong Kim, Jeong Ho Chang

“…While the structures of mammalian and protozoan ODCs have been elucidated, fungal ODCs remain uncharacterized. In this study, AlphaFold2 was employed to simulate the structures of ODCs from four fungi: Kluyveromyces lactis, Candida albicans, Debaryomyces hansenii, and Schizosaccharomyces pombe. …”
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The structural landscape and diversity of Pyricularia oryzae MAX effectors revisited. by Mounia Lahfa, Philippe Barthe, Karine de Guillen, Stella Cesari, Mouna Raji, Thomas Kroj, Marie Le Naour-Vernet, François Hoh, Pierre Gladieux, Christian Roumestand, Jérôme Gracy, Nathalie Declerck, André Padilla

“…Four novel MAX effector structures determined by NMR were in remarkably good agreement with AlphaFold2 (AF2) predictions. Based on the comparison of the AF2-generated 3D models we propose a classification of the MAX effectors superfamily in 20 structural groups that vary in the canonical MAX fold, disulfide bond patterns, and additional secondary structures in N- and C-terminal extensions. …”
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Artificial intelligence driven innovations in biochemistry: A review of emerging research frontiers by Mohammed Abdul Lateef Junaid

“…AI-driven tools like AlphaFold, which have significantly advanced protein structure prediction, are evaluated alongside AI’s role in expediting drug discovery. …”
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Identifying natural inhibitors against FUS protein in dementia through machine learning, molecular docking, and dynamics simulation by Darwin Li

“…We first reviewed the FUS protein's framework; early forecasting models using the AlphaFold2 and SwissModel algorithms indicated a loop-rich protein—a structure component correlating with flexibility. …”
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Assembly of oleosin during efficient extraction: Altering the sequence of defatting solvents by Yu Li, Yuqian Qiao, Yuxuan Zhu, Wangyang Shen, Weiping Jin, Dengfeng Peng, Qingrong Huang

“…The 3D spatial structure of oleosin was predicted using AlphaFold 2, revealing that the secondary structure of oleosin was dominated by α-helices (>60 %). …”
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Mismatch prime editing gRNA increased efficiency and reduced indels by Jidong Fei, Dongdong Zhao, Caiyi Pang, Ju Li, Siwei Li, Wentao Qiao, Juan Tan, Changhao Bi, Xueli Zhang

“…Combining mpegRNA with epegRNA further increases efficiency up to 14-fold, or 2.4-fold in PE4max/PE5max systems, underscoring its potential in research and therapy. AlphaFold 3 analysis suggests that the optimal mpegRNA structure contributes significantly to improved editing outcomes. …”
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EquiRank: Improved protein-protein interface quality estimation using protein language-model-informed equivariant graph neural networks by Md Hossain Shuvo, Debswapna Bhattacharya

“…Our experimental results demonstrate improved ranking performance on diverse datasets over existing latest protein complex quality estimation methods including the top-performing CASP15 protein complex quality estimation method VoroIF_GNN and the self-assessment module of AlphaFold-Multimer repurposed for protein complex scoring and across different performance evaluation metrics. …”
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Mechanisms of RCD-1 pore formation and membrane bending by Keli Ren, James Daniel Farrell, Yueyue Li, Xinrui Guo, Ruipei Xie, Xin Liu, Qiaozhen Kang, Qihui Fan, Fangfu Ye, Jingjin Ding, Fang Jiao

“…Using atomic force microscopy (AFM) and AlphaFold, we show that RCD-1-1 and RCD-1-2 form heterodimers that further self-assemble into ~14.5 nm-wide transmembrane pores (~10 heterodimers). …”
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Structural basis for the interaction between the Drosophila RTK Sevenless (dROS1) and the GPCR BOSS by Jianan Zhang, Yuko Tsutsui, Hengyi Li, Tongqing Li, Yueyue Wang, Salma Laraki, Sofia Alarcon-Frias, Steven E. Stayrook, Daryl E. Klein

“…Our mutagenesis studies, coupled with AlphaFold complex predictions, support a binding interaction mediated by a hydrophobic interaction and beta-strand augmentation between these regions. …”
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Hepatitis B virus genotypes A1 and A2 have distinct replication phenotypes due to polymorphisms in the HBx gene. by Min Zhang, Karim Mouzannar, Zhensheng Zhang, Yuji Teraoka, Jason Piotrowski, Yuji Ishida, Chise Tateno-Mukaidani, Takeshi Saito, Hiromi Abe-Chayama, Kazuaki Chayama, T Jake Liang

“…Mutagenesis studies identified two HBx amino acid variations responsible for the observed phenotypic difference. Using AlphaFold2, we generated structural models of HBx proteins of A1 and A2. …”
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Redesigning error control in cross-linking mass spectrometry enables more robust and sensitive protein-protein interaction studies by Boris Bogdanow, Max Ruwolt, Julia Ruta, Lars Mühlberg, Cong Wang, Wen-feng Zeng, Arne Elofsson, Fan Liu

“…In human cells, inter-link identifications increase by 75% and we confirm their structural accuracy through proteome-wide comparisons to AlphaFold2-derived models. Taken together, target-decoy fusion and context-sensitive data filtering deepen and fine-tune XL-MS-based interactomics.…”
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Contact-dependent growth inhibition (CDI) systems deploy a large family of polymorphic ionophoric toxins for inter-bacterial competition. by Tiffany M Halvorsen, Kaitlin A Schroeder, Allison M Jones, Disa Hammarlöf, David A Low, Sanna Koskiniemi, Christopher S Hayes

“…These CdiA-CT toxins are composed of two distinct domains based on AlphaFold2 modeling. The C-terminal ionophore domains are all predicted to form five-helix bundles capable of spanning the cell membrane. …”
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Innovative CDR grafting and computational methods for PD-1 specific nanobody design by Jagadeeswara Reddy Devasani, Girijasankar Guntuku, Nalini Panatula, Murali Krishna Kumar Muthyala, Mary Sulakshana Palla, Teruna J. Siahaan

“…The three-dimensional structure of the nanobody was predicted using AlphaFold2, and molecular docking simulations via ClusPro were conducted to evaluate binding interactions with PD-1. …”
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NHSL3 controls single and collective cell migration through two distinct mechanisms by Nikita M. Novikov, Jinmei Gao, Artem I. Fokin, Nathalie Rocques, Giovanni Chiappetta, Karina D. Rysenkova, Diego Javier Zea, Anna Polesskaya, Joelle Vinh, Raphael Guerois, Alexis M. Gautreau

“…We identify the partner repertoire of each isoform using proteomics and predict direct partners and their binding sites using an AlphaFold2-based pipeline. Rescue with specific isoforms, and lack of rescue when relevant binding sites are mutated, establish that the interaction of a long isoform with MENA/VASP proteins is critical at cell-cell junctions for collective migration, while the interaction of a short one with 14-3-3θ in lamellipodia is critical for single cell migration. …”
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C. perfringens enterotoxin-claudin pore complex: Models for structure, mechanism of pore assembly and cation permeability by Santhosh Kumar Nagarajan, Joy Weber, Daniel Roderer, Jörg Piontek

“…While the mechanism of CPE-claudin interaction is well understood, the structure and assembly of the pore complex remain elusive. Here, we used AlphaFold2 complex prediction, structure alignment, and molecular dynamics simulations to generate models of prepore and pore states of the CPE/claudin-4 complex. …”
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In silico characterisation of the avocado WAK/WAKL gene family with a focus on genes involved in defence against Phytophthora cinnamomi by Aaron Harvey, Aaron Harvey, Noëlani van den Berg, Noëlani van den Berg, Velushka Swart, Velushka Swart

“…The predicted proteins from these genes were modelled with AlphaFold2, and structural similarity across different rootstocks, as well as their binding affinity for oligogalacturonides, were assessed. …”
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Discovery and Characterization of Two Selective Inhibitors for a Mu-Class Glutathione S-Transferase of 25 kDa from <i>Taenia solium</i> Using Computational and Bioinformatics Tools by César Sánchez-Juárez, Roberto Flores-López, Lluvia de Carolina Sánchez-Pérez, Ponciano García-Gutiérrez, Lucía Jiménez, Abraham Landa, Rafael A. Zubillaga

“…The workflow involved modeling and refining the 3D structure from the sequence using the AlphaFold algorithm and all-atom molecular dynamics simulations with an explicit solvent. …”
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