Artículos de revistas sobre el tema "AlphaFold2"
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Wheeler, Richard John. "A resource for improved predictions of Trypanosoma and Leishmania protein three-dimensional structure". PLOS ONE 16, n.º 11 (11 de noviembre de 2021): e0259871. http://dx.doi.org/10.1371/journal.pone.0259871.
Texto completoStein, Richard A. y Hassane S. Mchaourab. "SPEACH_AF: Sampling protein ensembles and conformational heterogeneity with Alphafold2". PLOS Computational Biology 18, n.º 8 (22 de agosto de 2022): e1010483. http://dx.doi.org/10.1371/journal.pcbi.1010483.
Texto completoGordon, Catriona H., Emily Hendrix, Yi He y Mark C. Walker. "AlphaFold Accurately Predicts the Structure of Ribosomally Synthesized and Post-Translationally Modified Peptide Biosynthetic Enzymes". Biomolecules 13, n.º 8 (12 de agosto de 2023): 1243. http://dx.doi.org/10.3390/biom13081243.
Texto completoNunes-Alves, Ariane y Kenneth Merz. "AlphaFold2 in Molecular Discovery". Journal of Chemical Information and Modeling 63, n.º 19 (9 de octubre de 2023): 5947–49. http://dx.doi.org/10.1021/acs.jcim.3c01459.
Texto completoTourlet, Sébastien, Ragousandirane Radjasandirane, Julien Diharce y Alexandre G. de Brevern. "AlphaFold2 Update and Perspectives". BioMedInformatics 3, n.º 2 (9 de mayo de 2023): 378–90. http://dx.doi.org/10.3390/biomedinformatics3020025.
Texto completoBollinger, Terry. "Why AlphaFold is Not Like AlphaGo". Terry's Archive Online 2021, n.º 02 (12 de abril de 2021): 0206. http://dx.doi.org/10.48034/20210206.
Texto completoNg, Tsz Kin, Jie Ji, Qingping Liu, Yao Yao, Wen-Ying Wang, Yingjie Cao, Chong-Bo Chen et al. "Evaluation of Myocilin Variant Protein Structures Modeled by AlphaFold2". Biomolecules 14, n.º 1 (21 de diciembre de 2023): 14. http://dx.doi.org/10.3390/biom14010014.
Texto completoWilson, Carter J., Wing-Yiu Choy y Mikko Karttunen. "AlphaFold2: A Role for Disordered Protein/Region Prediction?" International Journal of Molecular Sciences 23, n.º 9 (21 de abril de 2022): 4591. http://dx.doi.org/10.3390/ijms23094591.
Texto completo伏信, 進矢. "【用語解説】AlphaFold2". Bulletin of Applied Glycoscience 13, n.º 2 (20 de agosto de 2023): 136. http://dx.doi.org/10.5458/bag.13.2_136.
Texto completoBoland, Devon J. y Nicola M. Ayres. "Cracking AlphaFold2: Leveraging the power of artificial intelligence in undergraduate biochemistry curriculums". PLOS Computational Biology 20, n.º 6 (27 de junio de 2024): e1012123. http://dx.doi.org/10.1371/journal.pcbi.1012123.
Texto completoYang, Zhuoya. "AlphaFold2-based structure prediction and target study of PD-L1 protein". Theoretical and Natural Science 3, n.º 1 (28 de abril de 2023): 1–10. http://dx.doi.org/10.54254/2753-8818/3/20220152.
Texto completoTikhonov, Denis B. y Boris S. Zhorov. "P-Loop Channels: Experimental Structures, and Physics-Based and Neural Networks-Based Models". Membranes 12, n.º 2 (16 de febrero de 2022): 229. http://dx.doi.org/10.3390/membranes12020229.
Texto completoSawhney, Aman, Jiefu Li y Li Liao. "Improving AlphaFold Predicted Contacts for Alpha-Helical Transmembrane Proteins Using Structural Features". International Journal of Molecular Sciences 25, n.º 10 (11 de mayo de 2024): 5247. http://dx.doi.org/10.3390/ijms25105247.
Texto completoFiorini, Giovana, Luana Luiza Bastos y Rafael Pereira Lemos. "ColabFold: uma ferramenta web para modelagem de proteínas". BIOINFO 3, n.º 1 (21 de septiembre de 2023): 22. http://dx.doi.org/10.51780/bioinfo-03-22.
Texto completoQiu, Xinru, Han Li, Greg Ver Steeg y Adam Godzik. "Advances in AI for Protein Structure Prediction: Implications for Cancer Drug Discovery and Development". Biomolecules 14, n.º 3 (12 de marzo de 2024): 339. http://dx.doi.org/10.3390/biom14030339.
Texto completoFinkelstein, Alexei V. "Protein 3D Structure Identification by AlphaFold: a Physics-Based Prediction or Recognition Using Huge Databases?" Journal of Molecular Biology 6, n.º 1 (20 de marzo de 2024): 1–10. http://dx.doi.org/10.52338/tjomb.2024.3935.
Texto completoHartley, Sophia M., Kelly A. Tiernan, Gjina Ahmetaj, Adriana Cretu, Yan Zhuang y Marc Zimmer. "AlphaFold2 and RoseTTAFold predict posttranslational modifications. Chromophore formation in GFP-like proteins". PLOS ONE 17, n.º 6 (16 de junio de 2022): e0267560. http://dx.doi.org/10.1371/journal.pone.0267560.
Texto completoCramer, Patrick. "AlphaFold2 and the future of structural biology". Nature Structural & Molecular Biology 28, n.º 9 (10 de agosto de 2021): 704–5. http://dx.doi.org/10.1038/s41594-021-00650-1.
Texto completoJones, David T. y Janet M. Thornton. "The impact of AlphaFold2 one year on". Nature Methods 19, n.º 1 (enero de 2022): 15–20. http://dx.doi.org/10.1038/s41592-021-01365-3.
Texto completoKosugi, Takatsugu y Masahito Ohue. "Design of Cyclic Peptides Targeting Protein–Protein Interactions Using AlphaFold". International Journal of Molecular Sciences 24, n.º 17 (26 de agosto de 2023): 13257. http://dx.doi.org/10.3390/ijms241713257.
Texto completoWuyun, Qiqige, Yihan Chen, Yifeng Shen, Yang Cao, Gang Hu, Wei Cui, Jianzhao Gao y Wei Zheng. "Recent Progress of Protein Tertiary Structure Prediction". Molecules 29, n.º 4 (13 de febrero de 2024): 832. http://dx.doi.org/10.3390/molecules29040832.
Texto completoAubel, Margaux, Lars Eicholt y Erich Bornberg-Bauer. "Assessing structure and disorder prediction tools for de novo emerged proteins in the age of machine learning". F1000Research 12 (29 de marzo de 2023): 347. http://dx.doi.org/10.12688/f1000research.130443.1.
Texto completoDominguez, Matthew J., Jon J. McCord y R. Bryan Sutton. "Redefining the architecture of ferlin proteins: Insights into multi-domain protein structure and function". PLOS ONE 17, n.º 7 (28 de julio de 2022): e0270188. http://dx.doi.org/10.1371/journal.pone.0270188.
Texto completoOsman, Sara. "Space exploration: finding new protein conformations using AlphaFold2". Nature Structural & Molecular Biology 30, n.º 12 (diciembre de 2023): 1835. http://dx.doi.org/10.1038/s41594-023-01186-2.
Texto completoBorkakoti, Neera y Janet M. Thornton. "AlphaFold2 protein structure prediction: Implications for drug discovery". Current Opinion in Structural Biology 78 (febrero de 2023): 102526. http://dx.doi.org/10.1016/j.sbi.2022.102526.
Texto completoMarchal, Iris. "OpenFold provides insights into AlphaFold2’s learning behavior". Nature Biotechnology 42, n.º 6 (junio de 2024): 847. http://dx.doi.org/10.1038/s41587-024-02290-4.
Texto completoYang, Yacong, Yu Hu, Fengli Yao, Jinbo Yang, Leilei Ge, Peng Wang y Ximing Xu. "Virtual screening and activity evaluation of human uric acid transporter 1 (hURAT1) inhibitors". RSC Advances 13, n.º 6 (2023): 3474–86. http://dx.doi.org/10.1039/d2ra07193b.
Texto completoPaiardini, Alessandro. "Protein Structure Prediction in Drug Discovery". Biomolecules 13, n.º 8 (17 de agosto de 2023): 1258. http://dx.doi.org/10.3390/biom13081258.
Texto completoArantes, Pablo R., Lukasz Nierzwicki, Helen Belato, Alexandra M. D'Ordine, Gerwald Jogl, George Lisi y Giulia Palermo. "Assessing structure and dynamics of AlphaFold2 prediction of GeoCas9". Biophysical Journal 121, n.º 3 (febrero de 2022): 45a. http://dx.doi.org/10.1016/j.bpj.2021.11.2474.
Texto completoZhang, Heng, Daniel S. Zhu y Jieqing Zhu. "Family-wide analysis of integrin structures predicted by AlphaFold2". Computational and Structural Biotechnology Journal 21 (2023): 4497–507. http://dx.doi.org/10.1016/j.csbj.2023.09.022.
Texto completoWang, Lei, Zehua Wen, Shi-Wei Liu, Lihong Zhang, Cierra Finley, Ho-Jin Lee y Hua-Jun Shawn Fan. "Overview of AlphaFold2 and breakthroughs in overcoming its limitations". Computers in Biology and Medicine 176 (junio de 2024): 108620. http://dx.doi.org/10.1016/j.compbiomed.2024.108620.
Texto completoYao, Wenyi. "Protein structure prediction based on deep learning: HER2 in complex with a covalent inhibitor". Advances in Engineering Innovation 6, n.º 1 (20 de febrero de 2024): 13–20. http://dx.doi.org/10.54254/2977-3903/6/2024056.
Texto completoTunyasuvunakool, Kathryn, Jonas Adler, Zachary Wu, Tim Green, Michal Zielinski, Augustin Žídek, Alex Bridgland et al. "Highly accurate protein structure prediction for the human proteome". Nature 596, n.º 7873 (22 de julio de 2021): 590–96. http://dx.doi.org/10.1038/s41586-021-03828-1.
Texto completoAderinwale, Tunde, Vijay Bharadwaj, Charles Christoffer, Genki Terashi, Zicong Zhang, Rashidedin Jahandideh, Yuki Kagaya y Daisuke Kihara. "Real-time structure search and structure classification for AlphaFold protein models". Communications Biology 5, n.º 1 (5 de abril de 2022). http://dx.doi.org/10.1038/s42003-022-03261-8.
Texto completoBaltzis, Athanasios, Leila Mansouri, Suzanne Jin, Björn E. Langer, Ionas Erb y Cedric Notredame. "Highly significant improvement of protein sequence alignments with AlphaFold2". Bioinformatics, 21 de septiembre de 2022. http://dx.doi.org/10.1093/bioinformatics/btac625.
Texto completoAlderson, T. Reid, Iva Pritišanac, Đesika Kolarić, Alan M. Moses y Julie D. Forman-Kay. "Systematic identification of conditionally folded intrinsically disordered regions by AlphaFold2". Proceedings of the National Academy of Sciences 120, n.º 44 (25 de octubre de 2023). http://dx.doi.org/10.1073/pnas.2304302120.
Texto completovan der Weg, Karel y Holger Gohlke. "TopEnzyme: A framework and database for structural coverage of the functional enzyme space". Bioinformatics, 8 de marzo de 2023. http://dx.doi.org/10.1093/bioinformatics/btad116.
Texto completoZhao, Kailong, Yuhao Xia, Fujin Zhang, Xiaogen Zhou, Stan Z. Li y Guijun Zhang. "Protein structure and folding pathway prediction based on remote homologs recognition using PAthreader". Communications Biology 6, n.º 1 (4 de marzo de 2023). http://dx.doi.org/10.1038/s42003-023-04605-8.
Texto completoPeng, Zhenling, Wenkai Wang, Hong Wei, Xiaoge Li y Jianyi Yang. "Improved protein structure prediction with trRosettaX2, AlphaFold2, and optimized MSAs in CASP15". Proteins: Structure, Function, and Bioinformatics, 10 de agosto de 2023. http://dx.doi.org/10.1002/prot.26570.
Texto completoLau, Andy M., Shaun M. Kandathil y David T. Jones. "Merizo: a rapid and accurate protein domain segmentation method using invariant point attention". Nature Communications 14, n.º 1 (19 de diciembre de 2023). http://dx.doi.org/10.1038/s41467-023-43934-4.
Texto completoGoulet, Adeline y Christian Cambillau. "Present Impact of AlphaFold2 Revolution on Structural Biology, and an Illustration With the Structure Prediction of the Bacteriophage J-1 Host Adhesion Device". Frontiers in Molecular Biosciences 9 (9 de mayo de 2022). http://dx.doi.org/10.3389/fmolb.2022.907452.
Texto completoRajpal, Simar y Daniel Plymire. "Comparison Of 3D Structures Generated by AlphaFold2 to Experimental Structures In Oncogenic Proteins". Journal of Student Research 12, n.º 4 (30 de noviembre de 2023). http://dx.doi.org/10.47611/jsrhs.v12i4.5532.
Texto completoSaldaño, Tadeo, Nahuel Escobedo, Julia Marchetti, Diego Javier Zea, Juan Mac Donagh, Ana Julia Velez Rueda, Eduardo Gonik et al. "Impact of protein conformational diversity on AlphaFold predictions". Bioinformatics, 5 de abril de 2022. http://dx.doi.org/10.1093/bioinformatics/btac202.
Texto completoUzoeto, Henrietta Onyinye, Samuel Cosmas, Toluwalope Temitope Bakare y Olanrewaju Ayodeji Durojaye. "AlphaFold-latest: revolutionizing protein structure prediction for comprehensive biomolecular insights and therapeutic advancements". Beni-Suef University Journal of Basic and Applied Sciences 13, n.º 1 (17 de mayo de 2024). http://dx.doi.org/10.1186/s43088-024-00503-y.
Texto completoVaradi, Mihaly, Damian Bertoni, Paulyna Magana, Urmila Paramval, Ivanna Pidruchna, Malarvizhi Radhakrishnan, Maxim Tsenkov et al. "AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences". Nucleic Acids Research, 2 de noviembre de 2023. http://dx.doi.org/10.1093/nar/gkad1011.
Texto completoCrunkhorn, Sarah. "Assessing accuracy of AlphaFold2". Nature Reviews Drug Discovery, 31 de mayo de 2024. http://dx.doi.org/10.1038/d41573-024-00090-8.
Texto completoTsaban, Tomer, Julia K. Varga, Orly Avraham, Ziv Ben-Aharon, Alisa Khramushin y Ora Schueler-Furman. "Harnessing protein folding neural networks for peptide–protein docking". Nature Communications 13, n.º 1 (10 de enero de 2022). http://dx.doi.org/10.1038/s41467-021-27838-9.
Texto completoAbanades, Brennan, Wing Ki Wong, Fergus Boyles, Guy Georges, Alexander Bujotzek y Charlotte M. Deane. "ImmuneBuilder: Deep-Learning models for predicting the structures of immune proteins". Communications Biology 6, n.º 1 (29 de mayo de 2023). http://dx.doi.org/10.1038/s42003-023-04927-7.
Texto completoXia, Yuhao, Kailong Zhao, Dong Liu, Xiaogen Zhou y Guijun Zhang. "Multi-domain and complex protein structure prediction using inter-domain interactions from deep learning". Communications Biology 6, n.º 1 (1 de diciembre de 2023). http://dx.doi.org/10.1038/s42003-023-05610-7.
Texto completoZheng, Lingyan, Shuiyang Shi, Xiuna Sun, Mingkun Lu, Yang Liao, Sisi Zhu, Hongning Zhang et al. "MoDAFold: a strategy for predicting the structure of missense mutant protein based on AlphaFold2 and molecular dynamics". Briefings in Bioinformatics 25, n.º 2 (22 de enero de 2024). http://dx.doi.org/10.1093/bib/bbae006.
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