Journal ArticleDOI
Can AlphaFold2 predict the impact of missense mutations on structure?
Gwen R. Buel,Kylie J. Walters +1 more
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This article is published in Nature Structural & Molecular Biology.The article was published on 2022-01-01. It has received 104 citations till now. The article focuses on the topics: Medicine & Missense mutation.read more
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A structural biology community assessment of AlphaFold2 applications
TL;DR: In this paper , the AlphaFold2 (AF2) model was used to predict protein structural elements, including missense variants, function and ligand binding site predictions, and modeling of experimental structural data.
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Scaffolding protein functional sites using deep learning
Jue Wang,Sidney Lisanza,David Juergens,Doug Tischer,Joseph L. Watson,Karla M Castro,Robert J. Ragotte,Amijai Saragovi,Lukas F. Milles,Minkyung Baek,Ivan Anishchenko,Wei Yang,Derrick R. Hicks,Marc Expòsit,Thomas Schlichthaerle,Jung Ho Chun,Justas Dauparas,N. Bennett,Basile I. M. Wicky,Andrew G. Muenks,Frank DiMaio,Bruno E. Correia,Sergey Ovchinnikov,David Baker +23 more
TL;DR: Wang et al. as mentioned in this paper proposed two deep learning methods to design proteins that contain prespecified functional sites, which can enable the scaffolding of desired functional residues within a well-folded designed protein.
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What's next for AlphaFold and the AI protein-folding revolution
TL;DR: DeepMind software that can predict the 3D shape of proteins is already changing biology as mentioned in this paper , and it is capable of predicting 3D shapes of proteins in real-world proteins.
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AlphaFold2: A Role for Disordered Protein/Region Prediction?
TL;DR: The ability of AlphaFold2 to predict disordered regions against traditional sequence-based disorder predictors is assessed and an interesting relationship between the pLDDT and secondary structure is noted, that may explain the observations and suggest a broader application of the p LDDT for characterizing the local dynamics of intrinsically disordered proteins and regions (IDPs/IDRs).
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The accuracy of protein structures in solution determined by AlphaFold and NMR
TL;DR: In the recent Critical Assessment of Structure Prediction (CASP) competition, AlphaFold2 performed outstandingly as mentioned in this paper , which has two alternative explanations: either the NMR structures were poor, implying that Alpha-Fold may be more accurate than NMR, or there is a genuine difference between crystal and solution structures.
References
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Journal ArticleDOI
Highly accurate protein structure prediction with AlphaFold
John M. Jumper,Richard O. Evans,Alexander Pritzel,Tim Green,Michael Figurnov,Olaf Ronneberger,Kathryn Tunyasuvunakool,Russell Bates,Augustin Žídek,Anna Potapenko,Alex Bridgland,Clemens Meyer,Simon A. A. Kohl,Andrew J. Ballard,Andrew Cowie,Bernardino Romera-Paredes,Stanislav Nikolov,R. D. Jain,Jonas Adler,Trevor Back,Stig Petersen,David Reiman,Ellen Clancy,Michal Zielinski,Martin Steinegger,Michalina Pacholska,Tamas Berghammer,Sebastian Bodenstein,David L. Silver,Oriol Vinyals,Andrew W. Senior,Koray Kavukcuoglu,Pushmeet Kohli,Demis Hassabis +33 more
TL;DR: For example, AlphaFold as mentioned in this paper predicts protein structures with an accuracy competitive with experimental structures in the majority of cases using a novel deep learning architecture. But the accuracy is limited by the fact that no homologous structure is available.
Journal ArticleDOI
Highly accurate protein structure prediction for the human proteome
Kathryn Tunyasuvunakool,Jonas Adler,Zachary Wu,Tim Green,Michal Zielinski,Augustin Žídek,Alex Bridgland,Andrew Cowie,Clemens Meyer,Agata Laydon,Sameer Velankar,Gerard J. Kleywegt,Alex Bateman,Richard Evans,Alexander Pritzel,Michael Figurnov,Olaf Ronneberger,Russell Bates,Simon A. A. Kohl,Anna Potapenko,Andrew J. Ballard,Bernardino Romera-Paredes,Stanislav Nikolov,R. D. Jain,Ellen Clancy,David Reiman,Stig Petersen,Andrew W. Senior,Koray Kavukcuoglu,Ewan Birney,Pushmeet Kohli,John M. Jumper,Demis Hassabis +32 more
TL;DR: The AlphaFold2 dataset as discussed by the authors is a large-scale and high-accuracy structure prediction dataset for protein structures, which is used to evaluate the structural properties of proteins.
Journal ArticleDOI
A Systematic Genetic Assessment of 1,433 Sequence Variants of Unknown Clinical Significance in the BRCA1 and BRCA2 Breast Cancer–Predisposition Genes
Douglas F. Easton,Amie M. Deffenbaugh,Dmitry Pruss,Cynthia Frye,Richard J. Wenstrup,Kristina Allen-Brady,Sean V. Tavtigian,Alvaro N.A. Monteiro,Edwin S. Iversen,Fergus J. Couch,David E. Goldgar +10 more
TL;DR: The global assessment of 1,433 sequence variants of unknown significance in the BRCA genes will be invaluable for validation of functional assays, structural models, and in silico analyses.
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Crystal structure of the BRCT repeat region from the breast cancer-associated protein BRCA1
TL;DR: The structure provides a basis to predict the structural consequences of uncharacterized BRCA1 mutations and may represent a general mode of interaction between homologous domains within proteins that interact to regulate the cellular response to DNA damage.
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DNA-repair protein hHR23a alters its protein structure upon binding proteasomal subunit S5a
TL;DR: This work illustrates how the proteasomal subunit S5a regulates hHR23a protein structure and elucidated the structure and dynamic properties of the 40-kDa hHR 23a protein and shows it to contain four structured domains connected by flexible linker regions.