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
TLDR
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.Abstract:
Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort1–4, the structures of around 100,000 unique proteins have been determined5, but this represents a small fraction of the billions of known protein sequences6,7. Structural coverage is bottlenecked by the months to years of painstaking effort required to determine a single protein structure. Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics. Predicting the three-dimensional structure that a protein will adopt based solely on its amino acid sequence—the structure prediction component of the ‘protein folding problem’8—has been an important open research problem for more than 50 years9. Despite recent progress10–14, existing methods fall far short of atomic accuracy, especially when no homologous structure is available. Here we provide the first computational method that can regularly predict protein structures with atomic accuracy even in cases in which no similar structure is known. We validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14)15, demonstrating accuracy competitive with experimental structures in a majority of cases and greatly outperforming other methods. Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm. AlphaFold predicts protein structures with an accuracy competitive with experimental structures in the majority of cases using a novel deep learning architecture.read more
Citations
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Journal ArticleDOI
AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models.
Mihaly Varadi,Stephen Anyango,Mandar Deshpande,Sreenath Nair,Cindy Natassia,Galabina Yordanova,David Yu Yuan,Oana Stroe,Gemma Wood,Agata Laydon,Augustin Žídek,Tim Green,Kathryn Tunyasuvunakool,Stig Petersen,John M. Jumper,Ellen Clancy,Richard E. Green,Ankur Vora,Mira Lutfi,Michael Figurnov,Andrew Cowie,Nicole Hobbs,Pushmeet Kohli,Gerard J. Kleywegt,Ewan Birney,Demis Hassabis,Sameer Velankar +26 more
TL;DR: The AlphaFold Protein Structure Database (AlphaFold DB, https://alphafold.ebi.ac.uk) is an openly accessible, extensive database of high-accuracy protein-structure predictions.
Journal ArticleDOI
ColabFold: making protein folding accessible to all
TL;DR: ColabFold as discussed by the authors combines the fast homology search of MMseqs2 with AlphaFold2 or RoseTTAFold for protein folding and achieves 40-60fold faster search and optimized model utilization.
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.
Posted ContentDOI
Protein complex prediction with AlphaFold-Multimer
Richard Evans,Michael J. O'Neill,Alexander Pritzel,Natasha Antropova,Andrew W. Senior,Tim Green,Augustin Žídek,Russell Bates,Sam Blackwell,Jason Yim,Olaf Ronneberger,Sebastian Bodenstein,Michal Zielinski,Alex Bridgland,Anna Potapenko,Andrew Cowie,Kathryn Tunyasuvunakool,R. D. Jain,Ellen Clancy,Pushmeet Kohli,John M. Jumper,Demis Hassabis +21 more
TL;DR: In this article, an AlphaFold model trained specifically for multimeric inputs of known stoichiometry was proposed, which significantly increases the accuracy of predicted multimimeric interfaces over input-adapted single-chain AlphaFolds.
Journal ArticleDOI
SARS-CoV-2 Omicron-B.1.1.529 leads to widespread escape from neutralizing antibody responses
Wanwisa Dejnirattisai,Jiandong Huo,D. Zhou,Jiří Zahradník,P Supasa,Changxiao Liu,Helen M. E. Duyvesteyn,Helen M. Ginn,Alexander J. Mentzer,Aekkachai Tuekprakhon,Rungtiwa Nutalai,Beibei Wang,Aiste Dijokaite,Suman Khan,Ori Avinoam,M.W. Bahar,Donal T. Skelly,S Adele,Síle A. Johnson,Thomas G Ritter,Chris Jb Mason,Christina Dold,Daniel Pan,Sara Assadi,A. Bellass,Nikki Omo-Dare,David Koeckerling,Amy Flaxman,D Jenkin,Parvinder K. Aley,Merryn Voysey,Sue Ann Costa Clemens,Felipe Gomes Naveca,Valdinete Alves do Nascimento,Fernanda Nascimento,Cristiano Fernandes da Costa,Paola Cristina Resende,Alex Pauvolid-Corrêa,Marilda M. Siqueira,Vicky L. Baillie,Natali Serafin,Gaurav Kwatra,Kelly Da Silva,Shabir A. Madhi,Marta C. Nunes,Tariq Mehmood Malik,Peter J. M. Openshaw,J Kenneth Baillie,Malcolm G Semple,Alain Townsend,Kuan-Ying A. Huang,Tiong Kit Tan,Miles W. Carroll,Paul Klenerman,Eleanor Barnes,Susanna Dunachie,Bede Constantinides,Hermione J. Webster,Derrick W. Crook,Andrew J. Pollard,Teresa Lambe,Neil G. Paterson,Mark Williams,Elizabeth E. Fry,Juthathip Mongkolsapaya,Jingshan Ren,Gideon Schreiber,David Stuart,Gavin R. Screaton +68 more
TL;DR: In this article , a new SARS-CoV-2 viral isolate Omicron-B.1.529 was announced, containing far more mutations in Spike (S) than previously reported variants, leading to a large number of mutations in the ACE2 binding site and rebalances receptor affinity to that of earlier pandemic viruses.
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