Improved protein structure prediction using predicted interresidue orientations
TLDR
A deep residual network for predicting interresidue orientations, in addition to distances, and a Rosetta-constrained energy-minimization protocol for rapidly and accurately generating structure models guided by these restraints are developed.Abstract:
The prediction of interresidue contacts and distances from coevolutionary data using deep learning has considerably advanced protein structure prediction. Here, we build on these advances by developing a deep residual network for predicting interresidue orientations, in addition to distances, and a Rosetta-constrained energy-minimization protocol for rapidly and accurately generating structure models guided by these restraints. In benchmark tests on 13th Community-Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP13)- and Continuous Automated Model Evaluation (CAMEO)-derived sets, the method outperforms all previously described structure-prediction methods. Although trained entirely on native proteins, the network consistently assigns higher probability to de novo-designed proteins, identifying the key fold-determining residues and providing an independent quantitative measure of the "ideality" of a protein structure. The method promises to be useful for a broad range of protein structure prediction and design problems.read more
Citations
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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
Accurate prediction of protein structures and interactions using a three-track neural network
Minkyung Baek,Frank DiMaio,Ivan Anishchenko,Justas Dauparas,Sergey Ovchinnikov,Gyu Rie Lee,Jue Wang,Qian Cong,Lisa N. Kinch,R. Dustin Schaeffer,Claudia Millán,Hahnbeom Park,Carson Adams,Caleb R. Glassman,Andy DeGiovanni,Jose Henrique Pereira,Andria V. Rodrigues,Alberdina A. van Dijk,Ana C. Ebrecht,Diederik J. Opperman,Theo Sagmeister,Christoph Buhlheller,Christoph Buhlheller,Tea Pavkov-Keller,Manoj K. Rathinaswamy,Udit Dalwadi,Calvin K. Yip,John E. Burke,K. Christopher Garcia,Nick V. Grishin,Paul D. Adams,Paul D. Adams,Randy J. Read,David Baker +33 more
TL;DR: In this article, a three-track network is proposed to combine information at the one-dimensional (1D) sequence level, the 2D distance map level, and the 3D coordinate level.
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
Accurate prediction of protein structures and interactions using a three-track neural network
B. M.,DiMaio F,Anishchenko I,Dauparas J,O. S.,Lee Gr,Wang J,Cong Q,Kinch Ln,Schaeffer Rd,Millan C,Park H,Adams C,Glassman Cr,DeGiovanni A,Pereira Jh,Rodrigues Av,AA van Dijk,Ebrecht Ac,Opperman Dj,Sagmeister T,Buhlheller C,Pavkov-Keller T,Rathinaswamy Mk,Dalwadi U,Yi Ck,Burke Je,G. Kc,Grishina Nv,Adamson Pd,Read Rj,Baker D +31 more
TL;DR: A three-track network produces structure predictions with accuracies approaching those of DeepMind in CASP14, enables the rapid solution of challenging X-ray crystallography and cryo-EM structure modeling problems, and provides insights into the functions of proteins of currently unknown structure.
Journal ArticleDOI
Comparative host-coronavirus protein interaction networks reveal pan-viral disease mechanisms.
David E. Gordon,Joseph Hiatt,Mehdi Bouhaddou,Veronica V. Rezelj,Svenja Ulferts,Hannes Braberg,Alexander S. Jureka,Kirsten Obernier,Jeffrey Z. Guo,Jyoti Batra,Robyn M. Kaake,Andrew R. Weckstein,Tristan W. Owens,Meghna Gupta,Sergei Pourmal,Erron W. Titus,Merve Cakir,Margaret Soucheray,Michael J. McGregor,Zeynep Cakir,Gwendolyn M. Jang,Matthew J. O’Meara,Tia A. Tummino,Ziyang Zhang,Helene Foussard,Ajda Rojc,Yuan Zhou,Dmitry Kuchenov,Ruth Hüttenhain,Jiewei Xu,Manon Eckhardt,Danielle L. Swaney,Jacqueline M. Fabius,Manisha Ummadi,Beril Tutuncuoglu,Ujjwal Rathore,Maya Modak,Paige Haas,Kelsey M. Haas,Zun Zar Chi Naing,Ernst H. Pulido,Ying Shi,Inigo Barrio-Hernandez,Danish Memon,Eirini Petsalaki,Alistair Dunham,Miguel Correa Marrero,David F. Burke,Cassandra Koh,Thomas Vallet,Jesus A. Silvas,Caleigh M. Azumaya,Christian B. Billesbølle,Axel F. Brilot,Melody G. Campbell,Melody G. Campbell,Amy Diallo,Miles Sasha Dickinson,Devan Diwanji,Nadia Herrera,Nick Hoppe,Huong T. Kratochvil,Yanxin Liu,Gregory E. Merz,Michelle Moritz,Henry C. Nguyen,Carlos Nowotny,Cristina Puchades,Alexandrea N. Rizo,Ursula Schulze-Gahmen,Amber M. Smith,Ming Sun,Iris D. Young,Jianhua Zhao,Daniel Asarnow,Justin T Biel,Alisa Bowen,Julian R. Braxton,Jen Chen,Cynthia M. Chio,Un Seng Chio,Ishan Deshpande,Loan Doan,Bryan Faust,Sebastian Flores,Mingliang Jin,Kate Kim,Victor L Lam,Fei Li,Junrui Li,Y. Li,Yang Li,Xi Liu,Megan Lo,Kyle E. Lopez,Arthur Alves de Melo,Frank R. Moss,Phuong Nguyen,Joana Paulino,Komal Ishwar Pawar,Jessica K. Peters,Thomas H. Pospiech,Maliheh Safari,Smriti Sangwan,Kaitlin Schaefer,Paul V. Thomas,Aye C. Thwin,Raphael Trenker,Eric Tse,Tsz Kin Martin Tsui,Feng Wang,Natalie Whitis,Zanlin Yu,Kaihua Zhang,Yang Zhang,Fengbo Zhou,Daniel J. Saltzberg,Anthony J. Hodder,Amber S. M. Shun-Shion,Daniel M. Williams,Kris M. White,Romel Rosales,Thomas Kehrer,Lisa Miorin,Elena Moreno,Arvind H. Patel,Suzannah J. Rihn,Mir M. Khalid,Albert Vallejo-Gracia,Parinaz Fozouni,Parinaz Fozouni,Camille R. Simoneau,Camille R. Simoneau,Theodore L. Roth,David Wu,Mohd Anisul Karim,Maya Ghoussaini,Ian Dunham,Francesco Berardi,Sebastian Weigang,Maxime Chazal,Jisoo Park,James Logue,Marisa McGrath,Stuart Weston,Robert Haupt,C. James Hastie,Matthew Elliott,Fiona Brown,Kerry A. Burness,Elaine Reid,Mark Dorward,Clare Johnson,Stuart G. Wilkinson,Anna Geyer,Daniel M. Giesel,Carla Baillie,Samantha Raggett,Hannah Leech,Rachel Toth,Nicola Goodman,Kathleen C. Keough,Abigail L. Lind,Reyna J. Klesh,Kafi R. Hemphill,Jared Carlson-Stevermer,Jennifer Oki,Kevin Holden,Travis J. Maures,Katherine S. Pollard,Katherine S. Pollard,Andrej Sali,David A. Agard,Yifan Cheng,James S. Fraser,Adam Frost,Natalia Jura,Tanja Kortemme,Aashish Manglik,Daniel R. Southworth,Robert M. Stroud,Dario R. Alessi,Paul Davies,Matthew B. Frieman,Trey Ideker,Carmen Abate,Nolwenn Jouvenet,Nolwenn Jouvenet,Georg Kochs,Brian K. Shoichet,Melanie Ott,Melanie Ott,Massimo Palmarini,Kevan M. Shokat,Adolfo García-Sastre,Jeremy A. Rassen,Robert Grosse,Oren S. Rosenberg,Kliment A. Verba,Christopher F. Basler,Marco Vignuzzi,Andrew A. Peden,Pedro Beltrao,Nevan J. Krogan +203 more
TL;DR: The authors identified shared biology and host-directed drug targets to prioritize therapeutics with potential for rapid deployment against current and future coronavirus outbreaks, and found that individuals with genotypes corresponding to higher soluble IL17RA levels in plasma are at decreased risk of COVID-19 hospitalization.
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