Sergey Ovchinnikov
Sergey Ovchinnikov
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Cited by
ColabFold: making protein folding accessible to all
M Mirdita, K Schütze, Y Moriwaki, L Heo, S Ovchinnikov, M Steinegger
Nature methods 19 (6), 679-682, 2022
Accurate prediction of protein structures and interactions using a three-track neural network
M Baek, F DiMaio, I Anishchenko, J Dauparas, S Ovchinnikov, GR Lee, ...
Science 373 (6557), 871-876, 2021
Improved protein structure prediction using predicted interresidue orientations
J Yang, I Anishchenko, H Park, Z Peng, S Ovchinnikov, D Baker
Proceedings of the National Academy of Sciences 117 (3), 1496-1503, 2020
Assessing the utility of coevolution-based residue–residue contact predictions in a sequence-and structure-rich era
H Kamisetty, S Ovchinnikov, D Baker
Proceedings of the National Academy of Sciences 110 (39), 15674-15679, 2013
Robust and accurate prediction of residue–residue interactions across protein interfaces using evolutionary information
S Ovchinnikov, H Kamisetty, D Baker
elife 3, e02030, 2014
Macromolecular modeling and design in Rosetta: recent methods and frameworks
JK Leman, BD Weitzner, SM Lewis, J Adolf-Bryfogle, N Alam, RF Alford, ...
Nature methods 17 (7), 665-680, 2020
Protein structure determination using metagenome sequence data
S Ovchinnikov, H Park, N Varghese, PS Huang, GA Pavlopoulos, DE Kim, ...
Science 355 (6322), 294-298, 2017
De novo protein design by deep network hallucination
I Anishchenko, SJ Pellock, TM Chidyausiku, TA Ramelot, S Ovchinnikov, ...
Nature 600 (7889), 547-552, 2021
De novo design of protein structure and function with RFdiffusion
JL Watson, D Juergens, NR Bennett, BL Trippe, J Yim, HE Eisenach, ...
Nature 620 (7976), 1089-1100, 2023
A structural biology community assessment of AlphaFold2 applications
M Akdel, DEV Pires, EP Pardo, J Jänes, AO Zalevsky, B Mészáros, ...
Nature Structural & Molecular Biology 29 (11), 1056-1067, 2022
Computed structures of core eukaryotic protein complexes
IR Humphreys, J Pei, M Baek, A Krishnakumar, I Anishchenko, ...
Science 374 (6573), eabm4805, 2021
De novo design of a fluorescence-activating β-barrel
J Dou, AA Vorobieva, W Sheffler, LA Doyle, H Park, MJ Bick, B Mao, ...
Nature 561 (7724), 485-491, 2018
Scaffolding protein functional sites using deep learning
J Wang, S Lisanza, D Juergens, D Tischer, JL Watson, KM Castro, ...
Science 377 (6604), 387-394, 2022
Large-scale determination of previously unsolved protein structures using evolutionary information
S Ovchinnikov, L Kinch, H Park, Y Liao, J Pei, DE Kim, H Kamisetty, ...
elife 4, e09248, 2015
Transformer protein language models are unsupervised structure learners
R Rao, J Meier, T Sercu, S Ovchinnikov, A Rives
Biorxiv, 2020.12. 15.422761, 2020
Protein interaction networks revealed by proteome coevolution
Q Cong, I Anishchenko, S Ovchinnikov, D Baker
Science 365 (6449), 185-189, 2019
Architectures of lipid transport systems for the bacterial outer membrane
DC Ekiert, G Bhabha, GL Isom, G Greenan, S Ovchinnikov, IR Henderson, ...
Cell 169 (2), 273-285. e17, 2017
Cryo-EM structure of the protein-conducting ERAD channel Hrd1 in complex with Hrd3
S Schoebel, W Mi, A Stein, S Ovchinnikov, R Pavlovicz, F DiMaio, D Baker, ...
Nature 548 (7667), 352-355, 2017
Structural basis of ER-associated protein degradation mediated by the Hrd1 ubiquitin ligase complex
X Wu, M Siggel, S Ovchinnikov, W Mi, V Svetlov, E Nudler, M Liao, ...
Science 368 (6489), eaaz2449, 2020
Origins of coevolution between residues distant in protein 3D structures
I Anishchenko, S Ovchinnikov, H Kamisetty, D Baker
Proceedings of the National Academy of Sciences 114 (34), 9122-9127, 2017
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