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Understanding how proteins structurally interact is crucial to modern biology, with applications in drug discovery and protein design.
A solution for the best rotation to relate two sets of vectors
Wolfgang Kabsch · 1976
Earlier work this paper cites.
Zdock: an initial-stage protein-docking algorithm
Rong Chen, Li Li, and Zhiping Weng · 2003
Earlier work this paper cites.
Patchdock and symmdock: servers for rigid and symmetric docking
Dina Schneidman-Duhovny, Yuval Inbar, Ruth Nussinov, and Haim J Wolfson · 2005
Earlier work this paper cites.
Docking and scoring protein complexes: Capri 3rd edition
Marc F Lensink, Raúl Méndez, and Shoshana J Wodak · 2007
Earlier work this paper cites.
An iterative knowledge-based scoring function for protein–protein recognition
Sheng-You Huang and Xiaoqin Zou · 2008
Earlier work this paper cites.
The haddock web server for data-driven biomolecular docking
Sjoerd J De Vries, Marc Van Dijk, and Alexandre MJJ Bonvin · 2010
Earlier work this paper cites.
An integrated suite of fast docking algorithms
Efrat Mashiach, Dina Schneidman-Duhovny, Aviyah Peri, Yoli Shavit, Ruth Nussinov, and Haim J Wolfson · 2010
Earlier work this paper cites.
A knowledge-based scoring function for protein-rna interactions derived from a statistical mechanics-based iterative method
Sheng-You Huang and Xiaoqin Zou · 2014
Earlier work this paper cites.
Protein-protein docking: From interaction to interactome
Ilya A Vakser · 2014
Earlier work this paper cites.
A web interface for easy flexible protein-protein docking with attract
Sjoerd J de Vries, Christina EM Schindler, Isaure Chauvot de Beauchêne, and Martin Zacharias · 2015
Earlier work this paper cites.
Updates to the integrated protein–protein interaction benchmarks: docking benchmark version 5 and affinity benchmark version 2
Thom Vreven, Iain H Moal, Anna Vangone, Brian G Pierce, Panagiotis L Kastritis, Mieczyslaw Torchala, Raphael Chaleil, Brian Jiménez-García, Paul A Bates, Juan Fernandez-Recio, et al · 2015
Earlier work this paper cites.
Dockq: a quality measure for protein-protein docking models
Sankar Basu and Björn Wallner · 2016
Earlier work this paper cites.
The cluspro web server for protein–protein docking
Dima Kozakov, David R Hall, Bing Xia, Kathryn A Porter, Dzmitry Padhorny, Christine Yueh, Dmitri Beglov, and Sandor Vajda · 2017
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Protein-protein and peptide-protein docking and refinement using attract in capri
Christina EM Schindler, Isaure Chauvot de Beauchêne, Sjoerd J de Vries, and Martin Zacharias · 2017
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Hdock: a web server for protein–protein and protein–dna/rna docking based on a hybrid strategy
Yumeng Yan, Di Zhang, Pei Zhou, Botong Li, and Sheng-You Huang · 2017
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Tensor field networks: Rotation-and translation-equivariant neural networks for 3d point clouds
Nathaniel Thomas, Tess Smidt, Steven Kearnes, Lusann Yang, Li Li, Kai Kohlhoff, and Patrick Riley · 2018
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Functional maps representation on product manifolds
Emanuele Rodolà, Zorah Lähner, Alexander M Bronstein, Michael M Bronstein, and Justin Solomon · 2019
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Independent se (3)-equivariant models for end-to-end rigid protein docking
Octavian-Eugen Ganea, Xinyuan Huang, Charlotte Bunne, Yatao Bian, Regina Barzilay, Tommi Jaakkola, and Andreas Krause · 2021
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Deep learning for protein–protein interaction site prediction
Arian R Jamasb, Ben Day, Cătălina Cangea, Pietro Liò, and Tom L Blundell · 2021
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Diffdock: Diffusion steps, twists, and turns for molecular docking
Gabriele Corso, Hannes Stärk, Bowen Jing, Regina Barzilay, and Tommi Jaakkola · 2022
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Riemannian score-based generative modeling
Valentin De Bortoli, Emile Mathieu, Michael Hutchinson, James Thornton, Yee Whye Teh, and Arnaud Doucet · 2022
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Equivariant diffusion for molecule generation in 3d
Emiel Hoogeboom, Vıctor Garcia Satorras, Clément Vignac, and Max Welling · 2022
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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End-to-end learning on 3d protein structure for interface prediction
Raphael Townshend, Rishi Bedi, Patricia Suriana, and Ron Dror · 2019
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Performance and its limits in rigid body protein-protein docking
Israel T Desta, Kathryn A Porter, Bing Xia, Dima Kozakov, and Sandor Vajda · 2020
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Euclidean neural networks: e3nn
Mario Geiger, Tess Smidt, M Alby, Benjamin Kurt Miller, Wouter Boomsma, Bradley Dice, Kostiantyn Lapchevskyi, Maurice Weiler, Michał Tyszkiewicz, Simon Batzner, et al · 2020
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2020
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The hdock server for integrated protein–protein docking
Yumeng Yan, Huanyu Tao, Jiahua He, and Sheng-You Huang · 2020
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Protein complex prediction with alphafold-multimer
Richard Evans, Michael O’Neill, Alexander Pritzel, Natasha Antropova, Andrew Senior, Tim Green, Augustin Žídek, Russ Bates, Sam Blackwell, Jason Yim, et al · 2021
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Illuminating protein space with a programmable generative model
John Ingraham, Max Baranov, Zak Costello, Vincent Frappier, Ahmed Ismail, Shan Tie, Wujie Wang, Vincent Xue, Fritz Obermeyer, Andrew Beam, et al · 2022
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Torsional diffusion for molecular conformer generation
Bowen Jing, Gabriele Corso, Jeffrey Chang, Regina Barzilay, and Tommi Jaakkola · 2022
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Language models of protein sequences at the scale of evolution enable accurate structure prediction
Zeming Lin, Halil Akin, Roshan Rao, Brian Hie, Zhongkai Zhu, Wenting Lu, Allan dos Santos Costa, Maryam Fazel-Zarandi, Tom Sercu, Sal Candido, et al · 2022
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Physics-informed deep neural network for rigid-body protein docking
Freyr Sverrisson, Jean Feydy, Joshua Southern, Michael M. Bronstein, and Bruno Correia · 2022
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Diffusion probabilistic modeling of protein backbones in 3d for the motif-scaffolding problem
Brian L Trippe, Jason Yim, Doug Tischer, Tamara Broderick, David Baker, Regina Barzilay, and Tommi Jaakkola · 2022
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Modeling molecular structures with intrinsic diffusion models
Gabriele Corso · 2023
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Deep learning for flexible and site-specific protein docking and design
Matthew McPartlon and Jinbo Xu · 2023
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