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Antibody design is valuable for therapeutic usage and biological research.
Stereochemistry of polypeptide chain configurations
GN Ramachandran, C Ramakrishnan, and V Sasisekharan · 1963
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A solution for the best rotation to relate two sets of vectors
Wolfgang Kabsch · 1976
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Amino acid substitution matrices from protein blocks
Steven Henikoff and Jorja G Henikoff · 1992
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Robust estimation of a location parameter
Peter J Huber · 1992
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Artificial neural networks (the multilayer perceptron)—a review of applications in the atmospheric sciences
Matt W Gardner and SR Dorling · 1998
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Dissecting protein–protein recognition sites
Pinak Chakrabarti and Joel Janin · 2002
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Imgt unique numbering for immunoglobulin and t cell receptor variable domains and ig superfamily v-like domains
Marie-Paule Lefranc, Christelle Pommié, Manuel Ruiz, Véronique Giudicelli, Elodie Foulquier, Lisa Truong, Valérie Thouvenin-Contet, and Gérard Lefranc · 2003
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Scoring function for automated assessment of protein structure template quality
Yang Zhang and Jeffrey Skolnick · 2004
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Prediction of residues in discontinuous b-cell epitopes using protein 3d structures
Pernille Haste Andersen, Morten Nielsen, and OLE Lund · 2006
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Characterization of protein–protein interfaces
Changhui Yan, Feihong Wu, Robert L Jernigan, Drena Dobbs, and Vasant Honavar · 2008
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How significant is a protein structure similarity with tm-score= 0.5?
Jinrui Xu and Yang Zhang · 2010
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Computer-aided antibody design
Daisuke Kuroda, Hiroki Shirai, Matthew P Jacobson, and Haruki Nakamura · 2012
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Sabdab: the structural antibody database
James Dunbar, Konrad Krawczyk, Jinwoo Leem, Terry Baker, Angelika Fuchs, Guy Georges, Jiye Shi, and Charlotte M Deane · 2014
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Optmaven–a new framework for the de novo design of antibody variable region models targeting specific antigen epitopes
Tong Li, Robert J Pantazes, and Costas D Maranas · 2014
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Abdesign: A n algorithm for combinatorial backbone design guided by natural conformations and sequences
Gideon D Lapidoth, Dror Baran, Gabriele M Pszolla, Christoffer Norn, Assaf Alon, Michael D Tyka, and Sarel J Fleishman · 2015
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Advances in antibody design
Kathryn E Tiller and Peter M Tessier · 2015
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The rosetta all-atom energy function for macromolecular modeling and design
Rebecca F Alford, Andrew Leaver-Fay, Jeliazko R Jeliazkov, Matthew J O’Meara, Frank P DiMaio, Hahnbeom Park, Maxim V Shapovalov, P Douglas Renfrew, Vikram K Mulligan, Kalli Kappel, et al · 2017
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Principles for computational design of binding antibodies
Dror Baran, M Gabriele Pszolla, Gideon D Lapidoth, Christoffer Norn, Orly Dym, Tamar Unger, Shira Albeck, Michael D Tyka, and Sarel J Fleishman · 2017
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Openmm 7: Rapid development of high performance algorithms for molecular dynamics
Peter Eastman, Jason Swails, John D Chodera, Robert T McGibbon, Yutong Zhao, Kyle A Beauchamp, Lee-Ping Wang, Andrew C Simmonett, Matthew P Harrigan, Chaya D Stern, et al · 2017
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Mmseqs2 enables sensitive protein sequence searching for the analysis of massive data sets
Martin Steinegger and Johannes Söding · 2017
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Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio · 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
Improving molecular design by stochastic iterative target augmentation
Kevin Yang, Wengong Jin, Kyle Swanson, Regina Barzilay, and Tommi Jaakkola · 2020
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Fold2seq: A joint sequence (1d)-fold (3d) embedding-based generative model for protein design
Yue Cao, Payel Das, Vijil Chenthamarakshan, Pin-Yu Chen, Igor Melnyk, and Yang Shen · 2021
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Iterative refinement graph neural network for antibody sequence-structure co-design
Wengong Jin, Jeremy Wohlwend, Regina Barzilay, and Tommi Jaakkola · 2021
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Highly accurate protein structure prediction with alphafold
John Jumper, Richard Evans, Alexander Pritzel, Tim Green, Michael Figurnov, Olaf Ronneberger, Kathryn Tunyasuvunakool, Russ Bates, Augustin Žídek, Anna Potapenko, et al · 2021
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Spherical message passing for 3d molecular graphs
Yi Liu, Limei Wang, Meng Liu, Yuchao Lin, Xuan Zhang, Bora Oztekin, and Shuiwang Ji · 2021
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Cited alongside, same era.
Rosettaantibodydesign (rabd): A general framework for computational antibody design
Jared Adolf-Bryfogle, Oleks Kalyuzhniy, Michael Kubitz, Brian D Weitzner, Xiaozhen Hu, Yumiko Adachi, William R Schief, and Roland L Dunbrack Jr · 2018
Cited alongside, same era.
Computational design of antibodies
Sharon Fischman and Yanay Ofran · 2018
Cited alongside, same era.
Unified rational protein engineering with sequence-based deep representation learning
Ethan C Alley, Grigory Khimulya, Surojit Biswas, Mohammed AlQuraishi, and George M Church · 2019
Cited alongside, same era.
Why recombinant antibodies—benefits and applications
Koli Basu, Evan M Green, Yifan Cheng, and Charles S Craik · 2019
Cited alongside, same era.
Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules
Niklas Gebauer, Michael Gastegger, and Kristof Schütt · 2019
Cited alongside, same era.
Generative models for graph-based protein design
John Ingraham, Vikas Garg, Regina Barzilay, and Tommi Jaakkola · 2019
Cited alongside, same era.
Skempi 2.0: an updated benchmark of changes in protein–protein binding energy, kinetics and thermodynamics upon mutation
Justina Jankauskaitė, Brian Jiménez-García, Justas Dapkūnas, Juan Fernández-Recio, and Iain H Moal · 2019
Cited alongside, same era.
Frame averaging for invariant and equivariant network design
Omri Puny, Matan Atzmon, Heli Ben-Hamu, Edward J Smith, Ishan Misra, Aditya Grover, and Yaron Lipman · 2021
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Deciphering antibody affinity maturation with language models and weakly supervised learning
Jeffrey A Ruffolo, Jeffrey J Gray, and Jeremias Sulam · 2021
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Antibody design using lstm based deep generative model from phage display library for affinity maturation
Koichiro Saka, Taro Kakuzaki, Shoichi Metsugi, Daiki Kashiwagi, Kenji Yoshida, Manabu Wada, Hiroyuki Tsunoda, and Reiji Teramoto · 2021
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E (n) equivariant graph neural networks
Vıćtor Garcia Satorras, Emiel Hoogeboom, and Max Welling · 2021
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Protein design and variant prediction using autoregressive generative models
Jung-Eun Shin, Adam J Riesselman, Aaron W Kollasch, Conor McMahon, Elana Simon, Chris Sander, Aashish Manglik, Andrew C Kruse, and Debora S Marks · 2021
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In silico proof of principle of machine learning-based antibody design at unconstrained scale
Rahmad Akbar, Philippe A Robert, Cédric R Weber, Michael Widrich, Robert Frank, Milena Pavlović, Lonneke Scheffer, Maria Chernigovskaya, Igor Snapkov, Andrei Slabodkin, et al · 2022
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Geometrically equivariant graph neural networks: A survey
Jiaqi Han, Yu Rong, Tingyang Xu, and Wenbing Huang · 2022
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Equivariant graph mechanics networks with constraints
Wenbing Huang, Jiaqi Han, Yu Rong, Tingyang Xu, Fuchun Sun, and Junzhou Huang · 2022
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Antibody-antigen docking and design via hierarchical structure refinement
Wengong Jin, Regina Barzilay, and Tommi Jaakkola · 2022
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Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies
Jeffrey A Ruffolo, Lee-Shin Chu, Sai Pooja Mahajan, and Jeffrey J Gray · 2022
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Deep learning guided optimization of human antibody against sars-cov-2 variants with broad neutralization
Sisi Shan, Shitong Luo, Ziqing Yang, Junxian Hong, Yufeng Su, Fan Ding, Lili Fu, Chenyu Li, Peng Chen, Jianzhu Ma, et al · 2022
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