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Deep generative models for structure-based drug design (SBDD), where molecule generation is conditioned on a 3D protein pocket, have received considerable interest in recent years.
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Tomohide Masuda, Matthew Ragoza, and David Ryan Koes · 2020
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Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Three-dimensional convolutional neural networks and a cross-docked data set for structure-based drug design
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Geometric deep learning on molecular representations
Kenneth Atz, Francesca Grisoni, and Gisbert Schneider · 2021
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A 3d generative model for structure-based drug design
Shitong Luo, Jiaqi Guan, Jianzhu Ma, and Jian Peng · 2021
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G Richard Bickerton, Gaia V Paolini, Jérémy Besnard, Sorel Muresan, and Andrew L Hopkins · 2012
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Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings
Christopher A Lipinski, Franco Lombardo, Beryl W Dominy, and Paul J Feeney · 2012
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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Lessons learned in empirical scoring with smina from the csar 2011 benchmarking exercise
David Ryan Koes, Matthew P Baumgartner, and Carlos J Camacho · 2013
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Generative adversarial networks
Ian J Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Molecular docking and structure-based drug design strategies
Leonardo G Ferreira, Ricardo N Dos Santos, Glaucius Oliva, and Adriano D Andricopulo · 2015
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Fast, accurate, and reliable molecular docking with quickvina 2
Amr Alhossary, Stephanus Daniel Handoko, Yuguang Mu, and Chee-Keong Kwoh · 2015
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Prolif: a library to encode molecular interactions as fingerprints
Cédric Bouysset and Sébastien Fiorucci · 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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Molgensurvey: A systematic survey in machine learning models for molecule design
Yuanqi Du, Tianfan Fu, Jimeng Sun, and Shengchao Liu · 2022
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Pocket2mol: Efficient molecular sampling based on 3d protein pockets
Xingang Peng, Shitong Luo, Jiaqi Guan, Qi Xie, Jian Peng, and Jianzhu Ma · 2022
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Structure-based drug design with equivariant diffusion models
Arne Schneuing, Yuanqi Du, Charles Harris, Arian Jamasb, Ilia Igashov, Weitao Du, Tom Blundell, Pietro Lió, Carla Gomes, Max Welling, et al · 2022
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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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Se (3) diffusion model with application to protein backbone generation
Jason Yim, Brian L Trippe, Valentin De Bortoli, Emile Mathieu, Arnaud Doucet, Regina Barzilay, and Tommi Jaakkola · 2022
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Structure-based drug design with geometric deep learning
Clemens Isert, Kenneth Atz, and Gisbert Schneider · 2023
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3d equivariant diffusion for target-aware molecule generation and affinity prediction
Jiaqi Guan, Wesley Wei Qian, Xingang Peng, Yufeng Su, Jian Peng, and Jianzhu Ma · 2023
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Deep generative models for 3d molecular structure
Benoit Baillif, Jason Cole, Patrick McCabe, and Andreas Bender · 2023
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On the importance of noise scheduling for diffusion models
Ting Chen · 2023
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