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Generative models see increasing use in computer-aided drug design.
The Logic of Chemical Synthesis
E. J. Corey and X.-M. Cheng · 1989
Earlier work this paper cites.
Automated site-directed drug design: the concept of spacer skeletons for primary structure generation
Richard A Lewis and PM Dean · 1989
Earlier work this paper cites.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J. Williams · 1992
Earlier work this paper cites.
BIRCH: An efficient data clustering method for very large databases
Tian Zhang, Raghu Ramakrishnan, and Miron Livny · 1996
Earlier work this paper cites.
Synopsis: SYNthesize and OPtimize System in Silico
H. Maarten Vinkers, Marc R. de Jonge, Frederik F. D. Daeyaert, Jan Heeres, Lucien M. H. Koymans, Joop H. van Lenthe, Paul J. Lewi, Henk Timmerman, Koen Van Aken, and Paul A. J. Janssen · 2003
Earlier work this paper cites.
Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions
Peter Ertl and Ansgar Schuffenhauer · 2009
Earlier work this paper cites.
Soluble epoxide hydrolase as a therapeutic target for cardiovascular diseases
John D. Imig and Bruce D. Hammock · 2009
Earlier work this paper cites.
The rise of fragment-based drug discovery
Christopher W Murray and David C Rees · 2009
Earlier work this paper cites.
Fragment-based drug discovery applied to Hsp90. Discovery of two lead series with high ligand efficiency
Christopher W Murray, Maria G Carr, Owen Callaghan, Gianni Chessari, Miles Congreve, Suzanna Cowan, Joseph E Coyle, Robert Downham, Eva Figueroa, Martyn Frederickson, et al · 2010
Earlier work this paper cites.
Extended-connectivity fingerprints
David Rogers and Mathew Hahn · 2010
Earlier work this paper cites.
Autodock Vina: improving the speed and accuracy of docking with a new scoring func- tion, efficient optimization, and multithreading
Oleg Trott and Arthur J. Olson · 2010
Earlier work this paper cites.
Discovery of (2, 4-dihydroxy-5-isopropylphenyl)-[5-(4-methylpiperazin-1-ylmethyl)-1, 3-dihydroisoindol-2-yl] methanone (at13387), a novel inhibitor of the molecular chaperone Hsp90 by fragment based drug design
Andrew J Woodhead, Hayley Angove, Maria G Carr, Gianni Chessari, Miles Congreve, Joseph E Coyle, Jose Cosme, Brent Graham, Philip J Day, Robert Downham, et al · 2010
Earlier work this paper cites.
DOGS: reaction-driven de novo design of bioactive
Hartenfeller M, Zettl H, Walter M, Rupp M, Reisen F, Proschak E, Weggen S, Stark H, and Schneider G · 2012
Earlier work this paper cites.
Fast, accurate, and reliable molecular docking with Quickvina 2
A Alhossary, SD Handoko, Y Mu, and CK Kwoh · 2015
Earlier work this paper cites.
Deep reinforcement learning in large discrete action spaces
Gabriel Dulac-Arnold, Richard Evans, Hado van Hasselt, Peter Sunehag, Timothy Lillicrap, Jonathan Hunt, Timothy Mann, Theophane Weber, Thomas Degris, and Ben Coppin · 2015
Earlier work this paper cites.
Neural message passing for quantum chemistry
Justin Gilmer, Samuel S. Schoenholz, Patrick F. Riley, Oriol Vinyals, and George E. Dahl · 2017
Earlier work this paper cites.
Reinforcement learning with deep energy-based policies, 2017
Tuomas Haarnoja, Haoran Tang, Pieter Abbeel, and Sergey Levine · 2017
Earlier work this paper cites.
Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
Earlier work this paper cites.
Generating focused molecule libraries for drug discovery with recurrent neural networks
Marwin H. S. Segler, Thierry Kogej, Christian Tyrchan, and Mark P. Waller · 2017
Earlier work this paper cites.
MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets
Martin Steinegger and Johannes Söding · 2017
Earlier work this paper cites.
Thermometer encoding: One hot way to resist adversarial examples
Jacob Buckman, Aurko Roy, Colin Raffel, and Ian Goodfellow · 2018
Earlier work this paper cites.
Scscore: Synthetic complexity learned from a reaction corpus
Connor W. Coley, Luke Rogers, William H. Green, and Klavs F. Jensen · 2018
Earlier work this paper cites.
Objective-reinforced generative adversarial networks (organ) for sequence generation models
Gabriel Lima Guimaraes, Benjamin Sanchez-Lengeling, Carlos Outeiral, Pedro Luis Cunha Farias, and Alán Aspuru-Guzik · 2018
Earlier work this paper cites.
Generative recurrent networks for de novo drug design
Anvita Gupta, Alex T Müller, Berend JH Huisman, Jens A Fuchs, Petra Schneider, and Gisbert Schneider · 2018
Earlier work this paper cites.
Automatic chemical design using a data-driven continuous representation of molecules
Rafael Gómez-Bombarelli, Jennifer N. Wei, David Duvenaud, José Miguel Hernández-Lobato, Benjamín Sánchez-Lengeling, Dennis Sheberla, Jorge Aguilera-Iparraguirre, Timothy D. Hirzel, Ryan P. Adams, and Alán Aspuru-Guzik · 2018
Earlier work this paper cites.
Junction tree variational autoencoder for molecular graph generation
Wengong Jin, Regina Barzilay, and Tommi Jaakkola · 2018
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Multi-objective de novo drug design with conditional graph generative model
Yibo Li, Liangren Zhang, and Zhenming Liu · 2018
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Planning chemical syntheses with deep neural networks and symbolic ai
Marwin HS Segler, Mike Preuss, and Mark P Waller · 2018
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A model to search for synthesizable molecules
John Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, and José Miguel Hernández-Lobato · 2019
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Automated de novo molecular design by hybrid machine intelligence and rule-driven chemical synthesis
Alexander Button, Daniel Merk, Jan A Hiss, and Schneider Gisbert · 2019
Cited alongside, same era.
Gflownet foundations
Yoshua Bengio, Salem Lahlou, Tristan Deleu, Edward J Hu, Mo Tiwari, and Emmanuel Bengio · 2023
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Open science discovery of potent noncovalent SARS-CoV-2 main protease inhibitors
Melissa L Boby, Daren Fearon, Matteo Ferla, Mihajlo Filep, Lizbé Koekemoer, Matthew C Robinson, COVID Moonshot Consortium‡, John D Chodera, Alpha A Lee, Nir London, et al · 2023
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Generative models should at least be able to design molecules that dock well: A new benchmark
Tobiasz Ciepliński, Tomasz Danel, Sabina Podlewska, and Stanisław Jastrzębski · 2023
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Posecheck: Generative models for 3d structure-based drug design produce unrealistic poses
Charles Harris, Kieran Didi, Arian Jamasb, Chaitanya Joshi, Simon Mathis, Pietro Lio, and Tom Blundell · 2023
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Moksh Jain, Sharath Chandra Raparthy, Alex Hernandez-Garcia, Jarrid Rector-Brooks, Yoshua Bengio, Santiago Miret, and Emmanuel Bengio · 2023
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A graph-based genetic algorithm and generative model/Monte Carlo tree search for the exploration of chemical space
Jan H Jensen · 2019
Cited alongside, same era.
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin, Regina Barzilay, and Tommi Jaakkola · 2019
Cited alongside, same era.
Structure-guided fragment-based drug discovery at the synchrotron: screening binding sites and correlations with hotspot mapping
Sherine E Thomas, Patrick Collins, Rory Hennell James, Vitor Mendes, Sitthivut Charoensutthivarakul, Chris Radoux, Chris Abell, Anthony G Coyne, R Andres Floto, Frank Von Delft, et al · 2019
Cited alongside, same era.
Graph transformer networks
Seongjun Yun, Minbyul Jeong, Raehyun Kim, Jaewoo Kang, and Hyunwoo J Kim · 2019
Cited alongside, same era.
REINVENT 2.0: An ai tool for de novo drug design
Thomas Blaschke, Josep Arús-Pous, Hongming Chen, Christian Margreitter, Christian Tyrchan, Ola Engkvist, Kostas Papadopoulos, and Atanas Patronov · 2020
Cited alongside, same era.
Barking up the right tree: an approach to search over molecule synthesis dags
John Bradshaw, Brooks Paige, Matt J Kusner, Marwin Segler, and José Miguel Hernández-Lobato · 2020
Cited alongside, same era.
The synthesizability of molecules proposed by generative models
Wenhao Gao and Connor W. Coley · 2020
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Pan-kras inhibitor disables oncogenic signalling and tumour growth
Dongsung Kim, Lorenz Herdeis, and Dorothea et al. Rudolph · 2023
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Goal-conditioned GFlowNets for controllable multi-objective molecular design
Julien Roy, Pierre-Luc Bacon, Christopher Pal, and Emmanuel Bengio · 2023
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Critical assessment of synthetic accessibility scores in computer-assisted synthesis planning
Grzegorz Skoraczyński, Mateusz Kitlas, Błażej Miasojedow, and Anna Gambin · 2023
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Fake it until you make it? Generative de novo design and virtual screening of synthesizable molecules
Megan Stanley and Marwin Segler · 2023
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Vina-gpu 2.1: towards further optimizing docking speed and precision of autodock vina and its derivatives
Shidi Tang, Ji Ding, Xiangyu Zhu, Zheng Wang, Haitao Zhao, and Jiansheng Wu · 2023
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The ChEMBL Database in 2023: a drug discovery platform spanning multiple bioactivity data types and time periods
Barbara Zdrazil, Eloy Felix, Fiona Hunter, Emma J Manners, James Blackshaw, Sybilla Corbett, Marleen de Veij, Harris Ioannidis, David Mendez Lopez, Juan F Mosquera, Maria Paula Magarinos, Nicolas Bosc, Ricardo Arcila, Tevfik Kizilören, Anna Gaulton, A Patrícia Bento, Melissa F Adasme, Peter Monecke, Gregory A Landrum, and Andrew R Leach · 2023
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SpaceLight
BioSolveIt · 2024
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Posebusters: AI-based docking methods fail to generate physically valid poses or generalise to novel sequences
Martin Buttenschoen, Garrett M Morris, and Charlotte M Deane · 2024
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Machine learning-aided generative molecular design
Yuanqi Du, Arian R Jamasb, Jeff Guo, Tianfan Fu, Charles Harris, Yingheng Wang, Chenru Duan, Pietro Liò, Philippe Schwaller, and Tom L Blundell · 2024
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Jeff Guo and Philippe Schwaller · 2024
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Pessimistic backward policy for gflownets
Hyosoon Jang, Yunhui Jang, Minsu Kim, Jinkyoo Park, and Sungsoo Ahn · 2024
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Efficient clustering of large molecular libraries
Vicky Jung, Kenneth Lopez Perez, Lexin Chen, Kate Huddleston, and Ramon Alain Miranda Quintana · 2024
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Thompson sampling–an efficient method for searching ultralarge synthesis on demand databases
Kathryn Klarich, Brian Goldman, Trevor Kramer, Patrick Riley, and W. Patrick Walters · 2024
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RGFN: Synthesizable molecular generation using GFlowNets
Michał Koziarski, Andrei Rekesh, Dmytro Shevchuk, Almer van der Sloot, Piotr Gaiński, Yoshua Bengio, Cheng-Hao Liu, Mike Tyers, and Robert A Batey · 2024
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Reinvent 4: Modern AI–driven generative molecule design
Hannes H. Loeffler, Jiazhen He, Alessandro Tibo, Jon Paul Janet, Alexey Voronov, Lewis H. Mervin, and Ola Engkvist · 2024
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Projecting molecules into synthesizable chemical spaces, 2024
Shitong Luo, Wenhao Gao, Zuofan Wu, Jian Peng, Connor W. Coley, and Jianzhu Ma · 2024
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Maximum entropy GFlowNets with soft Q-learning, 2024
Sobhan Mohammadpour, Emmanuel Bengio, Emma Frejinger, and Pierre-Luc Bacon · 2024
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Generative ai for designing and validating easily synthesizable and structurally novel antibiotics
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Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation
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