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RESEARCH PAPER · Journal of Medicinal Chemistry · 2020

“Ring Breaker”: Neural Network Driven Synthesis Prediction of the Ring System Chemical Space

Amol Thakkar, Nidhal Selmi, Jean‐Louis Reymond, Ola Engkvist, Esben Jannik Bjerrum

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“Ring Breaker”: Neural Network Driven Synthesis Prediction of the Ring System Chemical SpaceOriginalAiZynthFinder: A Fast Robust and Flexible Open-Source Software for Retrosynthetic Planning27Data Augmentation and Pretraining for Template-Based Retrosynthetic Prediction in Computer-Aided Synthesis Planning82Artificial intelligence and automation in computer aided synthesis planning88AiZynthFinder: a fast, robust and flexible open-source software for retrosynthetic planning378Artificial applicability labels for improving policies in retrosynthesis prediction5FragNet, a Contrastive Learning-Based Transformer Model for Clustering, Interpreting, Visualizing, and Navigating Chemical Space24Machine learning techniques applied to the drug design and discovery of new antivirals: a brief look over the past decade37Report on an NIH Workshop on Ultralarge Chemistry Databases23Report on an NIH Workshop on Ultralarge Chemistry Databases9Artificial Intelligence, Machine Learning, and Deep Learning in Real-Life Drug Design Cases37The roles of computer-aided drug synthesis in drug development29Ai's Assistance in Amplifying the Competence of Chemists0Ring systems in natural products: structural diversity, physicochemical properties, and coverage by synthetic compounds106Machine intelligence for chemical reaction space124Machine Learning in Chemoinformatics and Medicinal Chemistry47Benchmark of general-purpose machine learning-based quantum mechanical method AIQM1 on reaction barrier heights24Machine Learning in Drug Design6AiZynthTrain: Robust, Reproducible, and Extensible Pipelines for Training Synthesis Prediction Models30Data Sharing in Chemistry: Lessons Learned and a Case for Mandating Structured Reaction Data45Unbiasing Retrosynthesis Language Models with Disconnection Prompts39Augmenting DMTA using predictive AI modelling at AstraZeneca43Transfer learning for Heterocycle Synthesis Prediction0Augmenting large language models with chemistry tools762AiZynthFinder 4.0: developments based on learnings from 3 years of industrial application56Artificial Intelligence Methods and Models for Retro-Biosynthesis: A Scoping Review59Monte-Carlo tree search applied to structure generation0Advancements in Machine Learning Predicting Activation and Gibbs Free Energies in Chemical Reactions2Exploring Simple Drug Scaffolds from the Generated Database Chemical Space Reveals a Chiral Bicyclic Azepane with Potent Neuropharmacology13ASKCOS: Open-Source, Data-Driven Synthesis Planning77Enhancing Monte Carlo Tree Search for Retrosynthesis2Transfer Learning for Heterocycle Retrosynthesis3Consensus Prediction of Chemical Reactions with OCHEM-R Platform1Rethinking Retrosynthesis: Curriculum Learning Reshapes Transformer-Based Small-Molecule Reaction Prediction5Artificial intelligence in renewable energy technologies and sustainable transition0AI in Retrosynthesis: Introduction, Methods, Evaluation, and Future Directions0Big Data for Drug Discovery: Some Historical Landscape, Considerations, and Applications for a Medicinal Chemist1Mathematical concepts for representation of ligand permutation, stereochemistry, and bonding and integration with AI/ML: Application to ATP synthesis/hydrolysis0SynOmega: Simplifying Retrosynthesis for Efficient Synthesizability Scoring0

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  1. AiZynthFinder: A Fast Robust and Flexible Open-Source Software for Retrosynthetic Planning

    ChemRxiv · 2020-06-15

    Samuel Genheden, Amol Thakkar, Veronika Chadimová, Jean‐Louis Reymond, Ola Engkvist, Esben Jannik Bjerrum

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  2. Data Augmentation and Pretraining for Template-Based Retrosynthetic Prediction in Computer-Aided Synthesis Planning

    Journal of Chemical Information and Modeling · 2020-06-22

    Michael William-Patrick Fortunato, Connor W. Coley, Brian C. Barnes, Klavs F. Jensen

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  3. Artificial intelligence and automation in computer aided synthesis planning

    Reaction Chemistry & Engineering · 2020-11-05

    Amol Thakkar, Simon Johansson, Kjell Jorner, David Buttar, Jean‐Louis Reymond, Ola Engkvist

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  4. AiZynthFinder: a fast, robust and flexible open-source software for retrosynthetic planning

    Journal of Cheminformatics · 2020-11-17

    Samuel Genheden, Amol Thakkar, Veronika Chadimová, Jean‐Louis Reymond, Ola Engkvist, Esben Jannik Bjerrum

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  5. Artificial applicability labels for improving policies in retrosynthesis prediction

    Machine Learning Science and Technology · 2020-12-01

    Esben Jannik Bjerrum, Amol Thakkar, Ola Engkvist

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  6. FragNet, a Contrastive Learning-Based Transformer Model for Clustering, Interpreting, Visualizing, and Navigating Chemical Space

    Molecules · 2021-04-03

    Aditya Divyakant Shrivastava, Douglas Bruce Kell

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  7. Machine learning techniques applied to the drug design and discovery of new antivirals: a brief look over the past decade

    Expert Opinion on Drug Discovery · 2021-05-07

    Mateus Sá Magalhães Serafim, Valtair Severino dos Santos, Jadson Castro Gertrudes, Vinícius Gonçalves Maltarollo, Kathia Maria Honorio

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  8. Report on an NIH Workshop on Ultralarge Chemistry Databases

    ChemRxiv · 2021-05-10

    Wendy A. Warr

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  9. Report on an NIH Workshop on Ultralarge Chemistry Databases

    ChemRxiv · 2021-05-10

    Wendy A. Warr

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  10. Artificial Intelligence, Machine Learning, and Deep Learning in Real-Life Drug Design Cases

    Methods in molecular biology · 2021-11-03

    Christophe Müller, Obdulia Rabal, Constantino Diaz Gonzalez

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  11. The roles of computer-aided drug synthesis in drug development

    Green Synthesis and Catalysis · 2021-11-30

    Pengfei Jia, Junping Pei, Guan Wang, Xiaoli Pan, Yumeng Zhu, Yong Wu, Liang Ouyang

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  12. Ai's Assistance in Amplifying the Competence of Chemists

    SSRN Electronic Journal · 2022-01-01

    Shruti Goel, Mihir Khulbe, Reena Sharma, Abha Kathuria

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  13. Ring systems in natural products: structural diversity, physicochemical properties, and coverage by synthetic compounds

    Natural Product Reports · 2022-01-01

    Ya Chen, Cara Rosenkranz, Steffen Hirte, Johannes Kirchmair

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  14. Machine intelligence for chemical reaction space

    Wiley Interdisciplinary Reviews Computational Molecular Science · 2022-03-07

    Philippe Schwaller, Alain C. Vaucher, Rubén Laplaza, Charlotte Bunne, Andreas Krause, Clémence Corminbœuf, Teodoro Laino

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  15. Machine Learning in Chemoinformatics and Medicinal Chemistry

    Annual Review of Biomedical Data Science · 2022-04-19

    Raquel Rodríguez-Pérez, Filip N. Miljković, Jürgen Bajorath

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  16. Benchmark of general-purpose machine learning-based quantum mechanical method AIQM1 on reaction barrier heights

    The Journal of Chemical Physics · 2023-01-30

    Yuxinxin Chen, Yanchi Ou, Peikun Zheng, Yaohuang Huang, Fuchun Ge, Pavlo O. Dral

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  17. Machine Learning in Drug Design

    Royal Society of Chemistry eBooks · 2023-02-03

    Ola Engkvist, Lewis Mervin, Hongming Chen, Ting Ran

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  18. AiZynthTrain: Robust, Reproducible, and Extensible Pipelines for Training Synthesis Prediction Models

    Journal of Chemical Information and Modeling · 2023-03-24

    Samuel Genheden, Per‐Ola Norrby, Ola Engkvist

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  19. Data Sharing in Chemistry: Lessons Learned and a Case for Mandating Structured Reaction Data

    Journal of Chemical Information and Modeling · 2023-07-05

    Rocío Mercado, Steven M. Kearnes, Connor W. Coley

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  20. Unbiasing Retrosynthesis Language Models with Disconnection Prompts

    ACS Central Science · 2023-07-05

    Amol Thakkar, Alain C. Vaucher, Andrea Byekwaso, Philippe Schwaller, Alessandra Toniato, Teodoro Laino

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  21. Augmenting DMTA using predictive AI modelling at AstraZeneca

    Drug Discovery Today · 2024-03-08

    Gian Marco Ghiandoni, Emma Evertsson, David J. Riley, Christian Tyrchan, Prakash Chandra Rathi

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  22. Transfer learning for Heterocycle Synthesis Prediction

    ChemRxiv · 2024-05-05

    Ewa Wieczorek, Joshua W. Sin, Matthew T. O. Holland, Liam Wilbraham, Victor S. Perez, Anthony R Bradley, Dominik Miketa, Paul E. Brennan, Fernanda Duarte

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  23. Augmenting large language models with chemistry tools

    Nature Machine Intelligence · 2024-05-08

    Andres M Bran, Sam Cox, Oliver Tobias Schilter, Carlo Baldassari, Andrew Dickson White, Philippe Schwaller

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  24. AiZynthFinder 4.0: developments based on learnings from 3 years of industrial application

    Journal of Cheminformatics · 2024-05-23

    Lakshidaa Saigiridharan, Alan Kai Hassen, Helen Lai, Paula Torren-Peraire, Ola Engkvist, Samuel Genheden

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  25. Artificial Intelligence Methods and Models for Retro-Biosynthesis: A Scoping Review

    ACS Synthetic Biology · 2024-07-24

    Guillaume Gricourt, Philippe Meyer, Thomas Duigou, Jean‐Loup Faulon

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  26. Monte-Carlo tree search applied to structure generation

    Unknown journal · 2024-12-13

    Milo Roucairol

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  27. Advancements in Machine Learning Predicting Activation and Gibbs Free Energies in Chemical Reactions

    International Journal of Quantum Chemistry · 2025-03-19

    Guo‐Jin Cao

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  28. Exploring Simple Drug Scaffolds from the Generated Database Chemical Space Reveals a Chiral Bicyclic Azepane with Potent Neuropharmacology

    Journal of Medicinal Chemistry · 2025-04-24

    Aline Lucie Carrel, Adonis Yiannakas, Jaap-Jan Roukens, Inés Reynoso-Moreno, Markus Orsi, Amol Thakkar, Josep Arús‐Pous, Daniele Pellegata, Jürg Gertsch, Jean‐Louis Reymond

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  29. ASKCOS: Open-Source, Data-Driven Synthesis Planning

    Accounts of Chemical Research · 2025-05-21

    Zhengkai Tu, Sourabh J. Choure, Mun Hong Fong, Jihye Roh, Itai Levin, Kevin Yu, Joonyoung F. Joung, Nathan N. Morgan, Shih‐Cheng Li, Xiaoqi Sun, Huiqian Lin, Mark Murnin, Jordan P. Liles, Thomas J. Struble, Michael William-Patrick Fortunato, Mengjie Liu, William H. Green, Klavs F. Jensen, Connor W. Coley

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  30. Enhancing Monte Carlo Tree Search for Retrosynthesis

    Journal of Chemical Information and Modeling · 2025-06-13

    Ton M. Blackshaw, Joseph C. Davies, Kristian Spoerer, Jonathan D. Hirst

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  31. Transfer Learning for Heterocycle Retrosynthesis

    Journal of Chemical Information and Modeling · 2025-07-29

    Ewa Wieczorek, Joshua W. Sin, Sara Tanovic, Matthew T. O. Holland, Liam Wilbraham, Víctor Sebastián-Pérez, Anthony R Bradley, Dominik Miketa, Paul E. Brennan, Fernanda Duarte

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  32. Consensus Prediction of Chemical Reactions with OCHEM-R Platform

    Lecture notes in computer science · 2025-09-22

    Igor V. Tetko, Guillaume Godin, Kevin Maik Jablonka, Adrian Mirza, Luc Patiny

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  33. Rethinking Retrosynthesis: Curriculum Learning Reshapes Transformer-Based Small-Molecule Reaction Prediction

    Journal of Chemical Information and Modeling · 2025-09-26

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  34. Artificial intelligence in renewable energy technologies and sustainable transition

    Elsevier eBooks · 2025-12-05

    Bilal Fareed, Ljubinka Vasić, Farooq Sher, Nicolás M. Clauser, Madjid Soltani, Maria Veronica Sofianos

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  35. AI in Retrosynthesis: Introduction, Methods, Evaluation, and Future Directions

    Springer eBooks · 2026-01-01

    Ruchi Bharti, Ajay Thakur, Uma Koul, Monika Verma, Renu Sharma

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  36. Big Data for Drug Discovery: Some Historical Landscape, Considerations, and Applications for a Medicinal Chemist

    ACS Omega · 2026-01-26

    João A. L. de Lima, Lucas Silva Franco, Lı́dia Moreira Lima

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  37. Mathematical concepts for representation of ligand permutation, stereochemistry, and bonding and integration with AI/ML: Application to ATP synthesis/hydrolysis

    Inorganica Chimica Acta · 2026-08-03

    Sunil Nath

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  38. SynOmega: Simplifying Retrosynthesis for Efficient Synthesizability Scoring

    Journal of Chemical Information and Modeling · 2026-09-08

    Baicheng Zhang, Guoqing Zhang, Jun Jiang, Yi Luo

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