The Chemical Space Project

Reymond, Jean-Louis·2015·Accounts of Chemical Research

Cited by (715)

Items 101–200 of 715

  1. Fragment Database FDB-17
    Ricardo Visini, Mahendra Awale, Jean‐Louis Reymond · 2017 · Journal of Chemical Information and Modeling
  2. Integrated Molecular Modeling and Machine Learning for Drug Design
    Song Xia, Eric Chen, Yingkai Zhang · 2023 · Journal of Chemical Theory and Computation
  3. Applied Machine Learning for Developing Next‐Generation Functional Materials
    Filip Dinic, Kamalpreet Singh, Tony Dong, Milad Rezazadeh, Zhibo Wang, Ali Khosrozadeh, Tiange Yuan, Oleksandr Voznyy · 2021 · Advanced Functional Materials
  4. A hybrid modelling approach to compare chemical separation technologies in terms of energy consumption and carbon dioxide emissions
    Gergő Ignácz, Áron Kristóf Beke, Viktor Tóth, György Székely · 2024 · Nature Energy
  5. Machine Learning and Deep Learning in Data-Driven Decision Making of Drug Discovery and Challenges in High-Quality Data Acquisition in the Pharmaceutical Industry
    Sethu Arun Kumar, Thirumoorthy Durai Ananda Kumar, Narasimha Murthy Beeraka, Gurubasavaraj V. Pujar, Manisha Singh, H.S. Akshatha, Meduri Bhagyalalitha · 2021 · Future Medicinal Chemistry
  6. Virtual Compound Libraries in Computer-Assisted Drug Discovery
    Niek van Hilten, Florent Chevillard, Peter Kolb · 2019 · Journal of Chemical Information and Modeling
  7. Fragment Hits: What do They Look Like and How do They Bind?
    Fabrizio Giordanetto, Chentian Jin, Lindsay Willmore, Miklós Fehér, David Elliot Shaw · 2019 · Journal of Medicinal Chemistry
  8. Connecting chemistry and biology through molecular descriptors
    Adrià Fernández‐Torras, Arnau Comajuncosa-Creus, Miquel Duran‐Frigola, Patrick Aloy · 2021 · Current Opinion in Chemical Biology
  9. Neural multi-task learning in drug design
    Stephan Allenspach, Jan A. Hiss, Gisbert Schneider · 2024 · Nature Machine Intelligence
  10. Converging a Knowledge-Based Scoring Function: DrugScore2018
    Jonas Dittrich, Denis Schmidt, Christopher Pfleger, Holger Gohlke · 2018 · Journal of Chemical Information and Modeling
  11. Using Physicochemical Measurements to Influence Better Compound Design
    Shenaz B. Bunally, Christopher N. Luscombe, Robert J. Young · 2019 · SLAS DISCOVERY
  12. Drug Discovery Maps, a Machine Learning Model That Visualizes and Predicts Kinome–Inhibitor Interaction Landscapes
    Antonius P. A. Janssen, Sebastian H. Grimm, Ruud H. M. Wijdeven, Eelke Bart Lenselink, Jacques Neefjes, Constant A. A. van Boeckel, Gerard J. P. van Westen, Mario van der Stelt · 2018 · Journal of Chemical Information and Modeling
  13. Progress on open chemoinformatic tools for expanding and exploring the chemical space
    José L. Medina‐Franco, Norberto Sánchez‐Cruz, Edgar López‐López, Bárbara I. Díaz‐Eufracio · 2021 · Journal of Computer-Aided Molecular Design
  14. Artificial intelligence and machine learning for targeted energy storage solutions
    Dean H. Barrett, Aderemi Bashiru Haruna · 2020 · Current Opinion in Electrochemistry
  15. Rapid discovery of stable materials by coordinate-free coarse graining
    Rhys E. A. Goodall, Abhijith S. Parackal, Felix A. Faber, Rickard Armiento, Alpha A. Lee · 2022 · Science Advances
  16. Invalid SMILES are beneficial rather than detrimental to chemical language models
    Michael A. Skinnider · 2024 · Nature Machine Intelligence
  17. Molecular complexity as a driving force for the advancement of organic synthesis
    Brandon A. Wright, Richmond Sarpong · 2024 · Nature Reviews Chemistry
  18. Autonomous Reaction Network Exploration in Homogeneous and Heterogeneous Catalysis
    Miguel Steiner, Markus Reiher · 2022 · Topics in Catalysis
  19. Soft Matter Informatics: Current Progress and Challenges
    James S. Peerless, Nina J. B. Milliken, Thomas J. Oweida, Matthew D. Manning, Yaroslava G. Yingling · 2018 · Advanced Theory and Simulations
  20. PubChem and ChEMBL beyond Lipinski
    Alice Capecchi, Mahendra Awale, Daniel Probst, Jean‐Louis Reymond · 2019 · Molecular Informatics
  21. ChEMBL-Likeness Score and Database GDBChEMBL
    Sven Bühlmann, Jean‐Louis Reymond · 2020 · Frontiers in Chemistry
  22. Synthetic Strategies for 5- and 6-Membered Ring Azaheterocycles Facilitated by Iminyl Radicals
    John C. Walton · 2016 · Molecules
  23. ACCDB: A collection of chemistry databases for broad computational purposes
    Pierpaolo Morgante, Roberto Peverati · 2018 · Journal of Computational Chemistry
  24. Artificial Intelligence in Small-Molecule Drug Discovery: A Critical Review of Methods, Applications, and Real-World Outcomes
    Niazi, Sarfaraz K. · 2025 · Pharmaceuticals
  25. In silico design of low molecular weight protein–protein interaction inhibitors: Overall concept and recent advances
    Mélaine A. Kuenemann, Olivier Spérandio, Céline M. Labbé, David Lagorce, Maria A. Miteva, Bruno O. Villoutreix · 2015 · Progress in Biophysics and Molecular Biology
  26. Finding Constellations in Chemical Space Through Core Analysis
    J. Jesús Naveja, José L. Medina‐Franco · 2019 · Frontiers in Chemistry
  27. Supramolecular Oligothiophene Microfibers Spontaneously Assembled on Surfaces or Coassembled with Proteins inside Live Cells
    Giovanna Barbarella, Francesca Di Maria · 2015 · Accounts of Chemical Research
  28. A Photoaffinity‐Based Fragment‐Screening Platform for Efficient Identification of Protein Ligands
    Emma K. Grant, David J. Fallon, Michael M. Hann, Ken G. M. Fantom, Chad J. Quinn, Francesca Zappacosta, Roland S. Annan, Chun‐wa Chung, Paul Bamborough, David P. Dixon et al. · 2020 · Angewandte Chemie International Edition
  29. Computational discovery of energy materials in the era of big data and machine learning: A critical review
    Ziheng Lu · 2021 · Materials Reports Energy
  30. Chemical space guided discovery of antimicrobial bridged bicyclic peptides against Pseudomonas aeruginosa and its biofilms
    Ivan Di Bonaventura, Xian Jin, Ricardo Visini, Daniel Probst, Sacha Javor, Bee‐Ha Gan, Gaëlle Michaud, Antonino Natalello, Silvia Maria Doglia, Thilo Köhler et al. · 2017 · Chemical Science
  31. Cheminformatics in Drug Discovery, an Industrial Perspective
    Hongming Chen, Thierry Kogej, Ola Engkvist · 2018 · Molecular Informatics
  32. Applications of Deep-Learning in Exploiting Large-Scale and Heterogeneous Compound Data in Industrial Pharmaceutical Research
    Laurianne David, Josep Arús‐Pous, Johan Karlsson, Ola Engkvist, Esben Jannik Bjerrum, Thierry Kogej, Jan M. Kriegl, Bernd Beck, Hongming Chen · 2019 · Frontiers in Pharmacology
  33. PerturbNet predicts single-cell responses to unseen chemical and genetic perturbations
    Yu, Hengshi, Qian, Weizhou, Song, Yuxuan, Welch, Joshua D · 2025 · Molecular Systems Biology
  34. Deep Learning-Assisted Spectrum–Structure Correlation: State-of-the-Art and Perspectives
    Xinyu Lu, Hao-ping Wu, Hao Ma, Hui Li, Jia Zhao Li, Yan-Ti Liu, Zheng-Yan Pan, Yi Xie, Lei Wang, Bin W. Ren et al. · 2024 · Analytical Chemistry
  35. Synthesis of Fluorescent Indazoles by Palladium-Catalyzed Benzannulation of Pyrazoles with Alkynes
    Og Soon Kim, Jin Hyeok Jang, Hyun Tae Kim, Su Jin Han, Gavin Chit Tsui, Jung Min Joo · 2017 · Organic Letters
  36. Grand Challenges of Computer-Aided Drug Design: The Road Ahead
    José L. Medina‐Franco · 2021 · Frontiers in Drug Discovery
  37. Deep learning and generative methods in cheminformatics and chemical biology: navigating small molecule space intelligently
    Douglas Bruce Kell, Soumitra Samanta, Neil Swainston · 2020 · Biochemical Journal
  38. DNA‐Encoded Libraries: Towards Harnessing their Full Power with Darwinian Evolution
    Millicent Dockerill, Nicolas Winssinger · 2022 · Angewandte Chemie International Edition
  39. Machine learning-inspired battery material innovation
    Man‐Fai Ng, Yongming Sun, Zhi Wei Seh · 2023 · Energy Advances
  40. Sample efficient reinforcement learning with active learning for molecular design
    Michael Dodds, Jeff Guo, Thomas Löhr, Alessandro Tibo, Ola Engkvist, Jon Paul Janet · 2024 · Chemical Science
  41. Current and promising novel drug candidates against visceral leishmaniasis
    Rosa Maria Reguera, Yolanda Pérez‐Pertejo, Camino Gutiérrez-Corbo, Bárbara Domínguez-Asenjo, César Ordóñez, Carlos García‐Estrada, María Martínez Valladares, Rafael Balaña‐Fouce · 2019 · Pure and Applied Chemistry
  42. Recent progress on cheminformatics approaches to epigenetic drug discovery
    Zoe L. Sessions, Norberto Sánchez‐Cruz, Fernando Daniel Prieto-Martínez, Vinícius M. Alves, Hudson Pires de Oliveira Santos Junior, Eugene N. Muratov, Alexander Tropsha, José L. Medina‐Franco · 2020 · Drug Discovery Today
  43. De novodrug design by iterative multiobjective deep reinforcement learning with graph-based molecular quality assessment
    Yi Fang, Xiaoyong Pan, Hong‐Bin Shen · 2023 · Bioinformatics
  44. Recent advances from computer-aided drug design to artificial intelligence drug design
    Keran Wang, Yanwen Huang, Yan Wang, Qidong You, Lei Wang · 2024 · RSC Medicinal Chemistry
  45. Why big data and compute are not necessarily the path to big materials science
    Naohiro Fujinuma, Brian DeCost, Jason R. Hattrick-Simpers, S. E. Lofland · 2022 · Communications Materials
  46. Materials space of solid-state electrolytes: unraveling chemical composition–structure–ionic conductivity relationships in garnet-type metal oxides using cheminformatics virtual screening approaches
    Natalia V. Kireeva, Vladislav S. Pervov · 2017 · Physical Chemistry Chemical Physics
  47. Open chemoinformatic resources to explore the structure, properties and chemical space of molecules
    Mariana González-Medina, J. Jesús Naveja, Norberto Sánchez‐Cruz, José L. Medina‐Franco · 2017 · RSC Advances
  48. An approach towards enhancement of a screening library: The Next Generation Library Initiative (NGLI) at Bayer — against all odds?
    Markus Follmann, Hans Briem, Andreas Steinmeyer, Alexander Hillisch, Monika H. Schmitt, Helmut Haning, Heinrich Meier · 2018 · Drug Discovery Today
  49. Algorithm selection for protein–ligand docking: strategies and analysis on ACE
    Tianlai Chen, Xiwen Shu, Huiyuan Zhou, Floyd A. Beckford, Mustafa Mısır · 2023 · Scientific Reports
  50. Advancing algorithmic drug product development: Recommendations for machine learning approaches in drug formulation
    Jack D. Murray, Justus Johann Lange, Harriet Bennett-Lenane, René Holm, Martin Kuentz, P J O’Dwyer, Brendan T. Griffin · 2023 · European Journal of Pharmaceutical Sciences
  51. Applying statistical modeling strategies to sparse datasets in synthetic chemistry
    Brittany C. Haas, Dipannita Kalyani, Matthew S. Sigman · 2025 · Science Advances
  52. Generalizing arene C–H alkylations by radical–radical cross-coupling
    Johannes J. Großkopf, Chawanansaya Gopatta, Robert T. Martin, Alexander Haseloer, David W. C. MacMillan · 2025 · Nature
  53. Learning molecular potentials with neural networks
    Hatice Gökcan, Olexandr Isayev · 2021 · Wiley Interdisciplinary Reviews Computational Molecular Science
  54. A scoping review of artificial intelligence applications in clinical trial risk assessment
    Douglas Teodoro, Nona Naderi, Anthony Yazdani, Boya Zhang, Alban Bornet · 2025 · npj Digital Medicine
  55. Improved accuracy and transferability of molecular-orbital-based machine learning: Organics, transition-metal complexes, non-covalent interactions, and transition states
    Tamara Husch, Jiace Sun, Lixue Cheng, Sebastian J. R. Lee, Thomas F. Miller · 2021 · The Journal of Chemical Physics
  56. MoleGuLAR: Molecule Generation Using Reinforcement Learning with Alternating Rewards
    Manan Goel, Shampa Raghunathan, Siddhartha Laghuvarapu, U. Deva Priyakumar · 2021 · Journal of Chemical Information and Modeling
  57. GEN: highly efficient SMILES explorer using autodidactic generative examination networks
    Ruud van Deursen, Peter Ertl, Igor V. Tetko, Guillaume Godin · 2020 · Journal of Cheminformatics
  58. DrugSpaceX: a large screenable and synthetically tractable database extending drug space
    Tianbiao Yang, Zhaojun Steven Li, Yingjia Chen, Dan Feng, Guangchao Wang, Zunyun Fu, Xiaoyu Ding, Xiaoqin Tan, Jihui Zhao, Xiaomin Luo et al. · 2020 · Nucleic Acids Research
  59. Exploring and mapping chemical space with molecular assembly trees
    Yu Liu, Cole Mathis, Michał Dariusz Bajczyk, Stuart M. Marshall, Liam Wilbraham, Leroy Cronin · 2021 · Science Advances
  60. Fake it until you make it? Generative de novo design and virtual screening of synthesizable molecules
    Megan Stanley, Marwin Segler · 2023 · Current Opinion in Structural Biology
  61. Chemistry must respond to the crisis of transgression of planetary boundaries
    Stephen A. Matlin, Sarah Cornell, Alain Krief, Henning Hopf, Goverdhan Mehta · 2022 · Chemical Science
  62. From Molecular Descriptors to Intrinsic Fish Toxicity of Chemicals: An Alternative Approach to Chemical Prioritization
    Saer Samanipour, Jake William O'Brien, Malcolm J. Reid, Kevin Victor Thomas, Antonia Praetorius · 2022 · Environmental Science & Technology
  63. Exploring the Chemical Space of the Exposome: How Far Have We Gone?
    Saer Samanipour, Leon Barron, Denice van Herwerden, Antonia Praetorius, Kevin Victor Thomas, Jake William O'Brien · 2024 · JACS Au
  64. Modeling protein–ligand interactions for drug discovery in the era of deep learning
    Y.X. Wang, Yibo Li, Jiaxiao Chen, Luhua Lai · 2025 · Chemical Society Reviews
  65. Virtual Exploration of the Ring Systems Chemical Universe
    Ricardo Visini, Josep Arús‐Pous, Mahendra Awale, Jean‐Louis Reymond · 2017 · Journal of Chemical Information and Modeling
  66. Pattern Generation and Information Transfer through a Liquid/Liquid Interface in 3D Constitutional Dynamic Networks of Imine Ligands in Response to Metal Cation Effectors
    Artem Osypenko, Sébastien Dhers, Jean‐Maríe Lehn · 2019 · Journal of the American Chemical Society
  67. Exploring Chemical and Biological Space of Terpenoids
    Tao Zeng, Zhihong Liu, Huawei Liu, Wengan He, Xiaowen Tang, Liwei Xie, Ruibo Wu · 2019 · Journal of Chemical Information and Modeling
  68. Molecular generation targeting desired electronic properties via deep generative models
    Qi Yuan, Alejandro Santana‐Bonilla, Martijn A. Zwijnenburg, Kim E. Jelfs · 2020 · Nanoscale
  69. How predictive could alchemical derivatives be?
    Macarena Muñoz, Carlos Cárdenas · 2017 · Physical Chemistry Chemical Physics
  70. The multidimensional brain
    Arturo Tozzi · 2019 · Physics of Life Reviews
  71. PDB-Explorer: a web-based interactive map of the protein data bank in shape space
    Xian Jin, Mahendra Awale, Michaël Zasso, Daniel Kostro, Luc Patiny, Jean‐Louis Reymond · 2015 · BMC Bioinformatics
  72. Artificial Intelligence-Guided De Novo Molecular Design Targeting COVID-19
    Srilok Srinivasan, Rohit Batra, Henry Chan, Ganesh Kamath, Mathew J. Cherukara, Subramanian K. R. S. Sankaranarayanan · 2021 · ACS Omega
  73. Graph-based molecular Pareto optimisation
    Jonas Verhellen · 2022 · Chemical Science
  74. The future of machine learning for small-molecule drug discovery will be driven by data
    Guy Durant, Fergus Boyles, Kristian Birchall, Charlotte Mary Deane · 2024 · Nature Computational Science
  75. NeuralNEB—neural networks can find reaction paths fast
    Mathias Schreiner, Arghya Bhowmik, Tejs Vegge, Peter Bjørn Jørgensen, Ole Winther · 2022 · Machine Learning Science and Technology
  76. A graph-based approach to construct target-focused libraries for virtual screening
    Misagh Naderi, Chris Alvin, Yun Ding, Supratik Mukhopadhyay, Michał Bryliński · 2016 · Journal of Cheminformatics
  77. A brief guide to machine learning for antibiotic discovery
    Gary Liu, Jonathan M Stokes · 2022 · Current Opinion in Microbiology
  78. Populating Chemical Space with Peptides Using a Genetic Algorithm
    Alice Capecchi, Alain Zhang, Jean‐Louis Reymond · 2019 · Journal of Chemical Information and Modeling
  79. Predicting Molecular Energy Using Force-Field Optimized Geometries and Atomic Vector Representations Learned from an Improved Deep Tensor Neural Network
    Jianing Lu, Cheng Wang, Yingkai Zhang · 2019 · Journal of Chemical Theory and Computation
  80. Use of QSAR Global Models and Molecular Docking for Developing New Inhibitors of c-src Tyrosine Kinase
    Robert Ancuceanu, Bogdan-Ionel Tamba, Cristina Silvia Stoicescu, Mihaela Dinu · 2019 · International Journal of Molecular Sciences
  81. SAR by Space: Enriching Hit Sets from the Chemical Space
    Franca‐Maria Klingler, Marcus Gastreich, Oleksandr O. Grygorenko, Olena Savych, Petro Borysko, Anastasia Griniukova, K.E. Gubina, Christian Lemmen, Yurii S. Moroz · 2019 · Molecules
  82. Forty years of combinatorial technology
    Árpád Furka · 2022 · Drug Discovery Today
  83. Recent advances and applications of machine learning in electrocatalysis
    You Hu, Junhua Chen, Zheng Xi Wei, Qiu He, Yan Zhao · 2023 · Journal of Materials Informatics
  84. Improved understanding of aqueous solubility modeling through topological data analysis
    Mariam Pirashvili, Lee Steinberg, Francisco Belchi Guillamon, Mahesan Niranjan, Jeremy Graham Frey, Jacek Brodzki · 2018 · Journal of Cheminformatics
  85. Diversity and Chemical Library Networks of Large Data Sets
    Timothy B. Dunn, Gustavo de Miranda Seabra, Taewon David Kim, K. Eurídice Juárez‐Mercado, Chenglong Li, José L. Medina‐Franco, Ramón Alain Miranda‐Quintana · 2021 · Journal of Chemical Information and Modeling
  86. Artificial Intelligence, Machine Learning, and Deep Learning in Real-Life Drug Design Cases
    Christophe Müller, Obdulia Rabal, Constantino Diaz Gonzalez · 2021 · Methods in molecular biology
  87. OSCAR: an extensive repository of chemically and functionally diverse organocatalysts
    Simone Gallarati, Puck van Gerwen, Rubén Laplaza, Sergi Vela, Alberto Fabrizio, Clémence Corminbœuf · 2022 · Chemical Science
  88. Reaching for the bright StARs in chemical space
    José L. Medina‐Franco, J. Jesús Naveja, Edgar López‐López · 2019 · Drug Discovery Today
  89. Discovery and characterization of a novel non-competitive inhibitor of the divalent metal transporter DMT1/SLC11A2
    Nicolás Montalbetti, Alexandre Simonin, Céline Simonin, Mahendra Awale, Jean‐Louis Reymond, Matthias A. Hediger · 2015 · Biochemical Pharmacology
  90. Photogeneration of α-Bimetalloid Radicals via Selective Activation of Multifunctional C1 Units
    Lewis McGhie, Alessandro Marotta, Patrick O. Loftus, Peter H. Seeberger, Ignacio Funes‐Ardoiz, John J. Molloy · 2024 · Journal of the American Chemical Society
  91. Hydration free energies from kernel-based machine learning: Compound-database bias
    Clemens Rauer, Tristan Bereau · 2020 · The Journal of Chemical Physics
  92. Computergestützte Syntheseplanung: Das Ende vom Anfang
    Sara Szymkuć, Ewa P. Gajewska, Tomasz Klucznik, Karol Molga, Piotr Dittwald, Michał Piotr Startek, Michał Dariusz Bajczyk, Bartosz A. Grzybowski · 2016 · Angewandte Chemie
  93. One Drug for Multiple Targets: A Computational Perspective
    Oscar Méndez‐Lucio, J. Jesús Naveja, Hugo Vite‐Caritino, Fernando Daniel Prieto-Martínez, José L. Medina‐Franco · 2017 · Journal of the Mexican Chemical Society
  94. An antimicrobial bicyclic peptide from chemical space against multidrug resistant Gram-negative bacteria
    Ivan Di Bonaventura, S. Baeriswyl, Alice Capecchi, Bee‐Ha Gan, Xian Jin, Thissa N. Siriwardena, Runze He, Thilo Köhler, Arianna Pompilio, Giovanni Di Bonaventura et al. · 2018 · Chemical Communications
  95. Challenges in the design of formulated products: multiscale process and product design
    Manuel R. Taifouris, Mariano Martı́n, Alberto Martínez, Nats Esquejo · 2019 · Current Opinion in Chemical Engineering
  96. Free Energy Calculations for Protein–Ligand Binding Prediction
    Willem Jespers, Johan Åqvist, Hugo Gutiérrez‐de‐Terán · 2021 · Methods in molecular biology
  97. AI approaches for the discovery and validation of drug targets
    Aaron Wenteler, Claudia Cabrera, Wei Wei, Victor Neduva, Michael R. Barnes · 2024 · Cambridge Prisms Precision Medicine
  98. Epigenetic relevant chemical space: a chemoinformatic characterization of inhibitors of DNA methyltransferases
    Eli Fernández‐de Gortari, José L. Medina‐Franco · 2015 · RSC Advances
  99. Multi-level advances in databases related to systems pharmacology in traditional Chinese medicine: a 60-year review
    Mengyue Fan, Ching Jin, Daping Li, Yingshan Deng, Yao Lin, Yongjun Chen, Yuling Ma, Taiyi Wang · 2023 · Frontiers in Pharmacology
  100. Graph neural networks driven acceleration in drug discovery
    Rui Wang, Chunlin Zhuang · 2025 · Acta Pharmaceutica Sinica B