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  1. Pairs of similar compounds that only differ by a small structural modification but exhibit a large difference in their binding affinity for a given target are known as activity cliffs (ACs). It has been hypoth...

    Authors: Markus Dablander, Thierry Hanser, Renaud Lambiotte and Garrett M. Morris
    Citation: Journal of Cheminformatics 2023 15:47
  2. Efficient and machine-readable representations are needed to accurately identify, validate and communicate information of chemical structures. Many such representations have been developed (as, for example, th...

    Authors: Kostas Blekos, Kostas Chairetakis, Iseult Lynch and Effie Marcoulaki
    Citation: Journal of Cheminformatics 2023 15:44
  3. Artificial intelligence has deeply revolutionized the field of medicinal chemistry with many impressive applications, but the success of these applications requires a massive amount of training samples with hi...

    Authors: Kexin Chen, Guangyong Chen, Junyou Li, Yuansheng Huang, Ercheng Wang, Tingjun Hou and Pheng-Ann Heng
    Citation: Journal of Cheminformatics 2023 15:43
  4. Artificial intelligence (AI)-based molecular design methods, especially deep generative models for generating novel molecule structures, have gratified our imagination to explore unknown chemical space without...

    Authors: Xiaohong Liu, Wei Zhang, Xiaochu Tong, Feisheng Zhong, Zhaojun Li, Zhaoping Xiong, Jiacheng Xiong, Xiaolong Wu, Zunyun Fu, Xiaoqin Tan, Zhiguo Liu, Sulin Zhang, Hualiang Jiang, Xutong Li and Mingyue Zheng
    Citation: Journal of Cheminformatics 2023 15:42
  5. Ligand-based virtual screening is a widespread method in modern drug design. It allows for a rapid screening of large compound databases in order to identify similar structures. Here we report an open-source c...

    Authors: Sascha Jung, Helge Vatheuer and Paul Czodrowski
    Citation: Journal of Cheminformatics 2023 15:40
  6. High throughput screening (HTS) is widely used in drug discovery and chemical biology to identify and characterize agents having pharmacologic properties often by evaluation of large chemical libraries. Standa...

    Authors: Bryan Queme, John C. Braisted, Patricia Dranchak and James Inglese
    Citation: Journal of Cheminformatics 2023 15:39
  7. Drug discovery for a protein target is a laborious and costly process. Deep learning (DL) methods have been applied to drug discovery and successfully generated novel molecular structures, and they can substan...

    Authors: Yangyang Chen, Zixu Wang, Lei Wang, Jianmin Wang, Pengyong Li, Dongsheng Cao, Xiangxiang Zeng, Xiucai Ye and Tetsuya Sakurai
    Citation: Journal of Cheminformatics 2023 15:38
  8. Vibrational circular dichroism (VCD) spectroscopy can generate the data required for the assignment of absolute configuration, but the spectra are hard to interpret. We have recorded VCD data for thirty pairs ...

    Authors: Jonathan Lam, Richard J. Lewis and Jonathan M. Goodman
    Citation: Journal of Cheminformatics 2023 15:36
  9. Chemical mutagenicity is a serious issue that needs to be addressed in early drug discovery. Over a long period of time, medicinal chemists have manually summarized a series of empirical rules for the optimiza...

    Authors: Chaofeng Lou, Hongbin Yang, Hua Deng, Mengting Huang, Weihua Li, Guixia Liu, Philip W. Lee and Yun Tang
    Citation: Journal of Cheminformatics 2023 15:35
  10. Toxicological evaluation of substances in regulation still often relies on animal experiments. Understanding the substances’ mode-of-action is crucial to develop alternative test strategies. Omics methods are ...

    Authors: Aileen Bahl, Celine Ibrahim, Kristina Plate, Andrea Haase, Jörn Dengjel, Penny Nymark and Verónica I. Dumit
    Citation: Journal of Cheminformatics 2023 15:34
  11. Drug combination therapies are promising clinical treatments for curing patients. However, efficiently identifying valid drug combinations remains challenging because the number of available drugs has increase...

    Authors: Mengdie Xu, Xinwei Zhao, Jingyu Wang, Wei Feng, Naifeng Wen, Chunyu Wang, Junjie Wang, Yun Liu and Lingling Zhao
    Citation: Journal of Cheminformatics 2023 15:33
  12. Mapping the chemical space of compounds to chemical structures remains a challenge in metabolomics. Despite the advancements in untargeted liquid chromatography-mass spectrometry (LC–MS) to achieve a high-thro...

    Authors: Mahnoor Zulfiqar, Luiz Gadelha, Christoph Steinbeck, Maria Sorokina and Kristian Peters
    Citation: Journal of Cheminformatics 2023 15:32
  13. Protein mutations, especially those which occur in the binding site, play an important role in inter-individual drug response and may alter binding affinity and thus impact the drug’s efficacy and side effects...

    Authors: Ammar Ammar, Rachel Cavill, Chris Evelo and Egon Willighagen
    Citation: Journal of Cheminformatics 2023 15:31
  14. Graph convolutional neural networks (GCNs) have been repeatedly shown to have robust capacities for modeling graph data such as small molecules. Message-passing neural networks (MPNNs), a group of GCN variants...

    Authors: Chengyou Liu, Yan Sun, Rebecca Davis, Silvia T. Cardona and Pingzhao Hu
    Citation: Journal of Cheminformatics 2023 15:29
  15. Non-target analysis combined with liquid chromatography high resolution mass spectrometry is considered one of the most comprehensive strategies for the detection and identification of known and unknown chemic...

    Authors: Jim Boelrijk, Denice van Herwerden, Bernd Ensing, Patrick Forré and Saer Samanipour
    Citation: Journal of Cheminformatics 2023 15:28
  16. The simplified molecular-input line-entry system (SMILES) is the most prevalent molecular representation used in AI-based chemical applications. However, there are innate limitations associated with the intern...

    Authors: Umit V. Ucak, Islambek Ashyrmamatov and Juyong Lee
    Citation: Journal of Cheminformatics 2023 15:26

    The Correction to this article has been published in Journal of Cheminformatics 2023 15:68

  17. Published reports of chemical compounds often contain multiple machine-readable descriptions which may supplement each other in order to yield coherent and complete chemical representations. This publication p...

    Authors: Andrius Merkys, Antanas Vaitkus, Algirdas Grybauskas, Aleksandras Konovalovas, Miguel Quirós and Saulius Gražulis
    Citation: Journal of Cheminformatics 2023 15:25
  18. Rational drug design often starts from specific scaffolds to which side chains/substituents are added or modified due to the large drug-like chemical space available to search for novel drug-like molecules. Wi...

    Authors: Xuhan Liu, Kai Ye, Herman W. T. van Vlijmen, Adriaan P. IJzerman and Gerard J. P. van Westen
    Citation: Journal of Cheminformatics 2023 15:24
  19. The influence of molecular fragmentation and parameter settings on a mesoscopic dissipative particle dynamics (DPD) simulation of lamellar bilayer formation for a C10E4/water mixture is studied. A “bottom-up” dec...

    Authors: Felix Bänsch, Christoph Steinbeck and Achim Zielesny
    Citation: Journal of Cheminformatics 2023 15:23
  20. Generative deep learning models have emerged as a powerful approach for de novo drug design as they aid researchers in finding new molecules with desired properties. Despite continuous improvements in the fiel...

    Authors: Linde Schoenmaker, Olivier J. M. Béquignon, Willem Jespers and Gerard J. P. van Westen
    Citation: Journal of Cheminformatics 2023 15:22
  21. Artificial Intelligence is revolutionizing many aspects of the pharmaceutical industry. Deep learning models are now routinely applied to guide drug discovery projects leading to faster and improved findings, ...

    Authors: Paulo Neves, Kelly McClure, Jonas Verhoeven, Natalia Dyubankova, Ramil Nugmanov, Andrey Gedich, Sairam Menon, Zhicai Shi and Jörg K. Wegner
    Citation: Journal of Cheminformatics 2023 15:20

    The Correction to this article has been published in Journal of Cheminformatics 2023 15:30

  22. Particle-Based (PB) simulations, including Molecular Dynamics (MD), provide access to system observables that are not easily available experimentally. However, in most cases, PB data needs to be processed afte...

    Authors: Samuel Tovey, Fabian Zills, Francisco Torres-Herrador, Christoph Lohrmann, Marco Brückner and Christian Holm
    Citation: Journal of Cheminformatics 2023 15:19
  23. Citations are an essential aspect of research communication and have become the basis of many evaluation metrics in the academic world. Some see citation counts as a mark of scientific impact or even quality, ...

    Authors: Egon Willighagen
    Citation: Journal of Cheminformatics 2023 15:14

    The Editorial to this article has been published in Journal of Cheminformatics 2023 15:15

  24. Deep learning has been widely used for protein engineering. However, it is limited by the lack of sufficient experimental data to train an accurate model for predicting the functional fitness of high-order mut...

    Authors: Mingchen Li, Liqi Kang, Yi Xiong, Yu Guang Wang, Guisheng Fan, Pan Tan and Liang Hong
    Citation: Journal of Cheminformatics 2023 15:12
  25. In this work, we provide further development of the junction tree variational autoencoder (JT VAE) architecture in terms of implementation and application of the internal feature space of the model. Pretrainin...

    Authors: Vladimir Kondratyev, Marian Dryzhakov, Timur Gimadiev and Dmitriy Slutskiy
    Citation: Journal of Cheminformatics 2023 15:11
  26. This article documents enu, a freely-downloadable, open-source and stand-alone program written in C++ for the enumeration of the constitutional isomers and stereoisomers of a molecular formula. The program relies...

    Authors: Salomé R. Rieder, Marina P. Oliveira, Sereina Riniker and Philippe H. Hünenberger
    Citation: Journal of Cheminformatics 2023 15:10
  27. The field of high-resolution mass spectrometry (HRMS) and ancillary hyphenated techniques comprise a rapidly expanding and evolving area. As popularity of HRMS instruments grows, there is a concurrent need for...

    Authors: Dane R. Letourneau, Dennis D. August and Dietrich A. Volmer
    Citation: Journal of Cheminformatics 2023 15:7
  28. Modern computer-assisted synthesis planning tools provide strong support for this problem. However, they are still limited by computational complexity. This limitation may be overcome by scoring the synthetic ...

    Authors: Grzegorz Skoraczyński, Mateusz Kitlas, Błażej Miasojedow and Anna Gambin
    Citation: Journal of Cheminformatics 2023 15:6
  29. Ubiquitin-specific-processing protease 7 (USP7) is a promising target protein for cancer therapy, and great attention has been given to the identification of USP7 inhibitors. Traditional virtual screening meth...

    Authors: Wen-feng Shen, He-wei Tang, Jia-bo Li, Xiang Li and Si Chen
    Citation: Journal of Cheminformatics 2023 15:5
  30. Activity cliffs (AC) are formed by pairs of structural analogues that are active against the same target but have a large difference in potency. While much of our knowledge about ACs has originated from the an...

    Authors: Shunsuke Tamura, Tomoyuki Miyao and Jürgen Bajorath
    Citation: Journal of Cheminformatics 2023 15:4
  31. With the ongoing rapid growth of publicly available ligand–protein bioactivity data, there is a trove of valuable data that can be used to train a plethora of machine-learning algorithms. However, not all data...

    Authors: O. J. M. Béquignon, B. J. Bongers, W. Jespers, A. P. IJzerman, B. van der Water and G. J. P. van Westen
    Citation: Journal of Cheminformatics 2023 15:3
  32. Explainable artificial intelligence (XAI) methods have shown increasing applicability in chemistry. In this context, visualization techniques can highlight regions of a molecule to reveal their influence over ...

    Authors: Henry Heberle, Linlin Zhao, Sebastian Schmidt, Thomas Wolf and Julian Heinrich
    Citation: Journal of Cheminformatics 2023 15:2
  33. Developing and implementing computational algorithms for the extraction of specific substructures from molecular graphs (in silico molecule fragmentation) is an iterative process. It involves repeated sequence...

    Authors: Felix Bänsch, Jonas Schaub, Betül Sevindik, Samuel Behr, Julian Zander, Christoph Steinbeck and Achim Zielesny
    Citation: Journal of Cheminformatics 2023 15:1
  34. Traditional Chinese Medicine (TCM) has been widely used in the treatment of various diseases for millennia. In the modernization process of TCM, TCM ingredient databases are playing more and more important rol...

    Authors: Liu-Xia Zhang, Jie Dong, Hui Wei, Shao-Hua Shi, Ai-Ping Lu, Gui-Ming Deng and Dong-Sheng Cao
    Citation: Journal of Cheminformatics 2022 14:89
  35. This article demonstrates how to create Chemical Space Networks (CSNs) using a Python RDKit and NetworkX workflow. CSNs are a type of network visualization that depict compounds as nodes connected by edges, de...

    Authors: Vincent F. Scalfani, Vishank D. Patel and Avery M. Fernandez
    Citation: Journal of Cheminformatics 2022 14:87
  36. A de novo molecular design workflow can be used together with technologies such as reinforcement learning to navigate the chemical space. A bottleneck in the workflow that remains to be solved is how to integr...

    Authors: Iiris Sundin, Alexey Voronov, Haoping Xiao, Kostas Papadopoulos, Esben Jannik Bjerrum, Markus Heinonen, Atanas Patronov, Samuel Kaski and Ola Engkvist
    Citation: Journal of Cheminformatics 2022 14:86