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  1. Time-split cross-validation is broadly recognized as the gold standard for validating predictive models intended for use in medicinal chemistry projects. Unfortunately this type of data is not broadly availabl...

    Authors: Gregory A. Landrum, Maximilian Beckers, Jessica Lanini, Nadine Schneider, Nikolaus Stiefl and Sereina Riniker
    Citation: Journal of Cheminformatics 2023 15:119
  2. The solubility of proteins stands as a pivotal factor in the realm of pharmaceutical research and production. Addressing the imperative to enhance production efficiency and curtail experimental costs, the dema...

    Authors: Long Chen, Rining Wu, Feixiang Zhou, Huifeng Zhang and Jian K. Liu
    Citation: Journal of Cheminformatics 2023 15:118
  3. While the Protein Data Bank (PDB) contains a wealth of structural information on ligands bound to macromolecules, their analysis can be challenging due to the large amount and diversity of data. Here, we prese...

    Authors: Ibrahim Roshan Kunnakkattu, Preeti Choudhary, Lukas Pravda, Nurul Nadzirin, Oliver S. Smart, Qi Yuan, Stephen Anyango, Sreenath Nair, Mihaly Varadi and Sameer Velankar
    Citation: Journal of Cheminformatics 2023 15:117
  4. This paper presents a novel approach called Pharmacophore Activity Delta for extracting outstanding pharmacophores from a chemogenomic dataset, with a specific focus on a kinase target known as BCR-ABL. The me...

    Authors: Etienne Lehembre, Johanna Giovannini, Damien Geslin, Alban Lepailleur, Jean-Luc Lamotte, David Auber, Abdelkader Ouali, Bruno Cremilleux, Albrecht Zimmermann, Bertrand Cuissart and Ronan Bureau
    Citation: Journal of Cheminformatics 2023 15:116
  5. The discovery and utilization of natural products derived from endophytic microorganisms have garnered significant attention in pharmaceutical research. While remarkable progress has been made in this field ea...

    Authors: Hong-Quan Xu, Huan Xiao, Jin-Hui Bu, Yan-Feng Hong, Yu-Hong Liu, Zi-Yue Tao, Shu-Fan Ding, Yi-Tong Xia, E Wu, Zhen Yan, Wei Zhang, Gong-Xing Chen, Feng Zhu and Lin Tao
    Citation: Journal of Cheminformatics 2023 15:115
  6. Prediction of chemical shift in NMR using machine learning methods is typically done with the maximum amount of data available to achieve the best results. In some cases, such large amounts of data are not ava...

    Authors: Herman Rull, Markus Fischer and Stefan Kuhn
    Citation: Journal of Cheminformatics 2023 15:114
  7. While a multitude of deep generative models have recently emerged there exists no best practice for their practically relevant validation. On the one hand, novel de novo-generated molecules cannot be refuted by r...

    Authors: Koichi Handa, Morgan C. Thomas, Michiharu Kageyama, Takeshi Iijima and Andreas Bender
    Citation: Journal of Cheminformatics 2023 15:112
  8. In chemistry-related disciplines, a vast repository of molecular structural data has been documented in scientific publications but remains inaccessible to computational analyses owing to its non-machine-reada...

    Authors: Chong Zhou, Wei Liu, Xiyue Song, Mengling Yang and Xiaowang Peng
    Citation: Journal of Cheminformatics 2023 15:111
  9. BBPs have the potential to facilitate the delivery of drugs to the brain, opening up new avenues for the development of treatments targeting diseases of the central nervous system (CNS). The obstacle faced in ...

    Authors: Ansar Naseem, Fahad Alturise, Tamim Alkhalifah and Yaser Daanial Khan
    Citation: Journal of Cheminformatics 2023 15:110
  10. The discovery of both distinctive lead molecules and novel drug targets is a great challenge in drug discovery, which particularly accounts for orphan diseases. Huntington’s disease (HD) is an orphan, neurodeg...

    Authors: Sven Marcel Stefan, Jens Pahnke and Vigneshwaran Namasivayam
    Citation: Journal of Cheminformatics 2023 15:109
  11. Plants are one of the primary sources of natural products for drug development. However, despite centuries of research, only a limited region of the phytochemical space has been studied. To understand the scop...

    Authors: Daniel Domingo-Fernández, Yojana Gadiya, Sarah Mubeen, David Healey, Bryan H. Norman and Viswa Colluru
    Citation: Journal of Cheminformatics 2023 15:107
  12. Deep learning models have proven to be a powerful tool for the prediction of molecular properties for applications including drug design and the development of energy storage materials. However, in order to le...

    Authors: Tianzhixi Yin, Gihan Panapitiya, Elizabeth D. Coda and Emily G. Saldanha
    Citation: Journal of Cheminformatics 2023 15:105
  13. Identifying the molecular formula and fragmentation reactions of an unknown compound from its mass spectrum is crucial in areas such as natural product chemistry and metabolomics. We propose a method for ident...

    Authors: Sean Li, Björn Bohman, Gavin R. Flematti and Dylan Jayatilaka
    Citation: Journal of Cheminformatics 2023 15:104
  14. Docking of large compound collections becomes an important procedure to discover new chemical entities. Screening of large sets of compounds may also occur in de novo design projects guided by molecular dockin...

    Authors: Guzel Minibaeva, Aleksandra Ivanova and Pavel Polishchuk
    Citation: Journal of Cheminformatics 2023 15:102
  15. Science and art have been connected for centuries. With the development of new computational methods, new scientific disciplines have emerged, such as computational chemistry, and related fields, such as chemi...

    Authors: Daniela Gaytán-Hernández, Ana L. Chávez-Hernández, Edgar López-López, Jazmín Miranda-Salas, Fernanda I. Saldívar-González and José L. Medina-Franco
    Citation: Journal of Cheminformatics 2023 15:100
  16. A reliable and practical determination of a chemical species’ solubility in water continues to be examined using empirical observations and exhaustive experimental studies alone. Predictions of chemical solubi...

    Authors: Arash Tayyebi, Ali S Alshami, Zeinab Rabiei, Xue Yu, Nadhem Ismail, Musabbir Jahan Talukder and Jason Power
    Citation: Journal of Cheminformatics 2023 15:99
  17. In recent years, cheminformatics has experienced significant advancements through the development of new open-source software tools based on various cheminformatics programming toolkits. However, adopting thes...

    Authors: Venkata Chandrasekhar, Nisha Sharma, Jonas Schaub, Christoph Steinbeck and Kohulan Rajan
    Citation: Journal of Cheminformatics 2023 15:98
  18. Compound–protein interactions (CPI) play significant roles in drug development. To avoid side effects, it is also crucial to evaluate drug selectivity when binding to different targets. However, most selectivi...

    Authors: Nan Song, Ruihan Dong, Yuqian Pu, Ercheng Wang, Junhai Xu and Fei Guo
    Citation: Journal of Cheminformatics 2023 15:97
  19. Ultra-large chemical libraries are reaching 10s to 100s of billions of molecules. A challenge for these libraries is to efficiently check if a proposed molecule is present. Here we propose and study Bloom filt...

    Authors: Jorge Medina and Andrew D. White
    Citation: Journal of Cheminformatics 2023 15:95
  20. Metal–organic frameworks (MOFs), are porous crystalline structures comprising of metal ions or clusters intricately linked with organic entities, displaying topological diversity and effortless chemical flexib...

    Authors: Mehrdad Jalali, A. D. Dinga Wonanke and Christof Wöll
    Citation: Journal of Cheminformatics 2023 15:94

    The Correction to this article has been published in Journal of Cheminformatics 2023 15:108

  21. In recent years, drug design has been revolutionized by the application of deep learning techniques, and molecule generation is a crucial aspect of this transformation. However, most of the current deep learni...

    Authors: Chao Hu, Song Li, Chenxing Yang, Jun Chen, Yi Xiong, Guisheng Fan, Hao Liu and Liang Hong
    Citation: Journal of Cheminformatics 2023 15:91
  22. Mass-Suite (MSS) is a Python-based, open-source software package designed to analyze high-resolution mass spectrometry (HRMS)-based non-targeted analysis (NTA) data, particularly for water quality assessment and ...

    Authors: Ximin Hu, Derek Mar, Nozomi Suzuki, Bowei Zhang, Katherine T. Peter, David A. C. Beck and Edward P. Kolodziej
    Citation: Journal of Cheminformatics 2023 15:87
  23. Machine learning-based chemical screening has made substantial progress in recent years. However, these predictions often have low accuracy and high uncertainty when identifying new active chemical scaffolds. ...

    Authors: Prasannavenkatesh Durai, Sue Jung Lee, Jae Wook Lee, Cheol-Ho Pan and Keunwan Park
    Citation: Journal of Cheminformatics 2023 15:86
  24. Opioids are essential pharmaceuticals due to their analgesic properties, however, lethal side effects, addiction, and opioid tolerance are extremely challenging. The development of novel molecules targeting the

    Authors: Christopher Secker, Konstantin Fackeldey, Marcus Weber, Sourav Ray, Christoph Gorgulla and Christof Schütte
    Citation: Journal of Cheminformatics 2023 15:85
  25. Many recently proposed structure-based virtual screening models appear to be able to accurately distinguish high affinity binders from non-binders. However, several recent studies have shown that they often do...

    Authors: Thomas E. Hadfield, Jack Scantlebury and Charlotte M. Deane
    Citation: Journal of Cheminformatics 2023 15:84
  26. Generative models are frequently used for de novo design in drug discovery projects to propose new molecules. However, the question of whether or not the generated molecules can be synthesized is not systemati...

    Authors: Maud Parrot, Hamza Tajmouati, Vinicius Barros Ribeiro da Silva, Brian Ross Atwood, Robin Fourcade, Yann Gaston-Mathé, Nicolas Do Huu and Quentin Perron
    Citation: Journal of Cheminformatics 2023 15:83
  27. We report the major highlights of the School of Cheminformatics in Latin America, Mexico City, November 24–25, 2022. Six lectures, one workshop, and one roundtable with four editors were presented during an on...

    Authors: Karla Gonzalez-Ponce, Carolina Horta Andrade, Fiona Hunter, Johannes Kirchmair, Karina Martinez-Mayorga, José L. Medina-Franco, Matthias Rarey, Alexander Tropsha, Alexandre Varnek and Barbara Zdrazil
    Citation: Journal of Cheminformatics 2023 15:82
  28. Graph neural networks have recently become a standard method for analyzing chemical compounds. In the field of molecular property prediction, the emphasis is now on designing new model architectures, and the i...

    Authors: Agnieszka Wojtuch, Tomasz Danel, Sabina Podlewska and Łukasz Maziarka
    Citation: Journal of Cheminformatics 2023 15:81
  29. Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) spatially resolves the chemical composition of tissues. Lipids are of particular interest, as they influence important biologic...

    Authors: Gerard Baquer, Lluc Sementé, Pere Ràfols, Lucía Martín-Saiz, Christoph Bookmeyer, José A. Fernández, Xavier Correig and María García-Altares
    Citation: Journal of Cheminformatics 2023 15:80
  30. We developed a new seriation merit function for enhancing the visual information of data matrices. A local similarity matrix is calculated, where the average similarity of neighbouring objects is calculated in...

    Authors: Rita Lasfar and Gergely Tóth
    Citation: Journal of Cheminformatics 2023 15:78
  31. Lipophilicity is a fundamental physical property that significantly affects various aspects of drug behavior, including solubility, permeability, metabolism, distribution, protein binding, and toxicity. Accura...

    Authors: Yitian Wang, Jiacheng Xiong, Fu Xiao, Wei Zhang, Kaiyang Cheng, Jingxin Rao, Buying Niu, Xiaochu Tong, Ning Qu, Runze Zhang, Dingyan Wang, Kaixian Chen, Xutong Li and Mingyue Zheng
    Citation: Journal of Cheminformatics 2023 15:76
  32. Siamese networks, representing a novel class of neural networks, consist of two identical subnetworks sharing weights but receiving different inputs. Here we present a similarity-based pairing method for gener...

    Authors: Yumeng Zhang, Janosch Menke, Jiazhen He, Eva Nittinger, Christian Tyrchan, Oliver Koch and Hongtao Zhao
    Citation: Journal of Cheminformatics 2023 15:75
  33. Proteochemometric (PCM) modelling is a powerful computational drug discovery tool used in bioactivity prediction of potential drug candidates relying on both chemical and protein information. In PCM features a...

    Authors: Marina Gorostiola González, Remco L. van den Broek, Thomas G. M. Braun, Magdalini Chatzopoulou, Willem Jespers, Adriaan P. IJzerman, Laura H. Heitman and Gerard J. P. van Westen
    Citation: Journal of Cheminformatics 2023 15:74
  34. Decision tree ensembles are among the most robust, high-performing and computationally efficient machine learning approaches for quantitative structure–activity relationship (QSAR) modeling. Among them, gradie...

    Authors: Davide Boldini, Francesca Grisoni, Daniel Kuhn, Lukas Friedrich and Stephan A. Sieber
    Citation: Journal of Cheminformatics 2023 15:73
  35. In recent years, it has been seen that artificial intelligence (AI) starts to bring revolutionary changes to chemical synthesis. However, the lack of suitable ways of representing chemical reactions and the sc...

    Authors: Baiqing Li, Shimin Su, Chan Zhu, Jie Lin, Xinyue Hu, Lebin Su, Zhunzhun Yu, Kuangbiao Liao and Hongming Chen
    Citation: Journal of Cheminformatics 2023 15:72
  36. The identification of molecular structure is essential for understanding chemical diversity and for developing drug leads from small molecules. Nevertheless, the structure elucidation of small molecules by Nuc...

    Authors: Hyun Woo Kim, Chen Zhang, Raphael Reher, Mingxun Wang, Kelsey L. Alexander, Louis-Félix Nothias, Yoo Kyong Han, Hyeji Shin, Ki Yong Lee, Kyu Hyeong Lee, Myeong Ji Kim, Pieter C. Dorrestein, William H. Gerwick and Garrison W. Cottrell
    Citation: Journal of Cheminformatics 2023 15:71