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  1. Reaction databases are a key resource for a wide variety of applications in computational chemistry and biochemistry, including Computer-aided Synthesis Planning (CASP) and the large-scale analysis of metaboli...

    Authors: Tieu-Long Phan, Klaus Weinbauer, Thomas Gärtner, Daniel Merkle, Jakob L. Andersen, Rolf Fagerberg and Peter F. Stadler
    Citation: Journal of Cheminformatics 2024 16:82
  2. While drug combination therapies are of great importance, particularly in cancer treatment, identifying novel synergistic drug combinations has been a challenging venture. Computational methods have emerged in...

    Authors: Raghad AlJarf, Carlos H. M. Rodrigues, Yoochan Myung, Douglas E. V. Pires and David B. Ascher
    Citation: Journal of Cheminformatics 2024 16:81
  3. Retrosynthesis planning poses a formidable challenge in the organic chemical industry, particularly in pharmaceuticals. Single-step retrosynthesis prediction, a crucial step in the planning process, has witnes...

    Authors: Kaipeng Zeng, Bo Yang, Xin Zhao, Yu Zhang, Fan Nie, Xiaokang Yang, Yaohui Jin and Yanyan Xu
    Citation: Journal of Cheminformatics 2024 16:80
  4. Previous deep learning methods for predicting protein binding pockets mainly employed 3D convolution, yet an abundance of convolution operations may lead the model to excessively prioritize local information, ...

    Authors: Ruifeng Zhou, Jing Fan, Sishu Li, Wenjie Zeng, Yilun Chen, Xiaoshan Zheng, Hongyang Chen and Jun Liao
    Citation: Journal of Cheminformatics 2024 16:79
  5. Accurate recognition of hand-drawn chemical structures is crucial for digitising hand-written chemical information in traditional laboratory notebooks or facilitating stylus-based structure entry on tablets or...

    Authors: Kohulan Rajan, Henning Otto Brinkhaus, Achim Zielesny and Christoph Steinbeck
    Citation: Journal of Cheminformatics 2024 16:78
  6. SMILES-based generative models are amongst the most robust and successful recent methods used to augment drug design. They are typically used for complete de novo generation, however, scaffold decoration and f...

    Authors: Morgan Thomas, Mazen Ahmad, Gary Tresadern and Gianni de Fabritiis
    Citation: Journal of Cheminformatics 2024 16:77
  7. Materials science is an interdisciplinary field that studies the properties, structures, and behaviors of different materials. A large amount of scientific literature contains rich knowledge in the field of ma...

    Authors: Zihui Huang, Liqiang He, Yuhang Yang, Andi Li, Zhiwen Zhang, Siwei Wu, Yang Wang, Yan He and Xujie Liu
    Citation: Journal of Cheminformatics 2024 16:76
  8. Conformal prediction has seen many applications in pharmaceutical science, being able to calibrate outputs of machine learning models and producing valid prediction intervals. We here present the open source s...

    Authors: Staffan Arvidsson McShane, Ulf Norinder, Jonathan Alvarsson, Ernst Ahlberg, Lars Carlsson and Ola Spjuth
    Citation: Journal of Cheminformatics 2024 16:75
  9. Temperature-responsive liquid chromatography (TRLC) offers a promising alternative to reversed-phase liquid chromatography (RPLC) for environmentally friendly analytical techniques by utilizing pure water as a...

    Authors: Elena Bandini, Rodrigo Castellano Ontiveros, Ardiana Kajtazi, Hamed Eghbali and Frédéric Lynen
    Citation: Journal of Cheminformatics 2024 16:72
  10. Stereochemistry plays a fundamental role in pharmacology. Here, we systematically investigate the relationship between stereoisomerism and bioactivity on over 1 M compounds, finding that a very significant fra...

    Authors: Arnau Comajuncosa-Creus, Aksel Lenes, Miguel Sánchez-Palomino, Dylan Dalton and Patrick Aloy
    Citation: Journal of Cheminformatics 2024 16:70
  11. Identification of interactions between chemical compounds and proteins is crucial for various applications, including drug discovery, target identification, network pharmacology, and elucidation of protein fun...

    Authors: Yufang Zhang, Jiayi Li, Shenggeng Lin, Jianwei Zhao, Yi Xiong and Dong-Qing Wei
    Citation: Journal of Cheminformatics 2024 16:67
  12. Accurate ligand binding site prediction (LBSP) within proteins is essential for drug discovery. We developed ProteinUNetResNetV2.0 (PUResNetV2.0), leveraging sparse representation of protein structures to impr...

    Authors: Kandel Jeevan, Shrestha Palistha, Hilal Tayara and Kil T. Chong
    Citation: Journal of Cheminformatics 2024 16:66
  13. Generative models are undergoing rapid research and application to de novo drug design. To facilitate their application and evaluation, we present MolScore. MolScore already contains many drug-design-relevant ...

    Authors: Morgan Thomas, Noel M. O’Boyle, Andreas Bender and Chris De Graaf
    Citation: Journal of Cheminformatics 2024 16:64
  14. Drug discovery is an intricate and costly process. Repurposing existing drugs and active compounds offers a viable pathway to develop new therapies for various diseases. By leveraging publicly available biomed...

    Authors: Reagan M. Mogire, Silviane A. Miruka, Dennis W. Juma, Case W. McNamara, Ben Andagalu, Jeremy N. Burrows, Elodie Chenu, James Duffy, Bernhards R. Ogutu and Hoseah M. Akala
    Citation: Journal of Cheminformatics 2024 16:63
  15. In drug discovery, virtual screening is crucial for identifying potential hit compounds. This study aims to present a novel pipeline that employs machine learning models that amalgamates various conventional s...

    Authors: Said Moshawih, Zhen Hui Bu, Hui Poh Goh, Nurolaini Kifli, Lam Hong Lee, Khang Wen Goh and Long Chiau Ming
    Citation: Journal of Cheminformatics 2024 16:62
  16. Small molecule identification is a crucial task in analytical chemistry and life sciences. One of the most commonly used technologies to elucidate small molecule structures is mass spectrometry. Spectral libra...

    Authors: Danh Bui-Thi, Youzhong Liu, Jennifer L. Lippens, Kris Laukens and Thomas De Vijlder
    Citation: Journal of Cheminformatics 2024 16:61
  17. Selecting greener solvents during experiment design is imperative for greener chemistry. While many solvent selection guides are currently used in the pharmaceutical industry, these are often paper-based guide...

    Authors: Joseph Heeley, Samuel Boobier and Jonathan D. Hirst
    Citation: Journal of Cheminformatics 2024 16:60
  18. De novo molecular design is the process of searching chemical space for drug-like molecules with desired properties, and deep learning has been recognized as a promising solution. In this study, I developed an...

    Authors: Hocheol Lim
    Citation: Journal of Cheminformatics 2024 16:59
  19. We present an updated overview of the AiZynthFinder package for retrosynthesis planning. Since the first version was released in 2020, we have added a substantial number of new features based on user feedback....

    Authors: Lakshidaa Saigiridharan, Alan Kai Hassen, Helen Lai, Paula Torren-Peraire, Ola Engkvist and Samuel Genheden
    Citation: Journal of Cheminformatics 2024 16:57
  20. Deep learning models adapted from natural language processing offer new opportunities for the prediction of active compounds via machine translation of sequential molecular data representations. For example, c...

    Authors: Hengwei Chen and Jürgen Bajorath
    Citation: Journal of Cheminformatics 2024 16:55
  21. This work presents a proposed extension to the International Union of Pure and Applied Chemistry (IUPAC) International Chemical Identifier (InChI) standard that allows the representation of isotopically-resolv...

    Authors: Hunter N. B. Moseley, Philippe Rocca-Serra, Reza M. Salek, Masanori Arita and Emma L. Schymanski
    Citation: Journal of Cheminformatics 2024 16:54
  22. Molecular fingerprints are indispensable tools in cheminformatics. However, stereochemistry is generally not considered, which is problematic for large molecules which are almost all chiral.

    Authors: Markus Orsi and Jean-Louis Reymond
    Citation: Journal of Cheminformatics 2024 16:53
  23. Protein-ligand binding affinity plays a pivotal role in drug development, particularly in identifying potential ligands for target disease-related proteins. Accurate affinity predictions can significantly redu...

    Authors: Julia Rahman, M. A. Hakim Newton, Mohammed Eunus Ali and Abdul Sattar
    Citation: Journal of Cheminformatics 2024 16:52
  24. Chemical reaction optimization (RO) is an iterative process that results in large, high-dimensional datasets. Current tools allow for only limited analysis and understanding of parameter spaces, making it hard...

    Authors: Christina Humer, Rachel Nicholls, Henry Heberle, Moritz Heckmann, Michael Pühringer, Thomas Wolf, Maximilian Lübbesmeyer, Julian Heinrich, Julius Hillenbrand, Giulio Volpin and Marc Streit
    Citation: Journal of Cheminformatics 2024 16:51
  25. As the world grapples with the relentless challenges posed by diseases like malaria, the advent of sophisticated computational tools has emerged as a beacon of hope in the quest for effective treatments. In th...

    Authors: Nomagugu B. Ncube, Matshawandile Tukulula and Krishna G. Govender
    Citation: Journal of Cheminformatics 2024 16:50
  26. Adverse Outcome Pathways (AOPs) have been proposed to facilitate mechanistic understanding of interactions of chemicals/materials with biological systems. Each AOP starts with a molecular initiating event (MIE...

    Authors: Jeaphianne P. M. van Rijn, Marvin Martens, Ammar Ammar, Mihaela Roxana Cimpan, Valerie Fessard, Peter Hoet, Nina Jeliazkova, Sivakumar Murugadoss, Ivana Vinković Vrček and Egon L. Willighagen
    Citation: Journal of Cheminformatics 2024 16:49
  27. Previous studies have shown that the three-dimensional (3D) geometric and electronic structure of molecules play a crucial role in determining their key properties and intermolecular interactions. Therefore, i...

    Authors: Zhijiang Yang, Tengxin Huang, Li Pan, Jingjing Wang, Liangliang Wang, Junjie Ding and Junhua Xiao
    Citation: Journal of Cheminformatics 2024 16:48

    The Correction to this article has been published in Journal of Cheminformatics 2024 16:68

  28. In this paper we present a method that allows leveraging 3D electron density information to train a deep neural network pipeline to segment regions of high, medium and low electronegativity and classify substa...

    Authors: Satnam Singh, Gina Zeh, Jessica Freiherr, Thilo Bauer, Isik Türkmen and Andreas T. Grasskamp
    Citation: Journal of Cheminformatics 2024 16:45
  29. Multiple metrics are used when assessing and validating the performance of quantitative structure–activity relationship (QSAR) models. In the case of binary classification, balanced accuracy is a metric to ass...

    Authors: Sébastien J. J. Guesné, Thierry Hanser, Stéphane Werner, Samuel Boobier and Shaylyn Scott
    Citation: Journal of Cheminformatics 2024 16:43
  30. Wiswesser Line Notation (WLN) is a old line notation for encoding chemical compounds for storage and processing by computers. Whilst the notation itself has long since been surpassed by SMILES and InChI, distr...

    Authors: Michael Blakey, Samantha Pearman-Kanza and Jeremy G. Frey
    Citation: Journal of Cheminformatics 2024 16:42
  31. Drug combination therapies have shown promise in clinical cancer treatments. However, it is hard to experimentally identify all drug combinations for synergistic interaction even with high-throughput screening...

    Authors: Xinwei Zhao, Junqing Xu, Youyuan Shui, Mengdie Xu, Jie Hu, Xiaoyan Liu, Kai Che, Junjie Wang and Yun Liu
    Citation: Journal of Cheminformatics 2024 16:41
  32. Poly ADP-ribose polymerase 1 (PARP1) is an attractive therapeutic target for cancer treatment. Machine-learning scoring functions constitute a promising approach to discovering novel PARP1 inhibitors. Cutting-...

    Authors: Klaudia Caba, Viet-Khoa Tran-Nguyen, Taufiq Rahman and Pedro J. Ballester
    Citation: Journal of Cheminformatics 2024 16:40
  33. Stakeholders of machine learning models desire explainable artificial intelligence (XAI) to produce human-understandable and consistent interpretations. In computational toxicity, augmentation of text-based mo...

    Authors: Peter B. R. Hartog, Fabian Krüger, Samuel Genheden and Igor V. Tetko
    Citation: Journal of Cheminformatics 2024 16:39
  34. Accurate prediction of the enzyme comission (EC) numbers for chemical reactions is essential for the understanding and manipulation of enzyme functions, biocatalytic processes and biosynthetic planning. A numb...

    Authors: Wenjia Qian, Xiaorui Wang, Yu Kang, Peichen Pan, Tingjun Hou and Chang-Yu Hsieh
    Citation: Journal of Cheminformatics 2024 16:38
  35. The challenge of devising pathways for organic synthesis remains a central issue in the field of medicinal chemistry. Over the span of six decades, computer-aided synthesis planning has given rise to a plethor...

    Authors: Maarten R. Dobbelaere, István Lengyel, Christian V. Stevens and Kevin M. Van Geem
    Citation: Journal of Cheminformatics 2024 16:37
  36. Natural products are a diverse class of compounds with promising biological properties, such as high potency and excellent selectivity. However, they have different structural motifs than typical drug-like com...

    Authors: Davide Boldini, Davide Ballabio, Viviana Consonni, Roberto Todeschini, Francesca Grisoni and Stephan A. Sieber
    Citation: Journal of Cheminformatics 2024 16:35
  37. Kinetic process models are widely applied in science and engineering, including atmospheric, physiological and technical chemistry, reactor design, or process optimization. These models rely on numerous kineti...

    Authors: Matteo Krüger, Ashmi Mishra, Peter Spichtinger, Ulrich Pöschl and Thomas Berkemeier
    Citation: Journal of Cheminformatics 2024 16:34
  38. We present a user-friendly molecular generative pipeline called Pocket Crafter, specifically designed to facilitate hit finding activity in the drug discovery process. This workflow utilized a three-dimensiona...

    Authors: Lingling Shen, Jian Fang, Lulu Liu, Fei Yang, Jeremy L. Jenkins, Peter S. Kutchukian and He Wang
    Citation: Journal of Cheminformatics 2024 16:33