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  1. 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
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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
  9. 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
  10. 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
  11. 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
  12. 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
  13. 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
  14. 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
  15. 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
  16. 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
  17. 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
  18. 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

  19. 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
  20. 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
  21. 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
  22. 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
  23. 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
  24. 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
  25. 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
  26. 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
  27. 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
  28. 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
  29. 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
  30. Protein-ligand binding site prediction is a useful tool for understanding the functional behaviour and potential drug-target interactions of a novel protein of interest. However, most binding site prediction m...

    Authors: Anna Carbery, Martin Buttenschoen, Rachael Skyner, Frank von Delft and Charlotte M. Deane
    Citation: Journal of Cheminformatics 2024 16:32
  31. In materials science, accurately computing properties like viscosity, melting point, and glass transition temperatures solely through physics-based models is challenging. Data-driven machine learning (ML) also...

    Authors: Alex K. Chew, Matthew Sender, Zachary Kaplan, Anand Chandrasekaran, Jackson Chief Elk, Andrea R. Browning, H. Shaun Kwak, Mathew D. Halls and Mohammad Atif Faiz Afzal
    Citation: Journal of Cheminformatics 2024 16:31
  32. Chemical structure segmentation constitutes a pivotal task in cheminformatics, involving the extraction and abstraction of structural information of chemical compounds from text-based sources, including patent...

    Authors: Bowen Tang, Zhangming Niu, Xiaofeng Wang, Junjie Huang, Chao Ma, Jing Peng, Yinghui Jiang, Ruiquan Ge, Hongyu Hu, Luhao Lin and Guang Yang
    Citation: Journal of Cheminformatics 2024 16:29
  33. Computational methods such as molecular docking or molecular dynamics (MD) simulations have been developed to simulate and explore the interactions between biomolecules. However, the interactions obtained usin...

    Authors: Sabrina Jaeger-Honz, Karsten Klein and Falk Schreiber
    Citation: Journal of Cheminformatics 2024 16:28
  34. For understanding a chemical compound’s mechanism of action and its side effects, as well as for drug discovery, it is crucial to predict its possible protein targets. This study examines 15 developed target-c...

    Authors: Karina Jimenes-Vargas, Alejandro Pazos, Cristian R. Munteanu, Yunierkis Perez-Castillo and Eduardo Tejera
    Citation: Journal of Cheminformatics 2024 16:27
  35. Cosolvent molecular dynamics (MD) simulations are molecular dynamics simulations used to identify preferable locations of small organic fragments on a protein target. Most cosolvent molecular dynamics workflow...

    Authors: Olivier Beyens and Hans De Winter
    Citation: Journal of Cheminformatics 2024 16:23
  36. The conversion of chemical structures into computer-readable descriptors, able to capture key structural aspects, is of pivotal importance in the field of cheminformatics and computer-aided drug design. Molecu...

    Authors: Candida Manelfi, Valerio Tazzari, Filippo Lunghini, Carmen Cerchia, Anna Fava, Alessandro Pedretti, Pieter F. W. Stouten, Giulio Vistoli and Andrea Rosario Beccari
    Citation: Journal of Cheminformatics 2024 16:21