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  1. In untargeted metabolomics, structures of small molecules are annotated using liquid chromatography-mass spectrometry by leveraging information from the molecular retention time (RT) in the chromatogram and m/z (...

    Authors: Yuting Liu, Akiyasu C. Yoshizawa, Yiwei Ling and Shujiro Okuda
    Citation: Journal of Cheminformatics 2024 16:113
  2. Focused screening on target-prioritized compound sets can be an efficient alternative to high throughput screening (HTS). For most biomolecular targets, compound prioritization models depend on prior screening...

    Authors: Sejal Sharma, Liping Feng, Nicha Boonpattrawong, Arvinder Kapur, Lisa Barroilhet, Manish S. Patankar and Spencer S. Ericksen
    Citation: Journal of Cheminformatics 2024 16:112
  3. Bitter taste is an unpleasant taste modality that affects food consumption. Bitter peptides are generated during enzymatic processes that produce functional, bioactive protein hydrolysates or during the aging ...

    Authors: Prashant Srivastava, Alexandra Steuer, Francesco Ferri, Alessandro Nicoli, Kristian Schultz, Saptarshi Bej, Antonella Di Pizio and Olaf Wolkenhauer
    Citation: Journal of Cheminformatics 2024 16:111
  4. This paper proposes a novel multi-view ensemble predictor model that is designed to address the challenge of determining synergistic drug combinations by predicting both the synergy score value values and syne...

    Authors: Samar Monem, Aboul Ella Hassanien and Alaa H. Abdel-Hamid
    Citation: Journal of Cheminformatics 2024 16:110
  5. Nuclear receptors (NRs) play a crucial role as biological targets in drug discovery. However, determining which compounds can act as endocrine disruptors and modulate the function of NRs with a reduced amount ...

    Authors: Luis H. M. Torres, Joel P. Arrais and Bernardete Ribeiro
    Citation: Journal of Cheminformatics 2024 16:109
  6. The identification, establishment, and exploration of potential pharmacological drug targets are major steps of the drug development pipeline. Target validation requires diverse chemical tools that come with a...

    Authors: Sven Marcel Stefan, Katja Stefan and Vigneshwaran Namasivayam
    Citation: Journal of Cheminformatics 2024 16:108
  7. Despite recent advancement in 3D molecule conformation generation driven by diffusion models, its high computational cost in iterative diffusion/denoising process limits its application. Here, an equivariant c...

    Authors: Zhiguang Fan, Yuedong Yang, Mingyuan Xu and Hongming Chen
    Citation: Journal of Cheminformatics 2024 16:107
  8. Natural products are molecules that fulfil a range of important ecological functions. Many natural products have been exploited for pharmaceutical and agricultural applications. In contrast to many other speci...

    Authors: Barbara R. Terlouw, Friederike Biermann, Sophie P. J. M. Vromans, Elham Zamani, Eric J. N. Helfrich and Marnix H. Medema
    Citation: Journal of Cheminformatics 2024 16:106
  9. Ion Mobility coupled with Mass Spectrometry (IM-MS) is a promising analytical technique that enhances molecular characterization by measuring collision cross-section (CCS) values, which are indicative of the m...

    Authors: Chloe Engler Hart, António José Preto, Shaurya Chanana, David Healey, Tobias Kind and Daniel Domingo-Fernández
    Citation: Journal of Cheminformatics 2024 16:105
  10. Molecular fragmentation is an effective suite of approaches to reduce the formal computational complexity of quantum chemistry calculations while enhancing their algorithmic parallelisability. However, the pra...

    Authors: Fiona C. Y. Yu, Jorge L. Gálvez Vallejo and Giuseppe M. J. Barca
    Citation: Journal of Cheminformatics 2024 16:102
  11. With the increased availability of chemical data in public databases, innovative techniques and algorithms have emerged for the analysis, exploration, visualization, and extraction of information from these da...

    Authors: José T. Moreira-Filho, Dhruv Ranganath, Mike Conway, Charles Schmitt, Nicole Kleinstreuer and Kamel Mansouri
    Citation: Journal of Cheminformatics 2024 16:101
  12. One challenge that current de novo drug design models face is a disparity between the user’s expectations and the actual output of the model in practical applications. Tailoring models to better align with che...

    Authors: Janosch Menke, Yasmine Nahal, Esben Jannik Bjerrum, Mikhail Kabeshov, Samuel Kaski and Ola Engkvist
    Citation: Journal of Cheminformatics 2024 16:100
  13. Chemical engineers heavily rely on precise knowledge of physicochemical properties to model chemical processes. Despite the growing popularity of deep learning, it is only rarely applied for property predictio...

    Authors: Maarten R. Dobbelaere, István Lengyel, Christian V. Stevens and Kevin M. Van Geem
    Citation: Journal of Cheminformatics 2024 16:99
  14. The performance of molecular docking can be improved by comparing the shape similarity of the flexibly sampled poses against the target proteins’ inverted binding cavities. The effectiveness of these pseudo-li...

    Authors: Paola Moyano-Gómez, Jukka V. Lehtonen, Olli T. Pentikäinen and Pekka A. Postila
    Citation: Journal of Cheminformatics 2024 16:97
  15. An automated pipeline for comprehensive calculation of intermolecular interaction energies based on molecular force-fields using the Tinker molecular modelling package is presented. Starting with non-optimized...

    Authors: Felix Bänsch, Mirco Daniel, Harald Lanig, Christoph Steinbeck and Achim Zielesny
    Citation: Journal of Cheminformatics 2024 16:96
  16. Designing compounds with a range of desirable properties is a fundamental challenge in drug discovery. In pre-clinical early drug discovery, novel compounds are often designed based on an already existing prom...

    Authors: Jiazhen He, Alessandro Tibo, Jon Paul Janet, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky and Ola Engkvist
    Citation: Journal of Cheminformatics 2024 16:95
  17. In recent years, significant advancements have been made in molecular generation algorithms aimed at facilitating drug development, and molecular diversity holds paramount importance within the realm of molecu...

    Authors: Xiuyuan Hu, Guoqing Liu, Quanming Yao, Yang Zhao and Hao Zhang
    Citation: Journal of Cheminformatics 2024 16:94
  18. enviPath is a widely used database and prediction system for microbial biotransformation pathways of primarily xenobiotic compounds. Data and prediction system are freely available both via a web interface and...

    Authors: Jasmin Hafner, Tim Lorsbach, Sebastian Schmidt, Liam Brydon, Katharina Dost, Kunyang Zhang, Kathrin Fenner and Jörg Wicker
    Citation: Journal of Cheminformatics 2024 16:93
  19. Protein language models (PLMs) play a dominant role in protein representation learning. Most existing PLMs regard proteins as sequences of 20 natural amino acids. The problem with this representation method is...

    Authors: Yang Tan, Mingchen Li, Ziyi Zhou, Pan Tan, Huiqun Yu, Guisheng Fan and Liang Hong
    Citation: Journal of Cheminformatics 2024 16:92
  20. Data scarcity is one of the most critical issues impeding the development of prediction models for chemical effects. Multitask learning algorithms leveraging knowledge from relevant tasks showed potential for ...

    Authors: Run-Hsin Lin, Pinpin Lin, Chia-Chi Wang and Chun-Wei Tung
    Citation: Journal of Cheminformatics 2024 16:91
  21. Here, we present a new method for evaluating questions on chemical reactions in the context of remote education. This method can be used when binary grading is not sufficient as some tolerance may be acceptabl...

    Authors: Louis Plyer, Gilles Marcou, Céline Perves, Fanny Bonachera and Alexander Varnek
    Citation: Journal of Cheminformatics 2024 16:90
  22. Machine learning is becoming a preferred method for the virtual screening of organic materials due to its cost-effectiveness over traditional computationally demanding techniques. However, the scarcity of labe...

    Authors: Chengwei Zhang, Yushuang Zhai, Ziyang Gong, Hongliang Duan, Yuan-Bin She, Yun-Fang Yang and An Su
    Citation: Journal of Cheminformatics 2024 16:89
  23. Mass spectral libraries have proven to be essential for mass spectrum annotation, both for library matching and training new machine learning algorithms. A key step in training machine learning models is the a...

    Authors: Niek F. de Jonge, Helge Hecht, Michael Strobel, Mingxun Wang, Justin J. J. van der Hooft and Florian Huber
    Citation: Journal of Cheminformatics 2024 16:88
  24. Chemical space embedding methods are widely utilized in various research settings for dimensional reduction, clustering and effective visualization. The maps generated by the embedding process can provide valu...

    Authors: Gergely Zahoránszky-Kőhalmi, Kanny K. Wan and Alexander G. Godfrey
    Citation: Journal of Cheminformatics 2024 16:87
  25. Every year, more than 19 million cancer cases are diagnosed, and this number continues to increase annually. Since standard treatment options have varying success rates for different types of cancer, understan...

    Authors: Rayyan Tariq Khan, Petra Pokorna, Jan Stourac, Simeon Borko, Ihor Arefiev, Joan Planas-Iglesias, Adam Dobias, Gaspar Pinto, Veronika Szotkowska, Jaroslav Sterba, Ondrej Slaby, Jiri Damborsky, Stanislav Mazurenko and David Bednar
    Citation: Journal of Cheminformatics 2024 16:86
  26. It is well-accepted that knowledge of a small molecule’s target can accelerate optimization. Although chemogenomic databases are helpful resources for predicting or finding compound interaction partners, they ...

    Authors: Karla P. Godinez-Macias and Elizabeth A. Winzeler
    Citation: Journal of Cheminformatics 2024 16:84
  27. 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
  28. 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
  29. 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
  30. 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
  31. 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
  32. 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
  33. 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
  34. 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
  35. 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
  36. 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
  37. 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
  38. 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
  39. 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
  40. 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
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    Journal Impact Factor: 7.1
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