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  1. Drug repositioning is the process of identifying novel therapeutic potentials for existing drugs and discovering therapies for untreated diseases. Drug repositioning, therefore, plays an important role in opti...

    Authors: Tamer N. Jarada, Jon G. Rokne and Reda Alhajj

    Citation: Journal of Cheminformatics 2020 12:46

    Content type: Review

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  2. Mass spectrometry imaging (MSI) has become a mature, widespread analytical technique to perform non-targeted spatial metabolomics. However, the compounds used to promote desorption and ionization of the analyt...

    Authors: Gerard Baquer, Lluc Sementé, María García-Altares, Young Jin Lee, Pierre Chaurand, Xavier Correig and Pere Ràfols

    Citation: Journal of Cheminformatics 2020 12:45

    Content type: Research article

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  3. In silico prediction of drug–target interactions is a critical phase in the sustainable drug development process, especially when the research focus is to capitalize on the repositioning of existing drugs. How...

    Authors: Maha A. Thafar, Rawan S. Olayan, Haitham Ashoor, Somayah Albaradei, Vladimir B. Bajic, Xin Gao, Takashi Gojobori and Magbubah Essack

    Citation: Journal of Cheminformatics 2020 12:44

    Content type: Research article

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  4. With the rise of artificial intelligence (AI) in drug discovery, de novo molecular generation provides new ways to explore chemical space. However, because de novo molecular generation methods rely on abundant...

    Authors: Xuanyi Li, Yinqiu Xu, Hequan Yao and Kejiang Lin

    Citation: Journal of Cheminformatics 2020 12:42

    Content type: Research article

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  5. Affinity fingerprints report the activity of small molecules across a set of assays, and thus permit to gather information about the bioactivities of structurally dissimilar compounds, where models based on ch...

    Authors: Isidro Cortés-Ciriano, Ctibor Škuta, Andreas Bender and Daniel Svozil

    Citation: Journal of Cheminformatics 2020 12:41

    Content type: Research article

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  6. Here, we introduce the ChemicalToolbox, a publicly available web server for performing cheminformatics analysis. The ChemicalToolbox provides an intuitive, graphical interface for common tools for downloading,...

    Authors: Simon A. Bray, Xavier Lucas, Anup Kumar and Björn A. Grüning

    Citation: Journal of Cheminformatics 2020 12:40

    Content type: Software

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  7. An affinity fingerprint is the vector consisting of compound’s affinity or potency against the reference panel of protein targets. Here, we present the QAFFP fingerprint, 440 elements long in silico QSAR-based...

    Authors: C. Škuta, I. Cortés-Ciriano, W. Dehaen, P. Kříž, G. J. P. van Westen, I. V. Tetko, A. Bender and D. Svozil

    Citation: Journal of Cheminformatics 2020 12:39

    Content type: Research article

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  8. Molecular generative models trained with small sets of molecules represented as SMILES strings can generate large regions of the chemical space. Unfortunately, due to the sequential nature of SMILES strings, t...

    Authors: Josep Arús-Pous, Atanas Patronov, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen and Ola Engkvist

    Citation: Journal of Cheminformatics 2020 12:38

    Content type: Research article

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  9. For kinase inhibitors, X-ray crystallography has revealed different types of binding modes. Currently, more than 2000 kinase inhibitors with known binding modes are available, which makes it possible to derive...

    Authors: Raquel Rodríguez-Pérez, Filip Miljković and Jürgen Bajorath

    Citation: Journal of Cheminformatics 2020 12:36

    Content type: Research article

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  10. The development of drugs is often hampered due to off-target interactions leading to adverse effects. Therefore, computational methods to assess the selectivity of ligands are of high interest. Currently, sele...

    Authors: Lindsey Burggraaff, Herman W. T. van Vlijmen, Adriaan P. IJzerman and Gerard J. P. van Westen

    Citation: Journal of Cheminformatics 2020 12:33

    Content type: Research article

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  11. Deep learning is developing as an important technology to perform various tasks in cheminformatics. In particular, graph convolutional neural networks (GCNs) have been reported to perform well in many types of...

    Authors: Ryosuke Kojima, Shoichi Ishida, Masateru Ohta, Hiroaki Iwata, Teruki Honma and Yasushi Okuno

    Citation: Journal of Cheminformatics 2020 12:32

    Content type: Software

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  12. The spectroscopy of diatomic molecules is an important research area in chemical physics due to its relevance in astrochemistry, combustion chemistry, and ultracold physics. However, there is currently no data...

    Authors: Xiangyue Liu, Stefan Truppe, Gerard Meijer and Jesús Pérez-Ríos

    Citation: Journal of Cheminformatics 2020 12:31

    Content type: Database

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  13. Aromatic rings are important residues for biological interactions and appear to a large extent as part of protein–drug and protein–protein interactions. They are relevant for both protein stability and molecul...

    Authors: Esteban Lanzarotti, Lucas A. Defelipe, Marcelo A. Marti and Adrián G. Turjanski

    Citation: Journal of Cheminformatics 2020 12:30

    Content type: Research article

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  14. MFsim is an open Java all-in-one rich-client computing environment for mesoscopic simulation with Jdpd as its default simulation kernel for Molecular Fragment (Dissipative Particle) Dynamics. The new environme...

    Authors: Karina van den Broek, Mirco Daniel, Matthias Epple, Jan-Mathis Hein, Hubert Kuhn, Stefan Neumann, Andreas Truszkowski and Achim Zielesny

    Citation: Journal of Cheminformatics 2020 12:29

    Content type: Software

    Published on:

  15. Artificial intelligence (AI) is undergoing a revolution thanks to the breakthroughs of machine learning algorithms in computer vision, speech recognition, natural language processing and generative modelling. ...

    Authors: Noé Sturm, Andreas Mayr, Thanh Le Van, Vladimir Chupakhin, Hugo Ceulemans, Joerg Wegner, Jose-Felipe Golib-Dzib, Nina Jeliazkova, Yves Vandriessche, Stanislav Böhm, Vojtech Cima, Jan Martinovic, Nigel Greene, Tom Vander Aa, Thomas J. Ashby, Sepp Hochreiter…

    Citation: Journal of Cheminformatics 2020 12:26

    Content type: Research article

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  16. Risk assessment of newly synthesised chemicals is a prerequisite for regulatory approval. In this context, in silico methods have great potential to reduce time, cost, and ultimately animal testing as they mak...

    Authors: Andrea Morger, Miriam Mathea, Janosch H. Achenbach, Antje Wolf, Roland Buesen, Klaus-Juergen Schleifer, Robert Landsiedel and Andrea Volkamer

    Citation: Journal of Cheminformatics 2020 12:24

    Content type: Research article

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  17. We report on a new cheminformatics enumeration technology—SIME, synthetic insight-based macrolide enumerator—a new and improved software technology. SIME can enumerate fully assembled macrolides with synthetic...

    Authors: Phyo Phyo Kyaw Zin, Gavin Williams and Denis Fourches

    Citation: Journal of Cheminformatics 2020 12:23

    Content type: Research article

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  18. Recurrent neural networks have been widely used to generate millions of de novo molecules in defined chemical spaces. Reported deep generative models are exclusively based on LSTM and/or GRU units and frequent...

    Authors: Ruud van Deursen, Peter Ertl, Igor V. Tetko and Guillaume Godin

    Citation: Journal of Cheminformatics 2020 12:22

    Content type: Research article

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  19. Over the last few decades, chemists have become skilled at designing compounds that avoid cytochrome P (CYP) 450 mediated metabolism. Typical screening assays are performed in liver microsomal fractions and it...

    Authors: Pranav Shah, Vishal B. Siramshetty, Alexey V. Zakharov, Noel T. Southall, Xin Xu and Dac-Trung Nguyen

    Citation: Journal of Cheminformatics 2020 12:21

    Content type: Research article

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  20. Ensemble learning helps improve machine learning results by combining several models and allows the production of better predictive performance compared to a single model. It also benefits and accelerates the ...

    Authors: Chia-Hsiu Chen, Kenichi Tanaka, Masaaki Kotera and Kimito Funatsu

    Citation: Journal of Cheminformatics 2020 12:19

    Content type: Research article

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  21. Training neural networks with small and imbalanced datasets often leads to overfitting and disregard of the minority class. For predictive toxicology, however, models with a good balance between sensitivity an...

    Authors: Jennifer Hemmerich, Ece Asilar and Gerhard F. Ecker

    Citation: Journal of Cheminformatics 2020 12:18

    Content type: Research article

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  22. We present SMILES-embeddings derived from the internal encoder state of a Transformer [1] model trained to canonize SMILES as a Seq2Seq problem. Using a CharNN [2] architecture upon the embeddings results in high...

    Authors: Pavel Karpov, Guillaume Godin and Igor V. Tetko

    Citation: Journal of Cheminformatics 2020 12:17

    Content type: Research article

    Published on:

  23. Breast cancer resistance protein (BCRP/ABCG2), an ATP-binding cassette (ABC) efflux transporter, plays a critical role in multi-drug resistance (MDR) to anti-cancer drugs and drug–drug interactions. The predic...

    Authors: Dejun Jiang, Tailong Lei, Zhe Wang, Chao Shen, Dongsheng Cao and Tingjun Hou

    Citation: Journal of Cheminformatics 2020 12:16

    Content type: Research article

    Published on:

  24. Efficient and accurate prediction of molecular properties, such as lipophilicity and solubility, is highly desirable for rational compound design in chemical and pharmaceutical industries. To this end, we buil...

    Authors: Bowen Tang, Skyler T. Kramer, Meijuan Fang, Yingkun Qiu, Zhen Wu and Dong Xu

    Citation: Journal of Cheminformatics 2020 12:15

    Content type: Research article

    Published on:

  25. It was highlighted that the original article [1] contained an error in the last paragraph of the section ‘Structure search using SPARQL’, specifically in the radius of the used fingerprint. This Correction art...

    Authors: Miroslav Kratochvíl, Jiří Vondrášek and Jakub Galgonek

    Citation: Journal of Cheminformatics 2020 12:13

    Content type: Correction

    Published on:

    The original article was published in Journal of Cheminformatics 2019 11:45

  26. The reproducibility of experiments has been a long standing impediment for further scientific progress. Computational methods have been instrumental in drug discovery efforts owing to its multifaceted utilizat...

    Authors: Nalini Schaduangrat, Samuel Lampa, Saw Simeon, Matthew Paul Gleeson, Ola Spjuth and Chanin Nantasenamat

    Citation: Journal of Cheminformatics 2020 12:9

    Content type: Review

    Published on:

  27. The increasing number of organic and inorganic structures promotes the development of the “Big Data” in chemistry and material science, and raises the need for cross-platform and web-based methods to search, v...

    Authors: Pin Chen, Yu Wang, Hui Yan, Sen Gao, Zexin Xu, Yangzhong Li, Qing Mo, Junkang Huang, Jun Tao, GeChuanqi Pan, Jiahui Li and Yunfei Du

    Citation: Journal of Cheminformatics 2020 12:7

    Content type: Software

    Published on:

  28. Computer-aided research on the relationship between molecular structures of natural compounds (NC) and their biological activities have been carried out extensively because the molecular structures of new drug...

    Authors: Myungwon Seo, Hyun Kil Shin, Yoochan Myung, Sungbo Hwang and Kyoung Tai No

    Citation: Journal of Cheminformatics 2020 12:6

    Content type: Methodology

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  29. Drug discovery investigations need to incorporate network pharmacology concepts while navigating the complex landscape of drug-target and target-target interactions. This task requires solutions that integrate...

    Authors: Gergely Zahoránszky-Kőhalmi, Timothy Sheils and Tudor I. Oprea

    Citation: Journal of Cheminformatics 2020 12:5

    Content type: Research article

    Published on:

  30. Designing a molecule with desired properties is one of the biggest challenges in drug development, as it requires optimization of chemical compound structures with respect to many complex properties. To improv...

    Authors: Łukasz Maziarka, Agnieszka Pocha, Jan Kaczmarczyk, Krzysztof Rataj, Tomasz Danel and Michał Warchoł

    Citation: Journal of Cheminformatics 2020 12:2

    Content type: Research article

    Published on:

  31. Neural Message Passing for graphs is a promising and relatively recent approach for applying Machine Learning to networked data. As molecules can be described intrinsically as a molecular graph, it makes sense...

    Authors: M. Withnall, E. Lindelöf, O. Engkvist and H. Chen

    Citation: Journal of Cheminformatics 2020 12:1

    Content type: Research article

    Published on:

  32. The problem of drug side effects is one of the most crucial issues in pharmacological development. As there are many limitations in current experimental and clinical methods for detecting side effects, a lot o...

    Authors: Xujun Liang, Pengfei Zhang, Jun Li, Ying Fu, Lingzhi Qu, Yongheng Chen and Zhuchu Chen

    Citation: Journal of Cheminformatics 2019 11:79

    Content type: Research article

    Published on:

  33. We developed ChemScanner, a software that can be used for the extraction of chemical information from ChemDraw binary (CDX) or ChemDraw XML-based (CDXML) files and to retrieve the ChemDraw scheme from DOC, DOCX o...

    Authors: An Nguyen, Yu-Chieh Huang, Pierre Tremouilhac, Nicole Jung and Stefan Bräse

    Citation: Journal of Cheminformatics 2019 11:77

    Content type: Software

    Published on:

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