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  1. In the era of data science, data-driven algorithms have emerged as powerful platforms that can consolidate bioisosteric rules for preferential modifications on small molecules with a common molecular scaffold....

    Authors: Hadar Grimberg, Vinay S. Tiwari, Benjamin Tam, Lihi Gur-Arie, Daniela Gingold, Lea Polachek and Barak Akabayov
    Citation: Journal of Cheminformatics 2022 14:4
  2. Given an objective function that predicts key properties of a molecule, goal-directed de novo molecular design is a useful tool to identify molecules that maximize or minimize said objective function. Nonethel...

    Authors: Alan Kerstjens and Hans De Winter
    Citation: Journal of Cheminformatics 2022 14:3
  3. Human oral bioavailability (HOB) is a key factor in determining the fate of new drugs in clinical trials. HOB is conventionally measured using expensive and time-consuming experimental tests. The use of comput...

    Authors: Min Wei, Xudong Zhang, Xiaolin Pan, Bo Wang, Changge Ji, Yifei Qi and John Z. H. Zhang
    Citation: Journal of Cheminformatics 2022 14:1
  4. In this work, we introduce TorsiFlex, a user-friendly software written in Python 3 and designed to find all the torsional conformers of flexible acyclic molecules in an automatic fashion. For the mapping of the t...

    Authors: David Ferro-Costas, Irea Mosquera-Lois and Antonio Fernández-Ramos
    Citation: Journal of Cheminformatics 2021 13:100

    The Correction to this article has been published in Journal of Cheminformatics 2022 14:13

  5. The thermal shift assay (TSA)—also known as differential scanning fluorimetry (DSF), thermofluor, and Tm shift—is one of the most popular biophysical screening techniques used in fragment-based ligand discovery (...

    Authors: Errol L. G. Samuel, Secondra L. Holmes and Damian W. Young
    Citation: Journal of Cheminformatics 2021 13:99
  6. Chemical patents are a commonly used channel for disclosing novel compounds and reactions, and hence represent important resources for chemical and pharmaceutical research. Key chemical data in patents is ofte...

    Authors: Zenan Zhai, Christian Druckenbrodt, Camilo Thorne, Saber A. Akhondi, Dat Quoc Nguyen, Trevor Cohn and Karin Verspoor
    Citation: Journal of Cheminformatics 2021 13:97
  7. With the increase in applications of machine learning methods in drug design and related fields, the challenge of designing sound test sets becomes more and more prominent. The goal of this challenge is to hav...

    Authors: Jaak Simm, Lina Humbeck, Adam Zalewski, Noe Sturm, Wouter Heyndrickx, Yves Moreau, Bernd Beck and Ansgar Schuffenhauer
    Citation: Journal of Cheminformatics 2021 13:96
  8. Predicting compound–protein interactions (CPIs) is of great importance for drug discovery and repositioning, yet still challenging mainly due to the sparse nature of CPI matrixes, resulting in poor generalizat...

    Authors: Xinyu Bai and Yuxin Yin
    Citation: Journal of Cheminformatics 2021 13:95
  9. As safety is one of the most important properties of drugs, chemical toxicology prediction has received increasing attentions in the drug discovery research. Traditionally, researchers rely on in vitro and in ...

    Authors: Jiarui Chen, Yain-Whar Si, Chon-Wai Un and Shirley W. I. Siu
    Citation: Journal of Cheminformatics 2021 13:93
  10. A key challenge in the field of Quantitative Structure Activity Relationships (QSAR) is how to effectively treat experimental error in the training and evaluation of computational models. It is often assumed i...

    Authors: Scott S. Kolmar and Christopher M. Grulke
    Citation: Journal of Cheminformatics 2021 13:92
  11. With the development of advanced technologies in cell-based phenotypic screening, phenotypic drug discovery (PDD) strategies have re-emerged as promising approaches in the identification and development of nov...

    Authors: Bryan Dafniet, Natacha Cerisier, Batiste Boezio, Anaelle Clary, Pierre Ducrot, Thierry Dorval, Arnaud Gohier, David Brown, Karine Audouze and Olivier Taboureau
    Citation: Journal of Cheminformatics 2021 13:91
  12. Rationalizing the identification of hidden similarities across the repertoire of druggable protein cavities remains a major hurdle to a true proteome-wide structure-based discovery of novel drug candidates. We...

    Authors: Merveille Eguida and Didier Rognan
    Citation: Journal of Cheminformatics 2021 13:90
  13. Recently, we have released the de novo design platform REINVENT in version 2.0. This improved and extended iteration supports far more features and scoring function components, which allows bespoke and tailor-...

    Authors: Jeff Guo, Jon Paul Janet, Matthias R. Bauer, Eva Nittinger, Kathryn A. Giblin, Kostas Papadopoulos, Alexey Voronov, Atanas Patronov, Ola Engkvist and Christian Margreitter
    Citation: Journal of Cheminformatics 2021 13:89
  14. In recent years, in silico molecular design is regaining interest. To generate on a computer molecules with optimized properties, scoring functions can be coupled with a molecular generator to design novel molecu...

    Authors: Francois Berenger and Koji Tsuda
    Citation: Journal of Cheminformatics 2021 13:88
  15. Scaffold hopping is a central task of modern medicinal chemistry for rational drug design, which aims to design molecules of novel scaffolds sharing similar target biological activities toward known hit molecu...

    Authors: Shuangjia Zheng, Zengrong Lei, Haitao Ai, Hongming Chen, Daiguo Deng and Yuedong Yang
    Citation: Journal of Cheminformatics 2021 13:87
  16. In the process of drug discovery, the optimization of lead compounds has always been a challenge faced by pharmaceutical chemists. Matched molecular pair analysis (MMPA), a promising tool to efficiently extrac...

    Authors: Zi-Yi Yang, Li Fu, Ai-Ping Lu, Shao Liu, Ting-Jun Hou and Dong-Sheng Cao
    Citation: Journal of Cheminformatics 2021 13:86
  17. In polypharmacology drugs are required to bind to multiple specific targets, for example to enhance efficacy or to reduce resistance formation. Although deep learning has achieved a breakthrough in de novo des...

    Authors: Xuhan Liu, Kai Ye, Herman W. T. van Vlijmen, Michael T. M. Emmerich, Adriaan P. IJzerman and Gerard J. P. van Westen
    Citation: Journal of Cheminformatics 2021 13:85
  18. Mass spectrometry data is one of the key sources of information in many workflows in medicine and across the life sciences. Mass fragmentation spectra are generally considered to be characteristic signatures o...

    Authors: Florian Huber, Sven van der Burg, Justin J. J. van der Hooft and Lars Ridder
    Citation: Journal of Cheminformatics 2021 13:84
  19. The intelligent choice of extractants and entrainers can improve current mixture separation techniques allowing better efficiency and sustainability of chemical processes that are both used in industry and lab...

    Authors: Kyrylo Klimenko and Gonçalo V. S. M. Carrera
    Citation: Journal of Cheminformatics 2021 13:83
  20. Natural products (NPs) represent one of the most important resources for discovering new drugs. Here we asked whether NP origin can be assigned from their molecular structure in a subset of 60,171 NPs in the r...

    Authors: Alice Capecchi and Jean-Louis Reymond
    Citation: Journal of Cheminformatics 2021 13:82
  21. Structure-based drug design depends on the detailed knowledge of the three-dimensional (3D) structures of protein–ligand binding complexes, but accurate prediction of ligand-binding poses is still a major chal...

    Authors: Chao Shen, Xueping Hu, Junbo Gao, Xujun Zhang, Haiyang Zhong, Zhe Wang, Lei Xu, Yu Kang, Dongsheng Cao and Tingjun Hou
    Citation: Journal of Cheminformatics 2021 13:81
  22. We present a sequence-to-sequence machine learning model for predicting the IUPAC name of a chemical from its standard International Chemical Identifier (InChI). The model uses two stacks of transformers in an...

    Authors: Jennifer Handsel, Brian Matthews, Nicola J. Knight and Simon J. Coles
    Citation: Journal of Cheminformatics 2021 13:79
  23. Non-target screening consists in searching a sample for all present substances, suspected or unknown, with very little prior knowledge about the sample. This approach has been introduced more than a decade ago...

    Authors: Myriam Guillevic, Aurore Guillevic, Martin K. Vollmer, Paul Schlauri, Matthias Hill, Lukas Emmenegger and Stefan Reimann
    Citation: Journal of Cheminformatics 2021 13:78
  24. Chemical diversity is one of the key term when dealing with machine learning and molecular generation. This is particularly true for quantum chemical datasets. The composition of which should be done meticulou...

    Authors: Jules Leguy, Marta Glavatskikh, Thomas Cauchy and Benoit Da Mota
    Citation: Journal of Cheminformatics 2021 13:76
  25. Many contemporary cheminformatics methods, including computer-aided de novo drug design, hold promise to significantly accelerate and reduce the cost of drug discovery. Thanks to this attractive outlook, the f...

    Authors: M. Sicho, X. Liu, D. Svozil and G. J. P. van Westen
    Citation: Journal of Cheminformatics 2021 13:73
  26. Drug–target interaction (DTI) prediction is a crucial step in drug discovery and repositioning as it reduces experimental validation costs if done right. Thus, developing in-silico methods to predict potential DT...

    Authors: Maha A. Thafar, Rawan S. Olayan, Somayah Albaradei, Vladimir B. Bajic, Takashi Gojobori, Magbubah Essack and Xin Gao
    Citation: Journal of Cheminformatics 2021 13:71
  27. Reliable uncertainty quantification for statistical models is crucial in various downstream applications, especially for drug design and discovery where mistakes may incur a large amount of cost. This topic ha...

    Authors: Dingyan Wang, Jie Yu, Lifan Chen, Xutong Li, Hualiang Jiang, Kaixian Chen, Mingyue Zheng and Xiaomin Luo
    Citation: Journal of Cheminformatics 2021 13:69
  28. Natural products from traditional medicine inherit bioactivity from their source herbs. However, the pharmacological mechanism of natural products is often unclear and studied insufficiently. Pathway fingerpri...

    Authors: Feifei Guo, Chunhong Jiang, Yujie Xi, Dan Wang, Yi Zhang, Ning Xie, Yi Guan, Fangbo Zhang and Hongjun Yang
    Citation: Journal of Cheminformatics 2021 13:68
  29. Improving the accuracy of absolute energies associated with rovibronic quantum states of molecules requires accurate high-resolution spectroscopy measurements. Such experiments yield transition wavenumbers fro...

    Authors: Péter Árendás, Tibor Furtenbacher and Attila G. Császár
    Citation: Journal of Cheminformatics 2021 13:67
  30. Depicting a ligand-receptor complex via Interaction Fingerprints has been shown to be both a viable data visualization and an analysis tool. The spectrum of its applications ranges from simple visualization of...

    Authors: Stefan Mordalski, Agnieszka Wojtuch, Igor Podolak, Rafał Kurczab and Andrzej J. Bojarski
    Citation: Journal of Cheminformatics 2021 13:66
  31. We report the major conclusions of the online open-access workshop “Computational Applications in Secondary Metabolite Discovery (CAiSMD)” that took place from 08 to 10 March 2021. Invited speakers from academ...

    Authors: Fidele Ntie-Kang, Kiran K. Telukunta, Serge A. T. Fobofou, Victor Chukwudi Osamor, Samuel A. Egieyeh, Marilia Valli, Yannick Djoumbou-Feunang, Maria Sorokina, Conrad Stork, Neann Mathai, Paul Zierep, Ana L. Chávez-Hernández, Miquel Duran-Frigola, Smith B. Babiaka, Romuald Tematio Fouedjou, Donatus B. Eni…
    Citation: Journal of Cheminformatics 2021 13:64
  32. The prediction of metabolism and biotransformation pathways of xenobiotics is a highly desired tool in environmental sciences, drug discovery, and (eco)toxicology. Several systems predict single transformation...

    Authors: Jason Y. C. Tam, Tim Lorsbach, Sebastian Schmidt and Jörg S. Wicker
    Citation: Journal of Cheminformatics 2021 13:63
  33. Measurements of protein–ligand interactions have reproducibility limits due to experimental errors. Any model based on such assays will consequentially have such unavoidable errors influencing their performanc...

    Authors: Lewis H. Mervin, Maria-Anna Trapotsi, Avid M. Afzal, Ian P. Barrett, Andreas Bender and Ola Engkvist
    Citation: Journal of Cheminformatics 2021 13:62
  34. Ether-a-go-go-related gene (hERG) channel blockade by small molecules is a big concern during drug development in the pharmaceutical industry. Blockade of hERG channels may cause prolonged QT intervals that po...

    Authors: Abdul Karim, Matthew Lee, Thomas Balle and Abdul Sattar
    Citation: Journal of Cheminformatics 2021 13:60
  35. Scoring functions for the prediction of protein-ligand binding affinity have seen renewed interest in recent years when novel machine learning and deep learning methods started to consistently outperform class...

    Authors: Rocco Meli, Andrew Anighoro, Mike J. Bodkin, Garrett M. Morris and Philip C. Biggin
    Citation: Journal of Cheminformatics 2021 13:59
  36. Traditional techniques to identify macromolecular targets for drugs utilize solely the information on a query drug and a putative target. Nonetheless, the mechanisms of action of many drugs depend not only on...

    Authors: Guannan Liu, Manali Singha, Limeng Pu, Prasanga Neupane, Joseph Feinstein, Hsiao-Chun Wu, J. Ramanujam and Michal Brylinski
    Citation: Journal of Cheminformatics 2021 13:58
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