Skip to main content

Articles

Page 1 of 24

  1. Unpredicted drug safety issues constitute the majority of failures in the pharmaceutical industry according to several studies. Some of these preclinical safety issues could be attributed to the non-selective ...

    Authors: Doha Naga, Wolfgang Muster, Eunice Musvasva and Gerhard F. Ecker
    Citation: Journal of Cheminformatics 2022 14:27
  2. Chemical structure generators are used in cheminformatics to produce or enumerate virtual molecules based on a set of boundary conditions. The result can then be tested for properties of interest, such as adhe...

    Authors: Brendan D. McKay, Mehmet Aziz Yirik and Christoph Steinbeck
    Citation: Journal of Cheminformatics 2022 14:24
  3. Drug–drug interaction (DDI) often causes serious adverse reactions and thus results in inestimable economic and social loss. Currently, comprehensive DDI evaluation has become a major challenge in pharmaceutic...

    Authors: Ning-Ning Wang, Xiang-Gui Wang, Guo-Li Xiong, Zi-Yi Yang, Ai-Ping Lu, Xiang Chen, Shao Liu, Ting-Jun Hou and Dong-Sheng Cao
    Citation: Journal of Cheminformatics 2022 14:23
  4. We present several workflows for protein-ligand docking and free energy calculation for use in the workflow management system Galaxy. The workflows are composed of several widely used open-source tools, includ...

    Authors: Simon Bray, Tim Dudgeon, Rachael Skyner, Rolf Backofen, Björn Grüning and Frank von Delft
    Citation: Journal of Cheminformatics 2022 14:22
  5. The introduction of machine learning to small molecule research– an inherently multidisciplinary field in which chemists and data scientists combine their expertise and collaborate - has been vital to making s...

    Authors: Christina Humer, Henry Heberle, Floriane Montanari, Thomas Wolf, Florian Huber, Ryan Henderson, Julian Heinrich and Marc Streit
    Citation: Journal of Cheminformatics 2022 14:21
  6. Chemical space exploration is a major task of the hit-finding process during the pursuit of novel chemical entities. Compared with other screening technologies, computational de novo design has become a popula...

    Authors: Chong Lu, Shien Liu, Weihua Shi, Jun Yu, Zhou Zhou, Xiaoxiao Zhang, Xiaoli Lu, Faji Cai, Ning Xia and Yikai Wang
    Citation: Journal of Cheminformatics 2022 14:19
  7. Molecular optimization aims to improve the drug profile of a starting molecule. It is a fundamental problem in drug discovery but challenging due to (i) the requirement of simultaneous optimization of multiple...

    Authors: Jiazhen He, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Atanas Patronov, Esben Jannik Bjerrum and Ola Engkvist
    Citation: Journal of Cheminformatics 2022 14:18
  8. Structure-based drug repositioning has emerged as a promising alternative to conventional drug development. Regardless of the many success stories reported over the past years and the novel breakthroughs on th...

    Authors: Melissa F. Adasme, Sarah Naomi Bolz, Ali Al-Fatlawi and Michael Schroeder
    Citation: Journal of Cheminformatics 2022 14:17
  9. The Janus kinase (JAK) family plays a pivotal role in most cytokine-mediated inflammatory and autoimmune responses via JAK/STAT signaling, and administration of JAK inhibitors is a promising therapeutic strate...

    Authors: Yimeng Wang, Yaxin Gu, Chaofeng Lou, Yuning Gong, Zengrui Wu, Weihua Li, Yun Tang and Guixia Liu
    Citation: Journal of Cheminformatics 2022 14:16
  10. Drug-target binding affinity (DTA) reflects the strength of the drug-target interaction; therefore, predicting the DTA can considerably benefit drug discovery by narrowing the search space and pruning drug-tar...

    Authors: Junjie Wang, NaiFeng Wen, Chunyu Wang, Lingling Zhao and Liang Cheng
    Citation: Journal of Cheminformatics 2022 14:14
  11. Chemical–genetic interaction profiling is a genetic approach that quantifies the susceptibility of a set of mutants depleted in specific gene product(s) to a set of chemical compounds. With the recent advances...

    Authors: Chengyou Liu, Andrew M. Hogan, Hunter Sturm, Mohd Wasif Khan, Md. Mohaiminul Islam, A. S. M. Zisanur Rahman, Rebecca Davis, Silvia T. Cardona and Pingzhao Hu
    Citation: Journal of Cheminformatics 2022 14:12
  12. Graph based methods are increasingly important in chemistry and drug discovery, with applications ranging from QSAR to molecular generation. Combining graph neural networks and deep metric learning concepts, w...

    Authors: Damien E. Coupry and Peter Pogány
    Citation: Journal of Cheminformatics 2022 14:11
  13. Deep learning’s automatic feature extraction has been a revolutionary addition to computational drug discovery, infusing both the capabilities of learning abstract features and discovering complex molecular pa...

    Authors: Arash Keshavarzi Arshadi, Milad Salem, Arash Firouzbakht and Jiann Shiun Yuan
    Citation: Journal of Cheminformatics 2022 14:10
  14. A key concept in drug design is how natural variants, especially the ones occurring in the binding site of drug targets, affect the inter-individual drug response and efficacy by altering binding affinity. The...

    Authors: Ammar Ammar, Rachel Cavill, Chris Evelo and Egon Willighagen
    Citation: Journal of Cheminformatics 2022 14:8
  15. In this work we explore the properties which make many real-life global optimization problems extremely difficult to handle, and some of the common techniques used in literature to address them. We then introd...

    Authors: Michael Freitas Gustavo and Toon Verstraelen
    Citation: Journal of Cheminformatics 2022 14:7
  16. 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
  17. 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
  18. 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
  19. 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

  20. 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
  21. 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
  22. 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
  23. 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
  24. 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
  25. 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
  26. 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
  27. 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
  28. 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
  29. 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
  30. 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
  31. 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
  32. 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
  33. 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
  34. 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
  35. 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
  36. 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
  37. 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
  38. 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
BMC is part of Springer Nature

Annual Journal Metrics

  • Speed (average)
    47 days to first decision for reviewed manuscripts only
    32 days to first decision for all manuscripts
    124 days from submission to acceptance
    16 days from acceptance to publication

    Usage 
    760,938 downloads
    1567 Altmetric mentions

    Citations
    Click here to see citation distribution in recent years