Open Access
Database : the journal of biological databases and curation, volume 2019
Enhanced taxonomy annotation of antiviral activity data from ChEMBL
Nikitina Anastasia A
1, 2
,
Orlov Alexey A.
1, 2
,
Kozlovskaya Liubov I.
1, 3
,
Palyulin V. A.
2
,
Osolodkin Dmitry I.
1, 2, 3
Publication type: Journal Article
Publication date: 2019-01-01
Quartile SCImago
Q1
Quartile WOS
Q1
Impact factor: 5.8
ISSN: 17580463
PubMed ID:
30753475
General Biochemistry, Genetics and Molecular Biology
General Agricultural and Biological Sciences
Information Systems
Abstract
The discovery of antiviral drugs is a rapidly developing area of medicinal chemistry research. The emergence of resistant variants and outbreaks of poorly studied viral diseases make this area constantly developing. The amount of antiviral activity data available in ChEMBL consistently grows, but virus taxonomy annotation of these data is not sufficient for thorough studies of antiviral chemical space. We developed a procedure for semi-automatic extraction of antiviral activity data from ChEMBL and mapped them to the virus taxonomy developed by the International Committee for Taxonomy of Viruses (ICTV). The procedure is based on the lists of virus-related values of ChEMBL annotation fields and a dictionary of virus names and acronyms mapped to ICTV taxa. Application of this data extraction procedure allows retrieving from ChEMBL 1.6 times more assays linked to 2.5 times more compounds and data points than ChEMBL web interface allows. Mapping of these data to ICTV taxa allows analyzing all the compounds tested against each viral species. Activity values and structures of the compounds were standardized, and the antiviral activity profile was created for each standard structure. Data set compiled using this algorithm was called ViralChEMBL. As case studies, we compared descriptor and scaffold distributions for the full ChEMBL and its `viral' and `non-viral' subsets, identified the most studied compounds and created a self-organizing map for ViralChEMBL. Our approach to data annotation appeared to be a very efficient tool for the study of antiviral chemical space.
Citations by journals
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1
2
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Molecules
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Molecular Informatics
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Scientific Reports
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Russian Chemical Reviews
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1 publication, 5.56%
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1 publication, 5.56%
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1 publication, 5.56%
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1 publication, 5.56%
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1
2
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Citations by publishers
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1
2
3
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Multidisciplinary Digital Publishing Institute (MDPI)
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Multidisciplinary Digital Publishing Institute (MDPI)
3 publications, 16.67%
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Springer Nature
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Springer Nature
3 publications, 16.67%
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Elsevier
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Elsevier
3 publications, 16.67%
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Wiley
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Wiley
2 publications, 11.11%
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American Chemical Society (ACS)
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American Chemical Society (ACS)
1 publication, 5.56%
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Bentham Science
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Bentham Science
1 publication, 5.56%
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Frontiers Media S.A.
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Frontiers Media S.A.
1 publication, 5.56%
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Autonomous Non-profit Organization Editorial Board of the journal Uspekhi Khimii
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Autonomous Non-profit Organization Editorial Board of the journal Uspekhi Khimii
1 publication, 5.56%
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Pleiades Publishing
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Pleiades Publishing
1 publication, 5.56%
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Taylor & Francis
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Taylor & Francis
1 publication, 5.56%
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V. N. Orekhovich Research Institute of Biomedical Chemistry
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V. N. Orekhovich Research Institute of Biomedical Chemistry
1 publication, 5.56%
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1
2
3
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- We do not take into account publications that without a DOI.
- Statistics recalculated only for publications connected to researchers, organizations and labs registered on the platform.
- Statistics recalculated weekly.
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Nikitina A. A. et al. Enhanced taxonomy annotation of antiviral activity data from ChEMBL // Database : the journal of biological databases and curation. 2019. Vol. 2019.
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Nikitina A. A., Orlov A. A., Kozlovskaya L. I., Palyulin V. A., Osolodkin D. I. Enhanced taxonomy annotation of antiviral activity data from ChEMBL // Database : the journal of biological databases and curation. 2019. Vol. 2019.
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TY - JOUR
DO - 10.1093/database/bay139
UR - https://doi.org/10.1093%2Fdatabase%2Fbay139
TI - Enhanced taxonomy annotation of antiviral activity data from ChEMBL
T2 - Database : the journal of biological databases and curation
AU - Nikitina, Anastasia A
AU - Orlov, Alexey A.
AU - Kozlovskaya, Liubov I.
AU - Palyulin, V. A.
AU - Osolodkin, Dmitry I.
PY - 2019
DA - 2019/01/01 00:00:00
PB - Oxford University Press
VL - 2019
PMID - 30753475
SN - 1758-0463
ER -
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@article{2019_Nikitina,
author = {Anastasia A Nikitina and Alexey A. Orlov and Liubov I. Kozlovskaya and V. A. Palyulin and Dmitry I. Osolodkin},
title = {Enhanced taxonomy annotation of antiviral activity data from ChEMBL},
journal = {Database : the journal of biological databases and curation},
year = {2019},
volume = {2019},
publisher = {Oxford University Press},
month = {jan},
url = {https://doi.org/10.1093%2Fdatabase%2Fbay139},
doi = {10.1093/database/bay139}
}
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