Discovery of Multitarget-Directed Ligands Against Influenza A Virus From Compound Yizhihao Through a Predictive System for Compound-Protein Interactions Article Swipe
Lvjie Xu
,
Wen Jiang
,
Hao Jia
,
Lishu Zheng
,
Jianguo Xing
,
Ailin Liu
,
Guanhua Du
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3389/fcimb.2020.00016
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3389/fcimb.2020.00016
Influenza A virus (IAV) is a threat to public health due to its high mutation rate and resistance to existing drugs. In this investigation, 15 targets selected from an influenza virus-host interaction network were successfully constructed as a multitarget virtual screening system for new drug discovery against IAV using Naïve Bayesian, recursive partitioning, and CDOCKER methods. The predictive accuracies of the models were evaluated using training sets and test sets. The system was then used to predict active constituents of Compound Yizhihao (CYZH), a Chinese medicinal compound used to treat influenza. Twenty-eight compounds with multitarget activities were selected for subsequent in vitro evaluation. Of the four compounds predicted to be active on neuraminidase (NA), chlorogenic acid, and orientin showed inhibitory activity in vitro. Linarin, sinensetin, cedar acid, isoliquiritigenin, sinigrin, luteolin, chlorogenic acid, orientin, epigoitrin, and rupestonic acid exhibited significant effects on TNF-α expression, which is almost consistent with predicted results. Results from a cytopathic effect (CPE) reduction assay revealed acacetin, indirubin, tryptanthrin, quercetin, luteolin, emodin, and apigenin had protective effects against wild-type strains of IAV. Quercetin, luteolin, and apigenin had good efficacy against resistant IAV strains in CPE reduction assays. Finally, with the aid of Gene Ontology biological process analysis, the potential mechanisms of CYZH action were revealed. In conclusion, a compound-protein interaction-prediction system was an efficient tool for the discovery of novel compounds against influenza, and the findings from CYZH provide important information for its usage and development.
Related Topics
Concepts
Apigenin
Chlorogenic acid
Luteolin
Virtual screening
Chemistry
PubChem
Acacetin
Quercetin
Pharmacology
Drug discovery
Biochemistry
Biology
Flavonoid
Antioxidant
Food science
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/fcimb.2020.00016
- OA Status
- gold
- Cited By
- 30
- References
- 34
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3005971589
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3005971589Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3389/fcimb.2020.00016Digital Object Identifier
- Title
-
Discovery of Multitarget-Directed Ligands Against Influenza A Virus From Compound Yizhihao Through a Predictive System for Compound-Protein InteractionsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-02-11Full publication date if available
- Authors
-
Lvjie Xu, Wen Jiang, Hao Jia, Lishu Zheng, Jianguo Xing, Ailin Liu, Guanhua DuList of authors in order
- Landing page
-
https://doi.org/10.3389/fcimb.2020.00016Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.3389/fcimb.2020.00016Direct OA link when available
- Concepts
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Apigenin, Chlorogenic acid, Luteolin, Virtual screening, Chemistry, PubChem, Acacetin, Quercetin, Pharmacology, Drug discovery, Biochemistry, Biology, Flavonoid, Antioxidant, Food scienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
30Total citation count in OpenAlex
- Citations by year (recent)
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2025: 3, 2024: 3, 2023: 5, 2022: 9, 2021: 7Per-year citation counts (last 5 years)
- References (count)
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34Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.revealed | 158 |
| abstract_inverted_index.selected | 26, 97 |
| abstract_inverted_index.training | 65 |
| abstract_inverted_index.Bayesian, | 50 |
| abstract_inverted_index.Influenza | 0 |
| abstract_inverted_index.acacetin, | 159 |
| abstract_inverted_index.analysis, | 199 |
| abstract_inverted_index.compounds | 92, 106, 223 |
| abstract_inverted_index.discovery | 45, 220 |
| abstract_inverted_index.efficient | 216 |
| abstract_inverted_index.evaluated | 63 |
| abstract_inverted_index.exhibited | 137 |
| abstract_inverted_index.important | 232 |
| abstract_inverted_index.influenza | 29 |
| abstract_inverted_index.luteolin, | 129, 163, 176 |
| abstract_inverted_index.medicinal | 85 |
| abstract_inverted_index.orientin, | 132 |
| abstract_inverted_index.potential | 201 |
| abstract_inverted_index.predicted | 107, 148 |
| abstract_inverted_index.recursive | 51 |
| abstract_inverted_index.reduction | 156, 188 |
| abstract_inverted_index.resistant | 183 |
| abstract_inverted_index.revealed. | 207 |
| abstract_inverted_index.screening | 40 |
| abstract_inverted_index.sinigrin, | 128 |
| abstract_inverted_index.vitro</i> | 101 |
| abstract_inverted_index.wild-type | 171 |
| abstract_inverted_index.Quercetin, | 175 |
| abstract_inverted_index.accuracies | 58 |
| abstract_inverted_index.activities | 95 |
| abstract_inverted_index.biological | 197 |
| abstract_inverted_index.consistent | 146 |
| abstract_inverted_index.cytopathic | 153 |
| abstract_inverted_index.indirubin, | 160 |
| abstract_inverted_index.influenza, | 225 |
| abstract_inverted_index.influenza. | 90 |
| abstract_inverted_index.inhibitory | 119 |
| abstract_inverted_index.mechanisms | 202 |
| abstract_inverted_index.predictive | 57 |
| abstract_inverted_index.protective | 168 |
| abstract_inverted_index.quercetin, | 162 |
| abstract_inverted_index.resistance | 17 |
| abstract_inverted_index.rupestonic | 135 |
| abstract_inverted_index.subsequent | 99 |
| abstract_inverted_index.virus-host | 30 |
| abstract_inverted_index.vitro</i>. | 122 |
| abstract_inverted_index.chlorogenic | 114, 130 |
| abstract_inverted_index.conclusion, | 209 |
| abstract_inverted_index.constructed | 35 |
| abstract_inverted_index.epigoitrin, | 133 |
| abstract_inverted_index.evaluation. | 102 |
| abstract_inverted_index.expression, | 142 |
| abstract_inverted_index.information | 233 |
| abstract_inverted_index.interaction | 31 |
| abstract_inverted_index.multitarget | 38, 94 |
| abstract_inverted_index.significant | 138 |
| abstract_inverted_index.sinensetin, | 124 |
| abstract_inverted_index.Twenty-eight | 91 |
| abstract_inverted_index.constituents | 78 |
| abstract_inverted_index.development. | 238 |
| abstract_inverted_index.successfully | 34 |
| abstract_inverted_index.neuraminidase | 112 |
| abstract_inverted_index.partitioning, | 52 |
| abstract_inverted_index.tryptanthrin, | 161 |
| abstract_inverted_index.investigation, | 23 |
| abstract_inverted_index.compound-protein | 211 |
| abstract_inverted_index.isoliquiritigenin, | 127 |
| abstract_inverted_index.interaction-prediction | 212 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 96 |
| corresponding_author_ids | https://openalex.org/A5033681865, https://openalex.org/A5101429401 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 7 |
| corresponding_institution_ids | https://openalex.org/I200296433 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.8299999833106995 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.9386449 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |