Evidence map›Paper›PMID 34747471›Full record

ArticleNucleic acids research2022

VARIDT 2.0: structural variability of drug transporter.

Tingting Fu, Fengcheng Li, Yang Zhang, Jiayi Yin, Wenqi Qiu, Xuedong Li, Xingang Liu, Wenwen Xin, Chengzhao Wang, Lushan Yu and 4 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed.

  1. Article
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  4. Review
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  6. Article
  7. ISTransbase: an online database for inhibitor and substrate of drug transporters.Database : the journal of biological databases and curation · 2024
    Article
  8. Article
  9. Article
  10. INTEDE 2.0: the metabolic roadmap of drugs.Nucleic acids research · 2024
    Article
  11. Article
  12. Article
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  14. Article
  15. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Tingting FuCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Fengcheng LiCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Yang ZhangDepartment of Pharmacology, Hebei Medical University, Shijiazhuang 050017, China.
Jiayi YinCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Wenqi QiuDepartment of Surgery, HKU-SZH & Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
Xuedong LiDepartment of Pharmacology, Hebei Medical University, Shijiazhuang 050017, China.
Xingang LiuDepartment of Pharmacology, Hebei Medical University, Shijiazhuang 050017, China.
Wenwen XinDepartment of Pharmacology, Hebei Medical University, Shijiazhuang 050017, China.
Chengzhao WangDepartment of Pharmacology, Hebei Medical University, Shijiazhuang 050017, China.
Lushan YuCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Jianqing GaoCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Qingchuan ZhengInstitute of Theoretical Chemistry, College of Chemistry, Jilin University, Changchun 130023, China.
Su ZengCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Feng ZhuCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.ORCID 0000-0001-8069-0053

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The structural variability data of drug transporter (DT) are key for research on precision medicine and rational drug use. However, these valuable data are not sufficiently covered by the available databases. In this study, a major update of VARIDT (a database previously constructed to provide DTs' variability data) was thus described. First, the experimentally resolved structures of all DTs reported in the original VARIDT were discovered from PubMed and Protein Data Bank. Second, the structural variability data of each DT were collected by literature review, which included: (a) mutation-induced spatial variations in folded state, (b) difference among DT structures of human and model organisms, (c) outward/inward-facing DT conformations and (d) xenobiotics-driven alterations in the 3D complexes. Third, for those DTs without experimentally resolved structural variabilities, homology modeling was further applied as well-established protocol to enrich such valuable data. As a result, 145 mutation-induced spatial variations of 42 DTs, 1622 inter-species structures originating from 292 DTs, 118 outward/inward-facing conformations belonging to 59 DTs, and 822 xenobiotics-regulated structures in complex with 57 DTs were updated to VARIDT (https://idrblab.org/varidt/ and http://varidt.idrblab.net/). All in all, the newly collected structural variabilities will be indispensable for explaining drug sensitivity/selectivity, bridging preclinical research with clinical trial, revealing the mechanism underlying drug-drug interaction, and so on.

Indexed as

Databases, FactualDatabases, PharmaceuticalBiological TransportHumansMutationStructure-Activity RelationshipXenobioticsXenobiotics

Identifiers

PMID34747471
PMCPMC8728241

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.