Evidence map›Paper›PMID 25187683›Full record

ArticleBioinformation2014

Virtual screening of natural inhibitors to the predicted HBx protein structure of Hepatitis B Virus using molecular docking for identification of potential lead molecules for liver cancer.

Rajesh Kumar Pathak, Mamta Baunthiyal, Gohar Taj, Anil Kumar

Open access · hybridAbstract read
In one paragraph

Article in Bioinformation, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.7field-weighted citation impact, top 16% of its field
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

6 citing papers in PubMed, 27 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Rajesh Kumar PathakDepartment of Biotechnology, G. B. Pant Engineering College, Pauri Garhwal-246194, Uttarakhand, India ; Department of Molecular Biology & Genetic Engineering, College of Basic Sciences & Humanities, G. B. Pant University of Agriculture & Technology, Pantnagar-263145, Uttarakhand, India.
Mamta BaunthiyalDepartment of Biotechnology, G. B. Pant Engineering College, Pauri Garhwal-246194, Uttarakhand, India.
Gohar TajDepartment of Molecular Biology & Genetic Engineering, College of Basic Sciences & Humanities, G. B. Pant University of Agriculture & Technology, Pantnagar-263145, Uttarakhand, India.
Anil KumarDepartment of Molecular Biology & Genetic Engineering, College of Basic Sciences & Humanities, G. B. Pant University of Agriculture & Technology, Pantnagar-263145, Uttarakhand, India.
Govind Ballabh Pant University of Agriculture and Technology · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The HBx protein in Hepatitis B Virus (HBV) is a potential target for anti-liver cancer molecules. Therefore, it is of interest to screen known natural compounds against the HBx protein using molecular docking. However, the structure of HBx is not yet known. Therefore, the predicted structure of HBx using threading in LOMET was used for docking against plant derived natural compounds (curcumin, oleanolic acid, resveratrol, bilobetin, luteoline, ellagic acid, betulinic acid and rutin) by Molegro Virtual Docker. The screening identified rutin with binding energy of -161.65 Kcal/mol. Thus, twenty derivatives of rutin were further designed and screened against HBx. These in silico experiments identified compounds rutin01 (-163.16 Kcal/mol) and rutin08 (- 165.76 Kcal/mol) for further consideration and downstream validation.

Indexed as

HBxHepatitis b virusLiver cancerMolecular dockingNatural compounds

Identifiers

PMID25187683
PMCPMC4135291
OpenAlexW2087083517

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.