Evidence map›Paper›PMID 25709332›Full record

ArticleJournal of pharmacy & bioallied sciences

Prediction of anticancer property of bowsellic acid derivatives by quantitative structure activity relationship analysis and molecular docking study.

Raghunath Satpathy, R K Guru, R Behera, B Nayak

Open access · goldAbstract read
In one paragraph

Article in Journal of pharmacy & bioallied sciences. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 95% 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

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. Article
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.

Raghunath SatpathyDepartment of Biotechnology, MIRC Lab, MITS Engineering College, Rayagada, Odisha, India.
R K GuruDepartment of Biotechnology, MIRC Lab, MITS Engineering College, Rayagada, Odisha, India.
R BeheraDepartment of Biotechnology, MIRC Lab, MITS Engineering College, Rayagada, Odisha, India.
B NayakDepartment of Biotechnology, MIRC Lab, MITS Engineering College, Rayagada, Odisha, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

contextBoswellic acid consists of a series of pentacyclic triterpene molecules that are produced by the plant Boswellia serrata. The potential applications of Bowsellic acid for treatment of cancer have been focused here.

aimsTo predict the property of the bowsellic acid derivatives as anticancer compounds by various computational approaches. MATERIALS AND

methodsIn this work, all total 65 derivatives of bowsellic acids from the PubChem database were considered for the study. After energy minimization of the ligands various types of molecular descriptors were computed and corresponding two-dimensional quantitative structure activity relationship (QSAR) models were obtained by taking Andrews coefficient as the dependent variable. STATISTICAL ANALYSIS USED: Different types of comparative analysis were used for QSAR study are multiple linear regression, partial least squares, support vector machines and artificial neural network.

resultsFrom the study geometrical descriptors shows the highest correlation coefficient, which indicates the binding factor of the compound. To evaluate the anticancer property molecular docking study of six selected ligands based on Andrews affinity were performed with nuclear factor-kappa protein kinase (Protein Data Bank ID 4G3D), which is an established therapeutic target for cancers. Along with QSAR study and docking result, it was predicted that bowsellic acid can also be treated as a potential anticancer compound.

conclusionsAlong with QSAR study and docking result, it was predicted that bowsellic acid can also be treated as a potential anticancer compound.

Indexed as

Anticancer agentbowsellic aciddockingquantitative structure activity relationship studyregression equation

Identifiers

PMID25709332
PMCPMC4333623
OpenAlexW2147185219

What OpenQuestion holds

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LicenceCC BY-NC-SA
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Registered trials

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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.