Evidence map›Paper›PMID 37969663›Full record

ArticleBioinformation2023

Neurological potency of native plants from sub-Himalayan West Bengal through reverse pharmacology.

Lepcha Tshering Dhendup, Datta Sutapa, Joongku Lee, Ajmal Ali Mohammad, Arnab Sen

Abstract read
In one paragraph

Article in Bioinformation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Lepcha Tshering DhendupMolecular Genetics Laboratory, Department of Botany, University of North Bengal, Raja Rammohanpur, Siliguri-734013, India.
Datta SutapaMolecular Genetics Laboratory, Department of Botany, University of North Bengal, Raja Rammohanpur, Siliguri-734013, India.
Joongku LeeDepartment of Environmental and Forest Resources, Chungnam National University, Daehak-ro, Yuseong-gu, Daejeon, Republic of Korea.
Ajmal Ali MohammadDepartment of Botany and Microbiology, College of Sciences,King Saud University, Riyadh 11451, Saudi Arabia.
Arnab SenMolecular Genetics Laboratory, Department of Botany, University of North Bengal, Raja Rammohanpur, Siliguri-734013, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neurodegenerative diseases, such as Alzheimer's disease (AD), Parkinson's disease (PD), and epilepsy, pose a growing global health challenge due to an aging population. These conditions share common processes, including protein accumulation, oxidative stress, and neuro-inflammation, making their treatment complex and costly. Network pharmacology, an innovative approach integrating systems biology and computational biology, offers insights into multi-target formulations and the repurposing of existing medications for neurodegenerative diseases. We shortlisted 730 bioactive compounds from 25 traditional Himalayan plants, assessed their drug-like properties using ADME criteria, and predicted their potential target proteins through reverse docking and pharmacophore mapping. Our study identified 287 compounds with high gastrointestinal absorption and good blood-brain barrier permeability. These compounds were subjected to target prediction, yielding a list of 171 potential target proteins. Functional annotation and pathway enrichment analysis highlighted their involvement in steroid hormone-related pathways, MAPK signaling, FOXO signaling, TNF signaling, VEGF signaling, and neurotrophin signaling. Importantly, one plant,

Indexed as

native plantsNeurological potencyreverse pharmacologysub-Himalayan West Bengal

Identifiers

PMID37969663
PMCPMC10640792

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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.