Evidence map›Paper›PMID 39323335›Full record

ArticleCurrent computer-aided drug design2025

Maryam Khalili-Salmasi, Ahmad Nazarian, Amir Amirkhani, Hasan Mirzahoseini, Kamran Pooshang Bagheri

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Article in Current computer-aided drug design, 2025. 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
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.

  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

5 authors.

Maryam Khalili-SalmasiVenom and Biotherapeutics Molecules Laboratory, Medical Biotechnology Department, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran.
Ahmad NazarianVenom and Biotherapeutics Molecules Laboratory, Medical Biotechnology Department, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran.
Amir AmirkhaniVenom and Biotherapeutics Molecules Laboratory, Medical Biotechnology Department, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran.
Hasan MirzahoseiniVenom and Biotherapeutics Molecules Laboratory, Medical Biotechnology Department, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran.
Kamran Pooshang BagheriVenom and Biotherapeutics Molecules Laboratory, Medical Biotechnology Department, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran.ORCID 0000-0003-0125-3918

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBlocking Kv 1.2 and Kv 1.3 potassium channels using scorpion venom- derived toxins holds potential therapeutic value. These channels are implicated in autoimmune diseases such as neurodegenerative diseases, multiple sclerosis, rheumatoid arthritis, and type 1 diabetes.

objectivesThe present work aims at the discovery and in silico activity analysis of potassium channel blockers (KTxs) from the cDNA library derived from the venom gland of Iranian scorpion

methodsThe sequence regarding potassium channel blockers were extracted based on Gene Ontology for

resultsSeven H.L KTxs, designated as Leptukalin, were extracted from the cDNA library of

conclusionThree non-toxic KTxs, Leptukalin 3, 5, and 7, were successfully discovered from the cDNA library of

Indexed as

Potassium Channel BlockersScorpionsScorpion VenomsAmino Acid SequenceAnimalsAnimals, PoisonousComputer SimulationDrug DiscoveryGene LibraryHumansIranKv1.2 Potassium ChannelKv1.3 Potassium ChannelMiceMolecular Docking SimulationStructure-Activity RelationshipKv1.2 Potassium ChannelKv1.3 Potassium ChannelPotassium Channel BlockersScorpion Venomsautoimmune diseases.Hemiscorpius lepturusIn silico discoveryleptukalinpeptidespotassium channel blockersscorpionvenom

Identifiers

PMID39323335

What OpenQuestion holds

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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.