Evidence map›Paper›PMID 41404124›Full record

ArticleComputational and structural biotechnology journal2025

Ankita Pal, Sapna Pal, Shweta Mahapatra, Apratim Pandey, Debasisa Mohanty

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Ankita PalBioinformatics Center, BRIC-National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110067, India.
Sapna PalBioinformatics Center, BRIC-National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110067, India.
Shweta MahapatraBioinformatics Center, BRIC-National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110067, India.
Apratim PandeyBioinformatics Center, BRIC-National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110067, India.
Debasisa MohantyBioinformatics Center, BRIC-National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110067, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The tuberculosis mutation catalogue published by World Health Organization (WHO) lists a large number of mutations based on the statistical significance of their association with resistance or susceptibility to various drugs. However, the mechanism by which they confer resistance to drugs is often not understood. To address these gaps, we combined known resistance associated mutations from the WHO catalogue and newly discovered mutations by explainable artificial intelligence (XAI). In order to decipher the mechanistic basis of drug resistance, we examined where these mutations occur in three dimensional (3D) structures of key drug targets, measured their proximity to drug binding sites and compared their abundance in drug resistant as well as drug susceptible

Indexed as

Drug resistanceExplainable artificial intelligenceFunctional analysisMolecular dockingMycobacterium tuberculosis

Identifiers

PMID41404124
PMCPMC12703862

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.