Evidence map›Paper›PMID 35624324›Full record

ArticleJournal of molecular modeling2022

In silico and in vitro study of Mycobacterium tuberculosis H37Rv uncharacterized protein (RipD): an insight on tuberculosis therapeutics.

Aregitu Mekuriaw Arega, Ajit Kumar Dhal, Sasmita Nayak, Rajani Kanta Mahapatra

Open access · hybridAbstract read
PubMed Publisher
In one paragraph

Article in Journal of molecular modeling, 2022. 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
0.3field-weighted citation impact, top 45% 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, 3 citations in OpenAlex.

  1. Review
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 2 institutions in 2 countries.

Aregitu Mekuriaw AregaSchool of Biotechnology, KIIT Deemed to Be University, Bhubaneswar, Odisha, India.
Ajit Kumar DhalSchool of Biotechnology, KIIT Deemed to Be University, Bhubaneswar, Odisha, India.
Sasmita NayakSchool of Biotechnology, KIIT Deemed to Be University, Bhubaneswar, Odisha, India.
Rajani Kanta MahapatraSchool of Biotechnology, KIIT Deemed to Be University, Bhubaneswar, Odisha, India. rmahapatra@kiibiotech.ac.in.ORCID http://orcid.org/0000-0002-3654-2421
KIIT University · INNational Veterinary Institute · ET

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tuberculosis caused by Mycobacterium tuberculosis (Mtb) is responsible for the highest global health problem, with the deaths of millions of people. With prevalence of multiple drug resistance (MDR) strains and extended therapeutic times, it is important to discover small molecule inhibitors against novel hypothetical proteins of the pathogen. In this study, a virtual screening protocol was carried out against MtbH37Rv hypothetical protein RipD (Rv1566c) for the identification of potential small molecule inhibitors. The 3D model of the protein structure binding site was used for virtual screening (VS) of inhibitors from the Pathogen Box, followed by its validation through a molecular docking study. The stability of the protein-ligand complex was assessed using a 150 ns molecular dynamics simulation. MM-PBSA and MM-GBSA are the two approaches that were used to perform the trajectory analysis and determine the binding free energies, respectively. The ligand binding was observed to be stable across the entire time frame with an approximate binding free energy of -22.9916 kcal/mol. The drug-likeness of the inhibitors along with a potential anti-tuberculosis compound was validated by ADMET prediction software. Furthermore, a CFU inhibition assay was used to validate the best hit compound's in vitro inhibitory efficacy against a non-pathogenic Mycobacterium smegmatis MC2155 under low nutrient culture conditions. The study reported that the compound proposed in our study (Pathogen Box ID: MMV687700) will be useful for the identification of potential inhibitors against Mtb in future.

Indexed as

Mycobacterium tuberculosisTuberculosisHumansLigandsMolecular Docking SimulationMolecular Dynamics SimulationLigandsIn vitro inhibition assayMM-PB/GBSA approachMolecular dynamics simulationsTuberculosis, Hypothetical proteinVirtual screening

Identifiers

PMID35624324
OpenAlexW4281732394

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.