Evidence map›Paper›PMID 40920253›Full record

ArticleArchives of microbiology2025

Integrated machine learning, molecular dynamics, and DFT-based approach to elucidate the inhibitory effect of Ciprofloxacin analogues against fluoroquinolone-resistant Salmonella Typhi.

Romita Guchhait, Sudha Ramaiah

Abstract read
PubMed Publisher
In one paragraph

Article in Archives of microbiology, 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

2 authors.

Romita GuchhaitMedical and Biological Computing Laboratory, School of Biosciences and Technology (SBST), Vellore Institute of Technology (VIT), Vellore, 632014, India.ORCID http://orcid.org/0009-0006-8494-0199
Sudha RamaiahMedical and Biological Computing Laboratory, School of Biosciences and Technology (SBST), Vellore Institute of Technology (VIT), Vellore, 632014, India. sudhaanand@vit.ac.in.ORCID http://orcid.org/0000-0002-4800-329X

Funding

Indian Council of Medical Research IRIS ID: 2021-11889; AMR/Adhoc/290/2022-ECD-II
6 · The paper itself

Abstract

Salmonella enterica serovar Typhi, the etiological agent of Typhoid fever, remains a critical public health concern associated with high morbidity in many developing countries. The widespread emergence of multidrug-resistant (MDR) Salmonella Typhi strains against the fluoroquinolone group of antibiotics, particularly ciprofloxacin, poses a significant global therapeutic challenge with underlying resistance due to mutations in quinolone-resistance determining region (QRDR) of gyrA gene, encoding DNA gyrase subunit A (GyrA). In pursuit of alternative therapeutic candidates, the present study was designed to evaluate ciprofloxacin analogues against prevalent GyrA mutations (S83F, D87G, and D87N) to overcome fluoroquinolone resistance through machine learning (ML)-based approach. Based on Decision table algorithm with 78% predictive accuracy, 354 potential active ciprofloxacin analogues were identified from a dataset of 400 compounds. Following molecular docking against each mutant variant, top 10 analogues were screened out based on their higher binding affinity than the reference compound, from which 8 compounds revealed acceptable drug-likeness and ADMET properties. Notably, two analogue compounds (C1) and (C5) exhibited highest average binding affinities of -34.17 kJ/mol and -33.61 kJ/mol, respectively. These compounds further yielded validatory results in molecular dynamics (MD) simulation and binding-free energy analysis using Molecular mechanics/Poisson-Boltzmann surface area. Density functional theory (DFT) study of both the compounds indicated least HOMO-LUMO energy gaps, implying enhanced chemical reactivity. Additionally, MEP (Molecular electrostatic potential) surface mapping and Fukui function analysis revealed key reactive regions, supporting favourable binding orientations. Overall, the findings identify promising ciprofloxacin analogues as lead compounds against GyrA mutations, supporting the development of structurally optimised antimicrobial therapeutics.

Indexed as

Anti-Bacterial AgentsCiprofloxacinFluoroquinolonesSalmonella typhiBacterial ProteinsDensity Functional TheoryDNA GyraseDrug Resistance, BacterialDrug Resistance, Multiple, BacterialMachine LearningMicrobial Sensitivity TestsMolecular Docking SimulationMolecular Dynamics SimulationMutationTyphoid FeverAnti-Bacterial AgentsBacterial ProteinsCiprofloxacinDNA GyraseFluoroquinolonesDFTFluoroquinoloneMachine learningMD simulationMolecular dockingMultidrug-resistant

Identifiers

What Socratic 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 Socratic graph.