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ArticleMarine biotechnology (New York, N.Y.)2025

Coral-Derived Antimicrobial Peptides Identified In Silico from Acropora digitifera Transcriptomes: Potential Candidates Against Resistant Pathogens.

Paula Tatiana Uribe-Echeverry, Mariana Sofia Candamil-Cortés, Juan Rodrigo Salazar, Héctor Alejandro Rodríguez-Cabal, Alejandro Reyes-Bermúdez, Jorge William Arboleda-Valencia

Abstract read
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Article in Marine biotechnology (New York, N.Y.), 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. 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

6 authors.

Paula Tatiana Uribe-EcheverryDoctorado en Biotecnología, Universidad Tecnológica de Pereira, 660003, Pereira, Colombia.
Mariana Sofia Candamil-CortésBiotecnología, Centro de Bioinformática y Biología Computacional de Colombia-BIOS, Ecoparque Los Yarumos, 170002, Manizales, Colombia.
Juan Rodrigo SalazarDepartamento de Sistemas Biológicos, División de Ciencias Biológicas y de la Salud, Universidad Autónoma Metropolitana, Campus Xochimilco, Ciudad de México, 04960, México.
Héctor Alejandro Rodríguez-CabalGrupo de Agrobiotecnología, Facultad de Ciencias Agrarias y Naturales, Universidad de Antioquia, 050010, Medellín, Colombia.
Alejandro Reyes-BermúdezLaboratorio de Genómica y Biología Molecular, Departamento de Biología, Facultad de Ciencias Básicas, Universidad de La Amazonia, 180001, Florencia, Colombia.
Jorge William Arboleda-ValenciaInstituto de Biología, FITOBIOL, Facultad Ciencias Exactas y Naturales, Universidad de Antioquia, Bloque 7-107, Calle, 050010, Medellin, Colombia. jwilliam.arboleda@udea.edu.co.ORCID http://orcid.org/0000-0001-6165-978X

Funding

University of Manizales call 2024 Project Code (E0601X0233)
6 · The paper itself

Abstract

Antimicrobial resistance is a serious threat to global public health and requires new therapeutic approaches. Antimicrobial peptides (AMP) are recognized as promising candidates to address antimicrobial resistance. AMP can disrupt cell membranes by increasing permeability and causing lysis, or they can also interact with intracellular targets to inhibit essential metabolic processes. The genus Acropora is regarded as a valuable source for bioprospecting antimicrobial compounds. In this study, we employed in silico analytical strategies to predict potential antibacterial activity using AMPs derived from transcriptomes of multiple life cycle stages of the coral Acropora digitifera, as well as from cultured cells originating from adult coral tissues. The analysis involved multiple sequence alignments, Hidden Markov models, machine learning algorithms, structural modeling, physicochemical property assessment, and molecular docking. From the transcriptomic data, 15 sequences with potential antimicrobial activity were identified. Five AMPs were further evaluated for their binding efficacy against the TolC and OprM protein channels of RND-type transporter proteins, as well as DNA gyrase B of Klebsiella pneumoniae, Pseudomonas aeruginosa, and Escherichia coli. Binding free energy analysis indicated that AMP-Ad2 exhibited the most favorable interaction with the TolC channel of E. coli. AMP-Ad3 showed the highest binding affinity with the OprM channel of P. aeruginosa, while AMP-Ad15 displayed the most favorable binding energy for the TolC channel of K. pneumoniae. The strongest interaction overall was observed between AMP-Ad15 and the DNA gyrase B of K. pneumoniae. These results demonstrate the utility of in silico prediction tools for identifying AMP candidates from A. digitifera transcriptomes and provide a basis for the planned synthesis and in vitro evaluation of these peptides, aiming to assess their therapeutic potential against resistant Gram-negative bacteria.

Indexed as

AnthozoaAnti-Bacterial AgentsAntimicrobial PeptidesTranscriptomeAnimalsEscherichia coliKlebsiella pneumoniaeMolecular Docking SimulationPseudomonas aeruginosaAnti-Bacterial AgentsAntimicrobial PeptidesAcropora digitiferaAntimicrobial peptidesGram-negative bacterialMolecular dockingTranscriptome

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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.