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<p>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 <i>Acropora</i> 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 <i>Acropora digitifera</i>, 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 <i>Klebsiella pneumoniae</i>, <i>Pseudomonas aeruginosa</i>, and <i>Escherichia coli</i>. Binding free energy analysis indicated that AMP-Ad2 exhibited the most favorable interaction with the TolC channel of <i>E. coli.</i> AMP-Ad3 showed the highest binding affinity with the OprM channel of <i>P. aeruginosa</i>, while AMP-Ad15 displayed the most favorable binding energy for the TolC channel of <i>K. pneumoniae.</i> The strongest interaction overall was observed between AMP-Ad15 and the DNA gyrase B of <i>K. pneumoniae</i>. These results demonstrate the utility of in silico prediction tools for identifying AMP candidates from <i>A. digitifera</i> 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.</p>

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

  • 期刊论文

  • 发表日期：

    2025年10月30日

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

摘要

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.