Structural modeling and in silico screening of antimicrobial peptides targeting BauE in Acinetobacter baumannii

Acinetobacter baumannii is a multidrug-resistant pathogen that relies on ATP-binding cassette (ABC) transporters for siderophore-mediated iron acquisition. BauE, the ATP-binding subunit of the ferric acinetobactin transporter, drives ATP hydrolysis to power iron import and therefore represents a potential therapeutic target. In this study, an integrated computational approach was employed to characterize the structure of BauE and identify antimicrobial peptides (AMPs) predicted to interact with functionally important regions. Since no experimental structure of BauE is currently available, three-dimensional models were generated using AlphaFold, Robetta, and trRosetta and refined through structural validation and 500 ns molecular dynamics (MD) simulations. The AlphaFold-predicted model exhibited the highest structural stability and was selected for further analyses. Binding pocket prediction revealed a druggable cavity located near the Q-loop and Walker B motif, regions essential for ATP hydrolysis. Virtual screening of 601 AMPs followed by molecular docking identified Temporin-1CEc, Tachyplesin-1, and P7A3 as the top candidates based on favorable docking scores and interactions with functionally important residues. MD simulations provided comparative insights into the conformational stability of the peptide–protein complexes, while MM/GBSA calculations provided comparative estimates of their binding energetics. Temporin-1CEc and Tachyplesin-1 showed comparatively favorable interaction profiles during simulations. These peptides interacted with residues near the Q-loop and Walker B motif, suggesting a possible structural basis for investigating whether these interactions affect ATP hydrolysis and siderophore-mediated iron transport. Overall, this study provides the first structural insights into BauE and computationally prioritizes Temporin-1CEc and Tachyplesin-1 as promising peptide candidates for further experimental investigation against A. baumannii. Diagram showing iron transport through bacterial membranes, peptide interactions, and stability analysis across three panels.The figure consists of three panels labeled "Hypothesis," "Methodology," and "Result". The Hypothesis panel depicts a ferric-siderophore complex transporting across membranes via proteins BauA and BauB, highlighting iron deficiency. The Methodology panel showcases a 3D structure of BauE, peptide screening illustrated with colored lines, and an MD simulation in a cubic box filled with water molecules. The Result panel presents a stability profile graph over 500 time steps, a 3D model of peptide interactions with BauE, and a PCA scatterplot categorizing data points by group.

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Publication Details

Journal
Figshare
Published
2026-11-05
DOI
https://doi.org/10.6084/m9.figshare.34924843
Primary Topic
Antimicrobial Peptides and Activities
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article
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article

Structural modeling and in silico screening of antimicrobial peptides targeting BauE in Acinetobacter baumannii

Sadia Jaman, Punam Chowdhury, Syed Abu Fahad, Md. Mehedi Hasan Ridoy et al.
Figshare
Antimicrobial Peptides and Activities
article

Structural modeling and in silico screening of antimicrobial peptides targeting BauE in Acinetobacter baumannii

Sadia Jaman, Punam Chowdhury, Syed Abu Fahad, Md. Mehedi Hasan Ridoy, Al Hakim, Amina Khatun Sweety, Israt Khan Ananya, Susmita Chowhan, Jedni Akter Joty
article en

Abstract

Acinetobacter baumannii is a multidrug-resistant pathogen that relies on ATP-binding cassette (ABC) transporters for siderophore-mediated iron acquisition. BauE, the ATP-binding subunit of the ferric acinetobactin transporter, drives ATP hydrolysis to power iron import and therefore represents a potential therapeutic target. In this study, an integrated computational approach was employed to characterize the structure of BauE and identify antimicrobial peptides (AMPs) predicted to interact with functionally important regions. Since no experimental structure of BauE is currently available, three-dimensional models were generated using AlphaFold, Robetta, and trRosetta and refined through structural validation and 500 ns molecular dynamics (MD) simulations. The AlphaFold-predicted model exhibited the highest structural stability and was selected for further analyses. Binding pocket prediction revealed a druggable cavity located near the Q-loop and Walker B motif, regions essential for ATP hydrolysis. Virtual screening of 601 AMPs followed by molecular docking identified Temporin-1CEc, Tachyplesin-1, and P7A3 as the top candidates based on favorable docking scores and interactions with functionally important residues. MD simulations provided comparative insights into the conformational stability of the peptide–protein complexes, while MM/GBSA calculations provided comparative estimates of their binding energetics. Temporin-1CEc and Tachyplesin-1 showed comparatively favorable interaction profiles during simulations. These peptides interacted with residues near the Q-loop and Walker B motif, suggesting a possible structural basis for investigating whether these interactions affect ATP hydrolysis and siderophore-mediated iron transport. Overall, this study provides the first structural insights into BauE and computationally prioritizes Temporin-1CEc and Tachyplesin-1 as promising peptide candidates for further experimental investigation against A. baumannii. Diagram showing iron transport through bacterial membranes, peptide interactions, and stability analysis across three panels.The figure consists of three panels labeled "Hypothesis," "Methodology," and "Result". The Hypothesis panel depicts a ferric-siderophore complex transporting across membranes via proteins BauA and BauB, highlighting iron deficiency. The Methodology panel showcases a 3D structure of BauE, peptide screening illustrated with colored lines, and an MD simulation in a cubic box filled with water molecules. The Result panel presents a stability profile graph over 500 time steps, a 3D model of peptide interactions with BauE, and a PCA scatterplot categorizing data points by group.

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Openalex Percentile: Top 16%
Antimicrobial Peptides and Activities
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