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September 5, 20250 citationsOpen Access

In silico Identification of Novel Drug Targets in Erwinia amylovora: A Step Toward Fire Blight Control in pear and apple trees

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WEWael Badr El-KholyNSNesrine Ben SalahHAHeba Allam

Key Points

  • Two high-confidence drug targets were identified that may effectively inhibit erwinia amylovora.
  • The first target is a methylesterase domain that regulates chemotaxis, and the second is a cyclic-di-GMP signaling protein.
  • Proteomic analysis utilized by filtering, screening for virulence, and performing structural modeling using AlphaFold.
  • Integrative in silico methods propose promising candidates for targeted therapeutics to manage fire blight effectively.

Abstract

Abstract Fire blight, a destructive disease affecting apple and pear orchards, is caused by the Gram-negative pathogen Erwinia amylovora, leading to considerable economic losses worldwide. Current control strategies using copper-based bactericides and antibiotics are becoming increasingly ineffective due to resistance development, highlighting the need for novel therapeutic interventions. In this study, we applied a robust subtractive proteomics pipeline to identify potential drug targets unique to E. amylovora. The proteome was systematically filtered by length, redundancy, and host homology against Malus domestica and Pyrus communis, followed by screening for virulence and essentiality using VFDB and DEG. Subcellular localization, Pfam domain annotation, druggability analysis via DrugBank, and Gene Ontology enrichment were performed. Two high-confidence targets were identified. The first harbors the CheB methylesterase domain (PF01339), a key regulator of bacterial chemotaxis. The second is a cyclic-di-GMP signaling protein, essential for bacterial lifestyle transitions and biofilm regulation, and contains the GGDEF (PF13426), EAL (PF00989), and PilZ (PF08448) domains. These domain architectures underscore their roles in intracellular signaling and motility control. Structural modeling using AlphaFold, coupled with active site prediction, enabled virtual screening against ~ 9,500 bioactive compounds from Life Chemicals. Nine compounds demonstrated strong binding affinities with the predicted active sites via AutoDock Vina. These findings support their potential as inhibitors, although experimental validation is required. This integrative in silico pipeline offers promising candidates for the development of targeted therapeutics against E. amylovora, contributing to sustainable fire blight management.

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Cite This Study

El-Kholy et al. (2025) studied this question.

synapsesocial.com/papers/68bb49db6d6d5674bcd003achttps://doi.org/10.21203/rs.3.rs-7381667/v1
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