Aliarcobacter butzleri is an emerging foodborne and zoonotic pathogen, yet many of its encoded proteins remain functionally uncharacterized. This lack of annotation limits understanding of its molecular mechanisms and hampers the identification of novel therapeutic targets. In this study, we systematically performed functional annotation of essential hypothetical proteins from the BNI-3166 strain using an integrative-in-silico approach to uncover potential drug and vaccine candidates. 2,367 protein-coding sequences were retrieved from the RefSeq database and were identified 356 as hypothetical proteins. Using BLASTp, we screened these HPs against the Database of Essential Genes and the human proteome to identify essential non-homologous proteins, resulting in 20 ENH candidates. Functional annotation was performed using several domain-based databases, including Pfam, InterPro, SMART, and SUPERFAMILY. Subsequently, physicochemical properties were analyzed and predicted subcellular localization using PSORTb and CELLO. To assess druggability, the ChEMBL database was used. Virulence factors using VFDB, VICMpred, and VirulentPred 2.0 were also predicted. Gene Ontology annotations were generated via ARGOT2.5. Furthermore, we explored protein-protein interactions using STRING and predicted tertiary structures with AlphaFold3. Moreover, Ligand binding pockets were predicted using PrankWeb, and antigenicity of vaccine candidates was assessed using VaxiJen v2.0. We identified 20 essential non-homologous hypothetical proteins, of which 10 were confidently annotated based on conserved domain analysis. These proteins were classified as enzymes, binding proteins, transporters, regulatory proteins, and potential virulence factors. Among them, eight exhibited characteristics of promising drug targets, while two showed potential as vaccine candidates based on subcellular localization. Druggability analysis revealed that nine proteins had no similarity to known drug targets, suggesting novel therapeutic potential. Predicted 3D structures generated using AlphaFold3 yielded pTM scores ranging from 0.44 to 0.92, indicating acceptable to high modeling confidence. Ligand binding site analysis confirmed druggability in six candidates, and antigenicity screening identified one protein as a potential vaccine target. This study provides a computational framework for identifying functionally important proteins in A. butzleri BNI-3166 and highlights novel therapeutic candidates for experimental validation, offering new directions in drug and vaccine development against this underexplored pathogen.
Key words: Aliarcobacter butzleri, Drug Target Identification, Functional Annotation, Hypothetical Proteins, In Silico Analysis
Received: 08.07.2025; Accepted: 01.09.2025; Early view: 24.09.2025 Published: 10.01.2026
DOI: 10.62063/ecb-66
Citation: Paul, S., Barua, S., & Barua, J.D. (2026). In-silico functional annotation and structural characterization of hypothetical proteins from Aliarcobacter butzleri BNI-3166: Insights into novel virulence and drug targets. The European chemistry and biotechnology journal, 5, 22-39. https://doi.org/10.62063/ecb-66
The copyrights of the studies published in The European Chemistry and Biotechnology Journal (EUCHEMBIOJ) belong to their authors
This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)(https://creativecommons.org/licenses/by-nc/4.0/).
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Based on the naming convention—which includes a DLL filename, a version number, and an explicit password—this file is frequently associated with specialized software tools, often in the realm of hardware diagnostics, system utilities, or security research. What is this file?
If you must run the file for research or technical purposes, do so within a Virtual Machine (VM) or a Windows Sandbox environment to isolate it from your main files.
Unverified DLL files can cause "Blue Screen of Death" (BSOD) errors or system crashes if they are incompatible with your OS. Best Practices for Handling This File
The name suggests it contains , a component sometimes used in specific technical environments. The "x64" indicates it is designed for 64-bit Windows systems, and "v5200" likely refers to the version of the utility it supports. Safety and Security Warning
If you have downloaded or are planning to use this specific archive, follow these steps to protect your system:
Files distributed in .zip format with generic passwords like 12345 are a common method used to bypass email filters and antivirus scanners. While such files are sometimes legitimate tools used by technicians, they are also a primary vector for: Malicious code hidden inside a DLL.
If you are searching for this file because your computer is reporting that , the safest way to fix the issue is usually to reinstall the program that requires it. This ensures all registry entries and dependencies are correctly configured. Are you trying to resolve a specific error message , or
Only download system files and DLLs from the original developer's website. Avoid "DLL downloader" sites, as these are often unregulated. How to Fix DLL Errors