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Sweta Paul1, ORCID: 0009-0006-3419-4335
Susmoy Barua2 , ORCID: 0009-0004-0898-2384
Joy Dip Barua3 *, ORCID: 0000-0002-0392-8213

1Department of Bioinformatics, Maulana Abul Kalam Azad University of Technology, Haringhata, Nadia, West Bengal, India. ROR ID: 030tcae29

2Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore 7408, Bangladesh. ROR ID: 04eqvyq94

3Department of Bioinformatics, Pondicherry University, Kalapet, Puducherry 605014, India. ROR ID: 01a3mef16

High Quality Download Stick War Legacy Mod Vip Ios And New [hot] -

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

*Corresponding author: E-mail: ; Ph.: +8801644238988

Peer Review: Double Blind Refereeing.

Ethics Statement: It is declared that scientific and ethical principles were followed during the preparation of this study and all studies utilized were indicated in the bibliography (Ethical reporting: editor@euchembioj.com).

Plagiarism Check: Performed (iThenticate). Article has been screened for originality.

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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Downloading third-party modifications on iOS requires careful attention to security. Official applications belong on the Apple App Store . Modified application files (IPA packages) require specific steps to ensure device safety: Avoid System Jailbreaks

Go to Settings > General > VPN & Device Management, find the enterprise certificate, and select "Trust." Launch the game from your home screen. Strategic Tips for VIP Gameplay

To get the highest-quality version of Stick War: Legacy on iOS:

Before diving into modifications, it's important to understand the core game. Stick War: Legacy , developed by Max Games Studios, is a game where you control an army of stick figure warriors. The goal is simple: destroy the enemy's statue while defending your own. You command miners to gather gold, train units like Swordwrath, Archidons (archers), Magikill (mages), and the mighty Giant, and seize control of territories.

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