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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The Evil Queen, disguised as an old hag, eventually discovers Snow White's whereabouts and offers her a poisoned apple, which puts Snow White into a magical sleep. However, Snow White is eventually awakened by a handsome prince and lives happily ever after. The tale has been adapted and retold in various forms of media, captivating audiences with its themes of beauty, jealousy, and the ultimate triumph of good over evil.
: Velba portrays a stylized version of the character, often featuring the iconic red headband and blue-and-yellow color palette associated with the character's traditional look.
The story leans into the psychological interplay between the characters. The "Evil Queen" (Velba) seeks to assert her dominance, both through her magical prowess and her commanding personality.
The "Snow White Meets the Evil Queen" set was produced during Milena Velba's prime years of content creation. Following this period, Velba continued to operate her website and collaborate with other models in the industry. Her approach to modeling—emphasizing natural beauty and mature sensuality—earned her a loyal fanbase.
The most famous of these thematic endeavors is her Snow White and the Evil Queen set, released on April 20, 2010. The specific keyword "milena velba 20100420 snow white meets the evil queen top" refers to a photo set that perfectly captured the contrast between two iconic fairy tale archetypes: the innocent and beautiful princess and the vain, powerful queen. The date—April 20, 2010—marks an important timestamp in her career, showing when this specific set was released to her membership. This combination of performance and thematic richness is a hallmark of her best work.
The "20100420" identifier refers to the release date—April 20, 2010. During this era, Milena Velba was at the peak of her popularity in the glamour modeling industry, known for her high-quality digital sets that often incorporated themes of fantasy, cosplay, and professional costuming.
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