Unveiling a Novel Barstar Protein: In Silico Analysis of Hypothetical Protein WP_311008533.1 from Shigella boydii Reveals Its Role as an Intracellular Inhibitor of Barnase

Highlights

• The annotation of the hypothetical protein WP_311008533.1 from boydii is reported.
• Cysteine residues are completely absent in 1, which is significant as cysteine plays a crucial role in forming disulfide bonds that help to stabilize protein structures.
• This analysis confirms that the target protein is a Barstar family member, closely related to a homolog in Escherichia coli.
• The search results show that the target protein does not share any similarities with human proteins, confirming that it is unique to microbes.

 Introduction

Shigellosis, known as a food-borne disease, is caused by Shigella species S. sonnei, S. flexneri, S. boydii, and S. dysenteriae and is transmitted through the ingestion of food, water, or objects contaminated with human feces. While children in low-income regions are most affected, travelers and men who have sex with men (MSM) are increasingly at risk in higher-income countries. Shigellosis is estimated to cause an estimated 125 million cases of diarrhea each year contributing to around 160,000 deaths (1). Although shigellosis is relatively rare in the European Union (EU) and the European Economic Area (EEA), it remains a significant concern in certain countries and among specific population groups. In 2021, 2,115 confirmed cases were reported across 30 EU/EEA countries, with an overall notification rate of 0.8 cases per 100,000 people—a slight increase from the previous year, which saw the lowest recorded rates due to the impact of the COVID-19 pandemic and the absence of the United Kingdom (UK) data. The highest rates were observed in children under five and in male adults aged 25-44 years (2). Global Enteric Multicenter Study (GEMS) data revealed that, over a three-year period, 5.4% (61/1,130) of all Shigella cases were attributed to S. boydii. While this may seem modest compared to the other three Shigella species, S. boydii remains a notable contributor to the overall global burden of shigellosis (3, 4).  

Barnase is a member of a family of microbial ribonucleases that catalyzes the degradation of ribonucleic acid (RNA) by cleaving phosphodiester bonds between ribonucleotides. While this activity is critical for various biological processes, its uncontrolled action can be lethal to bacterial cells. To avoid cellular damage, Barnase activity is tightly regulated by its natural inhibitor, Barstar. The regulation of Barnase involves a highly specific interaction between Barnase and Barstar, which prevents its harmful RNA-cleaving activity (5). With the rise of large-scale whole genome sequencing projects in the post-genomic era, a wealth of previously uncharacterized protein-coding genes, comprising roughly two-thirds of bacterial genomes, has been identified. These genes are often categorized as hypothetical protein (HPs), which, while conserved in expression, remain largely enigmatic in terms of their function and role within the bacterial cell. It is hypothesized that these proteins are involved in critical processes such as bacterial growth, survival, and virulence, potentially harboring vital insights that could aid in the fight against bacterial infections. Investigating the functions of HPs can unveil key biological pathways, identify novel protein structures for drug and vaccine development, and significantly enhance our understanding of bacterial pathogens (6).

In this study, we performed an in silico analysis of a hypothetical protein, WP_311008533.1, identified in Shigella boydii. At the initiation of this study (January 2024), WP_311008533.1 was classified as a hypothetical protein in the NCBI database with no assigned function, justifying its selection for in silico functional and structural analysis. This protein was selected from numerous hypothetical proteins in the S. boydii genome based on its high sequence novelty (<30% identity to annotated proteins in UniProt and NCBI databases), predicted role as a Barstar protein through domain analysis, and computational predictions of cytoplasmic localization and structural stability using tools such as CELLO and PSORTb. Our computational investigations revealed structural and functional similarities between this protein and Barstar, a known intracellular inhibitor of the ribonuclease Barnase. Barnase plays a crucial role in bacterial RNA degradation, but without proper regulation, its activity can be lethal. Barstar tightly binds to Barnase, forming a highly specific protein-protein complex to neutralize its enzymatic function. Our findings suggest that WP_311008533.1 may serve as a regulator within this system, highlighting an unforeseen molecular adaptation in S. boydii. Using advanced computational tools, including protein structure prediction and functional annotation, we provide the first insights into the potential role of WP_311008533.1 in S. boydii. This discovery sheds light on a previously unknown bacterial self-regulation mechanism, offering potential targets for future antimicrobial interventions.

Materials and Methods

Selection of Hypothetical Protein

The hypothetical protein WP_311008533.1 was selected from the Shigella boydii genome based on stringent criteria to ensure its suitability for this study. These criteria included: (1) high sequence novelty, with <30% identity to annotated proteins in UniProt and NCBI databases, as determined by BLAST analysis; (2) predicted function as a Barstar protein, identified through domain and motif analysis using InterPro; and (3) favorable structural and localization properties, with cytoplasmic localization and high stability predicted by CELLO, PSORTb, and AlphaFold2. These attributes positioned WP_311008533.1 as a promising candidate for in-silico analysis of its structural and functional roles.

 Annotation Status Verification

The hypothetical protein WP_311008533.1 was selected based on its annotation status in the NCBI database as of January 2024, where it was listed as a "hypothetical protein" without a specific functional assignment. This was confirmed using archival snapshots of the NCBI protein record. Subsequent database updates, likely reflecting recent annotations, have assigned a Barstar function to this protein, consistent with our findings. All analyses in this study were conducted based on the information available at the study’s outset.

Sequence retrieval with FASTA format

The FASTA sequence of the hypothetical protein (WP_311008533.1) was retrieved from the National Center for Biotechnology Information (NCBI) database for detailed analysis (7). The sequence was then submitted to various advanced prediction servers for in silico annotation, enabling a thorough examination of its potential functions and properties (8).

 Physicochemical properties analysis

The ExPASy ProtParam tool (https://web.expasy.org/protparam/) was employed to analyze the hypothetical protein (HPs) by evaluating its physicochemical properties. This comprehensive analysis included the following: molecular weight, aliphatic index, extinction coefficients, amino acid composition, grand average of hydropathy (GRAVY), isoelectric point (pI), and estimated half-life. This provided key insights into the  structural characteristics and stability of the protein (9).

Subcellular localization and solubility prediction

The subcellular localization of the hypothetical protein was predicted using CELLO v.2.5 (http://cello.life.nctu.edu.tw/) (10), which utilizes a two-level support vector prediction system. To validate and refine these predictions, we incorporated results from three additional tools—SOSUIGramN (https://harrier.nagahama-i-bio.ac.jp/sosui/sosuigramn/) (11), PSLpred (https://webs.iiitd.edu.in/raghava/pslpred/submit.html) (12), and PSORTb (https://www.psort.org/psortb/) each based on distinct algorithms and training datasets. (13). This integrative approach allowed for cross-validation and minimized potential bias from any single method. Additionally, SOSUI (http://harrier.nagahama-i-bio.ac.jp/sosui/) was used to calculate the protein’s average hydrophobicity helping to determine its solubility and identify hydrophobic regions likely to form transmembrane domains (14).

 Domain and motif identification

The following software was employed for protein domain analysis: NCBI CD-Search (https://structure.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi) (15), Pfam 34.0 (http://pfam.xfam.org/) (16), and InterProScan5 (http://www.ebi.ac.uk/Tools/services/web/toolform.ebi?tool=iprscan5&sequence=uniprot:KPYM_HUMAN) (17). To ascertain the protein sequence motif, the MOTIF Search tool (https://www.genome.jp/tools/motif/) was employed (18). A conserved domain (CD) search involves comparing a query sequence with CD alignments sourced from the Conserved Domain Database (CDD). The functional analysis of the protein was conducted using the InterProScan tool. Pfam is a protein family database that employs hidden Markov models (HMMs) to generate annotations and multiple sequence alignments.

Protein family and phylogenetic tree analysis

A BLASTp search was conducted using the non-redundant database at the National Center for Biotechnology Information (NCBI) (http://www.ncbi.nlm.nih.gov/) with default parameters to identify homologues of the protein. A multiple sequence alignment was performed using BioEdit (19) for its robust visualization and manual curation tools, which were essential for refining alignments in regions of low sequence similarity (<30% identity to known proteins). This ensured high-quality alignment for subsequent analyses. A phylogenetic tree was constructed using MEGA (version 11) with the neighbor-joining (NJ) method, employing the Jones-Taylor-Thornton (JTT) substitution model and 1,000 bootstrap replicates to assess tree robustness (20). The NJ method was selected for its suitability in analyzing proteins with low sequence similarity, enabling reliable inference of the evolutionary relationships WP_311008533.1, consistent with its predicted Barstar function.

Secondary structure determination

The secondary structure was predicted using the self-optimized prediction method with alignment (SOPMA) (https://npsa-prabi.ibcp.fr/cgi-bin/npsa_automat.pl?page=/NPSA/npsa_sopma.html) (21). We also used JPred4 (http://www.compbio.dundee.ac.uk/jpred4/) to validate the results obtained from SOPMA (22).

Homology modeling

The Alpha Fold 2 Protein Structure Prediction Database (https://alphafold.ebi.ac.uk/) was used to determine the 3D structure of our putative HP, and the performance of this determination was based on the pairwise comparison profile of the HMMs (23). The template protein of the Barnase inhibitor protein (DB ID: AF-A0A0E2L2L1-F1-v4) was retrieved from the query result for homology-based modeling. UCSF Chimera version 1.16 was used to visualize the 3D model structure (24).

Quality assessment

Several evaluation tools were used to assess the quality of the predicted 3D structure. These included the programs PROCHECK (https://www.ebi.ac.uk/thornton-srv/software/PROCHECK/), Verify3D (https://servicesn.mbi.ucla.edu/Verify3D/) (25), and QMEAN (https://swissmodel.expasy.org/qmean/) from the ExPASy server within the SWISS-MODEL Workspace (26). The Z-scores for the protein were also estimated using the ProSA-web server (27).

Energy minimization of the model structure

The energy of the 3D model structure was minimized using the YASARA (http://www.yasara.org/minimizationserver.htm) force field minimization server. After refining through YASARA, a more stable and reliable 3D structure of the target protein was obtained (28).

Comparative genomics approach

To ascertain whether our target hypothetical protein WP_311008533.1 bears any resemblance to human proteins, a BLASTp search (https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE=Proteins) against the Homo sapiens proteome was performed (29). A threshold E-value (expected value) of 0.005 and a minimum bit score of 100 were set to filter the results.

Active site analysis

The active site of the hypothetical protein WP_311008533.1 was analyzed using the Computed Atlas of Surface Topography of Proteins (CASTp, version 3.0; http://sts.bioe.uic.edu/castp/). CASTp was employed to identify potential binding pockets and characterize the surface topography of the protein based on geometric and topological properties. The analysis was performed with a probe radius of 1.4 Å to assess solvent-accessible surfaces, enabling the identification of a functionally relevant active site. The predicted active site was evaluated for its suitability as a drug target, supporting the functional annotation of the protein as a Barstar inhibitor.

Results

Physicochemical properties

The ProtParam tool was employed to ascertain a number of pivotal physicochemical characteristics. The protein was predicted to contain 90 amino acids, a theoretical pI of 4.55, and a molecular weight of 10,752.13 Da. The GRAVY value of the protein was calculated to be -0.317. The instability index of the desired protein was found to be 76.43.

Analysis of the amino acid composition revealed several functionally significant features of WP_311008533.1. The protein is enriched in hydrophobic residues, with leucine (14.4%) and phenylalanine (10.0%) being the most abundant, consistent with the structural requirements of Barstar proteins. Notably, cysteine is completely absent from the sequence, indicating that protein stability is maintained through non-covalent interactions rather than disulfide bonds. The protein exhibits an acidic character with 20 negatively charged residues (aspartic and glutamic acids) compared to 10 positively charged residues (arginine and lysine) (Table 1), contributing to its predicted cytoplasmic localization and solubility. The molecular composition comprises 1,501 atoms with the formula C₄₈₉H₇₄₀N₁₂₆O₁₄₄S₂, providing essential parameters for structural modeling and drug design applications.

Table 1. The physicochemical properties of the WP_311008533.1 protein estimated by ProtParam.

Subcellular localization and solubility prediction

Predicting subcellular localization provides critical insights into protein function and guides drug design strategies. Using computational analysis, CELLO, SOSUIGramN, PSLpred, and PSORTb all consistently predicted that WP_311008533.1 was cytoplasmic. SOSUI further classified the protein as soluble, thus confirming its cytoplasmic nature. This localization is consistent with known Barnase-barstar regulatory systems that function within the bacterial cytoplasm.

Domain and motif identification

Computational domain analysis using CD-Search identified the query protein as belonging to the barstar family an intracellular inhibitor of Barnase with a highly significant E-value of 6.59e-27, spanning residues 3-88. This classification was corroborated by multiple independent analyses: Pfam mapped the barstar domain to residues 1-81, InterProScan identified the same domain within residues 3-88, and MOTIF server predicted the Barnase inhibitor domain at residues 1-81 with an E-value of 1.1e-08. The convergence of these predictions from different algorithmic approaches provides robust evidence for the barstar domain annotation, and the highly significant E-values indicating extremely low probability of chance occurrence.

Protein family and phylogenetic tree analysis

BLASTp search against the non-redundant database revealed up to 97% sequence similarity with known Barstar family proteins from various bacterial species (Table 2). From the results, 7 closely related protein sequences, along with the target sequence, were selected for multiple sequence alignment (MSA). MSA, performed using BioEdit, identified conserved and variable residues among homologous proteins (Fig. 1). Based on these sequences, a phylogenetic tree was constructed (Fig. 2), illustrating evolutionary relationships. Notably, the target protein shares a common ancestor with the WP_209205137.1 protein from Escherichia coli. The scale bar (0.01) represents sequence divergence, quantifying the extent of genetic variation.

Table 2. Identification of homologs of WP_311008533.1 through protein BLASTp search analysis.

Fig. 1. Multiple sequence alignment (MSA) of the target protein sequence and 7 closely related homologous proteins, highlighting conserved (shaded) and variable residues, performed using BioEdit.

Fig. 2. Phylogenetic tree illustrating the evolutionary relationship of WP_311008533.1 with closely related proteins. The tree was constructed using the neighbor-joining (NJ) method in MEGA (version 11) with the Jones-Taylor-Thornton (JTT) substitution model and 1,000 bootstrap replicates. The phylogenetic analysis traced the evolutionary history of WP_311008533.1, linking it closely to a homologous protein in Escherichia coli.

Secondary structure determination

The SOPMA server predicted the secondary structure of the protein, revealing that α-helices dominate its architecture (55.56%), followed by random coils (28.89%) and extended strands (15.56%). The structural composition identified by SOPMA was strongly supported by the JPred4 analysis, which further reinforces the reliability of these findings (Fig. 3).

Homology modeling

The three-dimensional (3D) structure of the target protein was modeled using the Barnase inhibitor protein (PDB ID: AF-A0A829A9B4-F1-v4) as a structural template. This template, which is a Barnase inhibitor from Escherichia coli, exhibited an exceptionally high sequence identity (99%) with the target protein, thereby confirming its suitability for structural modeling. The final 3D structure was meticulously visualized using UCSF Chimera 1.16, providing a detailed representation of the protein’s spatial conformation (Fig. 4).

Fig. 3. Secondary structure prediction of WP_311008533.1 using JPRED4 server, showing the distribution of α-helices (H), extended strands (E), and random coils (C) along the protein sequence.

Fig. 4 .Predicted three-dimensional structure of WP_311008533.1 based on AlphaFold 2 prediction with 99% sequence identity to Barnase inhibitor (PDB ID: AF-A0A829A9B4-F1-v4). Structure visualized using UCSF Chimera 1.16.

Active site analysis

The active site of the predicted 3D protein structure was identified using the CASTp server, which maps solvent-accessible pockets that are critical for molecular interactions (Fig. 5). The largest and most significant active site was found to be located within a spacious binding pocket, with a solvent-accessible surface area of 94.801 Ų and a total volume of 53.400 ų. The key catalytic and binding residues within this site are Glu15, Tyr18, Arg19, Ser22, Gln23, Lys29, Asp30, Val32, and Arg33, which may play essential roles in substrate recognition and enzymatic function. Pinpointing the active site is a crucial step in the design of rational drugs, as it provides a precise target for the development of inhibitors or therapeutic compounds.

Fig. 5. Active site identification of WP_311008533.1 using CASTp server. The predicted binding pocket shows a solvent-accessible surface area of 94.801 Ų and volume of 53.400 ų, with key residues Glu15, Tyr18, Arg19, Ser22, Gln23, Lys29, Asp30, Val32, and Arg33 highlighted.

Quality assessment

The structural integrity and reliability of the predicted 3D model of the target protein were rigorously assessed using multiple validation tools. PROCHECK analysis of the Ramachandran plot revealed that 92.7% of amino acid residues reside within the most favored regions, indicating a highly reliable structural conformation (Table 3, Fig. 6A). Further validation using the Verify 3D plot demonstrated that 100% of residues achieved an averaged 3D-1D score ≥ 0.1, reinforcing the model’s consistency with experimentally determined structures. The ERRAT program assigned an overall quality factor of 85.19, signifying a robust structural model. Additionally, the QMEAN4 score, a comparative metric evaluating the model against known experimental structures, yielded a global score of 0.87, confirming its high accuracy and reliability (Fig. 6B).

Table 3. Ramachandran plot statistics of the target protein.

                          (A)                                                                               (B)

Fig. 6. Model Quality Assessment. (A) Ramachandran plot illustrating Phi (φ) and Psi (ψ) angles of the protein structure, with labeled allowed regions (A, B, L, P). Generated using PROCHECK. (B) Graphical representation of QMEAN result of the model structure.

Energy minimization result

The energy optimization of the protein’s three-dimensional structure was performed using the YASARA force field minimizer. This process successfully reduced the energy from –69835.6 kJ/mol to –59690.7 kJ/mol, indicating a significant decrease in structural strain. The initial energy deviation was 0.61 kJ/mol, which increased slightly to 1.08 kJ/mol after minimization, indicating that the structure reached a stable, energetically favorable conformation. The protein structure was further refined for enhanced stability, and the energy reduction shows that it has reached a favorable, low-energy state.

Comparative genomics approach

Following the successful structural and functional annotation of the hypothetical protein, a comparative genomic analysis was employed to further investigate its characteristics. A BLASTp search was performed against the human proteome to determine whether the target protein shares any homology with human proteins. The results indicated that the target protein does not show homology with any known human protein, thereby confirming its novelty. Targeting microbial proteins that are non-homologous with human proteins presents an advantageous strategy for drug development, as it reduces the likelihood of off-target effects and potential side effects in human systems.

Discussion

In this study, we successfully annotated the hypothetical protein WP_311008533.1 from Shigella boydii, an important bacterium responsible for causing shigellosis—a severe gastrointestinal infection. This analysis confirmed that WP_311008533.1 is similar to the Barstar family of intracellular inhibitors that protect against Barnase ribonuclease by binding to and blocking its activity, thereby preventing RNA degradation. The close evolutionary relationship between WP_311008533.1 and a homologous protein from Escherichia coli suggests that this protein may play a similar role in Shigella boydii, contributing to the bacterium’s ability to survive in harsh, competitive environments by protecting its RNA from degradation. This functional analogy to the E. coli homolog provides important clues about the protein’s role in Shigella and the potential mechanisms of bacterial resistance to host immunity and antibiotic pressure. Our phylogenetic analysis further supported this conclusion, as it traced the evolutionary lineage of WP_311008533.1 and revealed its close relationship with other Barstar-family proteins.

Barnase and Barstar are two small, soluble proteins produced by Bacillus amyloliquefaciens. Both proteins are composed of 110 and 89 amino acids, respectively, and neither requires disulfide bonds, metal ions, or other cofactors for folding or activity. The inhibition mechanism involves the formation of a highly stable bimolecular complex (with a dissociation constant of approximately 10⁻¹⁴ to 10⁻¹³ M) (30). This interaction is reversible, and both proteins can be unfolded and refolded in solution. They are frequently used in studies of protein folding and protein–protein interactions, serving as a model for protein engineering and directed mutagenesis (31). Barnase catalyzes the degradation of RNA by cleaving phosphodiester bonds in the RNA backbone. Barnase is highly specific for RNA and plays a role in bacterial RNA metabolism. However, Barnase is highly toxic to cells because its activity leads to the breakdown of essential RNA, making its uncontrolled expression lethal to the bacterial cell. Therefore, its activity must be tightly regulated. The Barstar protein is crucial for regulating the activity of Barnase, ensuring that the enzyme only functions when needed and does not cause damage to the bacterial cell, effectively neutralizing its toxicity (5, 32). Barstar interacts with Barnase through a combination of hydrogen bonds, hydrophobic forces, and ionic interactions, creating a strong and stable complex. This binding is highly dynamic under certain conditions, the complex can dissociate, allowing Barnase to regain its RNA-degrading activity. The unique backbone fold of Barstar is specifically tuned to bind tightly to Barnase, outperforming mutants with altered residues. This observation highlights how natural proteins optimize electrostatic interactions to achieve high-affinity binding (33). In its natural setting, the Barstar and Barnase system is part of the bacterial self-regulation mechanism, ensuring that the cell's RNA degradation machinery (Barnase) is tightly controlled and does not harm the cell. Barstar is also exploited in biotechnology for its stabilizing effect on protein–protein interactions, and the system is frequently used as a model for studying protein folding and stability (34, 35). Kim et al. studied an HP named SF216 in S. flexneri and its weak ribonuclease activity, as confirmed by a fluorescence quenching assay. Additionally, through computational mapping, they identified potential druggable pockets for future drug design. They also observed that SF216 shares structural similarities with domain-swapped trimeric ribonucleases like Barnase and RNase A, which adopt similar structures under specific conditions such as low pH or high protein concentration (36). Unlike other dimerization systems, the Barnase-Barstar complex maintains a precise one-to-one ratio of its components, with both proteins showing high stability and solubility in aqueous solutions without aggregating. These unique characteristics make the Barnase-Barstar system an attractive tool for engineering anticancer compounds and cytotoxic supramolecular complexes (37). The Barnase-Barstar system has emerged as a powerful tool in cancer research and nanotechnology, offering potential for targeted therapies and innovative nanomaterial designs. Alekseeva et al. investigated a novel approach for targeted cancer immunotherapy using DARPin9_29-Barnase as a targeting module to deliver heat shock protein 70 KDa (HSP70) to tumor cells expressing the HER2/neu antigen. Building on previous research using chimeric recombinant proteins (4D5scFv-Barnase and Barstar-HSP70), the authors explored the efficacy of DARPin9_29-Barnase for targeting HER2/neu-positive human carcinoma cell lines (SK-BR-3 and BT474) (38). Proshkina et al. explored the use of pre-targeting technology to improve the targeting of cancer cells with a cytotoxic module composed of nanoliposomes carrying a truncated form of Pseudomonas aeruginosa exotoxin A (PE40). The pre-targeting system utilizes the bacterial ribonuclease Barnase and its natural antitoxin, Barstar. Barstar is genetically fused to engineered scaffold proteins targeting tumor-associated antigens (HER2, EpCAM) for precise cancer cell recognition, while Barnase is conjugated to a therapeutic agent for cytotoxicity. The strong, non-covalent interaction (KD10−14M) between Barstar and Barnase enables efficient interaction between the two modules on the cell surface, as confirmed by confocal microscopy and flow cytometry. In mice with SKOV-3 ovarian cancer xenografts, the pre-targeting approach demonstrated significantly greater efficacy than single-step active targeting (39).

Conclusion and future perspectives

In this study, we characterized the hypothetical protein WP_311008533.1 from Shigella boydii using comprehensive bioinformatics approaches. Our analyses revealed that this protein belongs to the Barstar family and exhibits strong evolutionary and structural similarity to known Barnase inhibitors, particularly those in Escherichia coli. Structural predictions indicate the presence of a solvent-accessible active pocket, suggesting potential functional importance. Importantly, comparative genomics showed no significant similarity to human proteins, positioning WP_311008533.1 as a promising candidate for selective antimicrobial drug development with minimal off-target effects. Further experimental validation is needed to confirm the predicted structure, active site, and functional role of WP_311008533.1. High-resolution techniques such as X-ray crystallography or cryo-EM, combined with in vitro and in vivo studies, will clarify its biological activity and stability. In addition, molecular docking, dynamics simulations, and antimicrobial assays could help identify specific inhibitors and explore its therapeutic potential, particularly against antibiotic-resistant pathogens.

Abbreviations

1. boydii: Shigella boydii; HP: Hypothetical Protein; MSM: Men who have sex with men; EU: European Union; EEA: European Economic Area; UK: United Kingdom; GEMS: Global Enteric Multicenter Study; RNA: Ribonucleic acid; NCBI: National Center for Biotechnology Information; pI: Isoelectric point; GRAVY: Grand Average of Hydropathy; CD: Conserved Domain; CDC: Conserved Domain Database; HMMs: Hidden Markov Models; SOPMA: Self-Optimized Prediction Method with Alignment; MSA: Multiple Sequence Alignment; 3D: Three-Dimensional; HSP70: Heat Shock Protein 70 kDa; PE40: Pseudomonas aeruginosa exotoxin A; Cryo-EM: Cryo-Electron Microscopy.

 Declarations

Ethical Approval and Consent to Participate

Conflict of Interest All the authors of this paper declare the existence of no actual conflict of interests.

Availability of Data and Materials

The data of the paper, which support the analysis and results of this paper, are available with the corresponding author and the data can be obtained from the authors upon request.

Clinical Trial Number: Not applicable.

Consent for Publication

Authors agree to publication.

Funding

The authors did not receive any funding support.

Competing Interests

The authors declare no conflict of interest.

Authors' Contributions

All authors contributed to the study's conception and design. Supervision, revision, and checking the results were done by M.K, M.M and H.S, Material preparation, bioinformatics analysis, and writing the manuscript were performed by Z.D.Z and A.R.A.Z.

Acknowledgment

None.

Figure legends:

Fig. 1. Multiple Sequence Alignment among different types of phage baseplate assembly protein V proteins with the target protein. This analysis confirms that the target protein belongs to the Barstar family and shares a high degree of similarity with known bacterial proteins. The MSA highlighted conserved regions, supporting its functional role.

Fig. 2. Phylogenetic tree illustrating the evolutionary relationship of WP_311008533.1 with closely related proteins. The phylogenetic tree traces its evolutionary history, linking it closely to a homologous protein in Escherichia coli.

Fig. 3. The secondary structures as predicted by JPRED servers. The protein is rich in alpha helices, which could indicate a structural or enzymatic role. The presence of random coils suggests flexibility, while extended strands hint at possible beta-sheet formation.

Fig. 4. Predicted three-dimensional structure of the WP_311008533.1 (visualized by UCSF Chimera 1.16). This study used an existing Barnase inhibitor protein as a structural reference to predict the 3D structure of the target protein with high confidence. The 99% sequence identity ensures an accurate model, which was then visualized in UCSF Chimera to study its shape and potential function.

Fig. 5. Determination of the active site of WP_311008533.1 using the CASTp server. A solvent-accessible surface area of 94.801 Ų indicates that part of the pocket is exposed to water, which is important for interactions with molecules. A total volume of 53.400 ų indicates the space available within the pocket for ligand or drug binding. These residues (Glu15, Tyr18, Arg19, Ser22, Gln23, Lys29, Asp30, Val32, and Arg33) are likely involved in binding or catalysis and may contribute to the protein’s function by mediating molecular interactions or catalysis.

Fig. 6. Model Quality Assessment. (A) The predicted 3D structure of the protein was evaluated using multiple validation tools. The results showed that the model is highly accurate and structurally reliable. This validated structure can now be used confidently for further studies, including drug design, protein function studies, and molecular docking. (B) Graphical representation of QMEAN result of the model structure. A QMEAN4 score close to 1.0 indicates a high-quality, accurate model. The target protein received a score of 0.87, reflecting a reliable and robust structural prediction.