In Silico Characterization of Hypothetical Protein AZJ53_10480 in Streptococcus pneumoniae

Introduction

Streptococcus pneumoniae, or pneumococcus, is a gram-positive, circular, alpha-hemolytic (under high-impact conditions) or beta-hemolytic (under anaerobic conditions), facultative, anaerobic microorganism isolated from Streptococcus. These bacteria are non motile, do not form spores and are forund in pairs.It is a major cause of death in children, worldwide. As a critical human pathogenic bacterium, S. pneumoniae has been perceived as a significant cause of pneumonia since the late 19^th century and remains the subject of numerous humoral resistances [1]. Pneumococcus spreads through respiratory droplets, such as those produced when an infected person coughs or sneezes. The bacteria can enter the body through the nose or mouth and then spread to the lungs, where it can cause pneumonia. It can also spread to other parts of the body, such as the bloodstream and brain. Pneumococcal infections can be serious, especially in young children, elderly adults, and people with weakened immune systems. In some cases, pneumococcal infections can lead to death [2].

In this study, a hypothetical protein (AZJ53_10480) was characterized in S. pneumoniae using in silico tools. Hence, this study provides information about the structure and function of hypothetical proteins. A comprehensive sequence analysis of the hypothetical protein was conducted, including the determination of its primary structure and the identification of conserved motifs. The study also investigated whether the hypothetical protein has any known associations with pathogenicity or virulence in S. pneumoniae, which may involve comparing it with proteins known to contribute in the pathogenicity of the bacterium. These objectives collectively aimed to provide a comprehensive understanding of the hypothetical protein AZJ53_10480 using in silico methods to uncover its sequence, structure, and potential biological functions.

There are multiple bacterial proteins that have different functions. In the respective bacteria, the proteins are particularly responsible for many important pathogenic activities, although some such proteins have yet to be characterized. Thus, protein characterization is required. Therefore, it remains unknown whether this protein is pathogenic, and if pathogenic, what the parameters are. If this protein is involved in any pathogenic activity, then there should be some drugs available to deal with it. .

In this study, the hypothetical protein AZJ53_10480 (S. pneumoniae) was utilized for in silico mutational analysis. The sequence of this protein was retrieved from NCBI and its structure was modeled and validated by using different types of tools including BLAST, CLUSTAL W, PSIPRED, Expasy protparam, I-TASSER, and CELLO . The modeled protein was then docked using AutoDock Vina [3].

Figure 1. Layout of the methodology

MATERIALS AND METHODS

2.1. Data Collection

The genomic sequences of the hypothetical protein AZJ53_10480 were retrieved from the NCBI database. From the genome of S. pneumoniae, the hypothetical protein was selected having accession number TVX06118.1 and its sequence was retrived in FASTA format for futher analysis [4].

2.2. Sequence Analysis

The sequences were identified and aligned using BLASTp. It showed top hundred sequence results in four forms, namely description, graphic summary, alignments, and taxonomy. The top five proteins were selected for comparison. In graphics, the results appear to be based on score ranges that show the similarity between the sequences. The description shows the results on the basis of e-value, percentage identity, and query coverage. Further, alignments results give the number of matches between the sequences, the length of the sequences, and the mismatch or gaps collectively called identities. The authors downloaded the top ten sequences results. These results are shown in the description from BLAST. The Phymol bootstrap phylogenetic tree was generated using CLUSTALW [5].

2.3. Physiochemical Analysis

It was performed using ProtParam. Protparam performs a comprehensive analysis of protein sequences. It calculates various physiochemical properties of proteins and provides valuable insights into their structural and functional characteristics. These properties include amino acid composition, molecular weight, theoretical pI, extinction coefficient, instability index, aliphatic index, and the grand average of hydropathicity [6].

2.4. Secondary Structure Prediction

The secondary structure of the hypothetical protein AZJ53_10480 was predicted using PSIPRED. This is an Expasy tool that can predict protein function directly from amino acid sequences using limited or possibly no homology information. It uses artificial neural network and machine learning methods in its algorithms [7].

2.5. Tertiary Structural Prediction of Protein

Iterative reading assembly refinement (I-TASSER) was used to predict the tertiary structure and functions of protein. It provides sequence to sequence, sequence to structure, and structure to function analyses. In I TASSER, scores play an important role in predicting the efficiency of the model [8].

2.6. Domain Prediction of Protein

Domain and family similarity analyses were performed using InterPro software. This software predicts domains and classifies proteins into families. Conserved domains of AZJ53_10480 protein were predicted using CD NCBI [9].

2.7. Docking and Modeling with Ligand

Docking and modeling of the protein AZJ503_10480 were performed using AutoDock Vina and Patch Dock. The interaction between AZJ53_10480 and the ligand sofosbuvir was performed using AutoDock Vina and PatchDock. In PatchDock, protein and ligand were entered as input and the output comprised a list of potential complexes [10].

RESULTS

3.1. Phylogenetic Tree Construction

Protein BLAST was used to search for the alignment of this protein with other proteins that show similarities with it on the basis of description, alignment, and graphics. The top five protein sequences were obtained and a phylogenetic tree was constructed by using these FASTA sequences on ClustalW, as shown in Figure 2.

Figure 2. Phylogenetic Tree by ClustalW

This tree indicates similarity with some of the proteins but shows 100% similarity with WP_180958168.1, which is another hypothetical protein from a Streptococcus sp. of a different strain. It is also similar to the hepatitis C virus proteins in the coat. There are phylogenetic similarities between different proteins in the capsid and precursor proteins of hepatitis C viruses from different strains.

Table 1. Amino Acid Composition of Protein

3.2. Physiochemical Analysis of Protein

ProtParam was used to perform a comprehensive analysis of physical and chemical properties of protein [9]. These pyscical and chemical properties include amino acid composition, molecular weight, theoretical pI, extinction coefficient, instability index, aliphatic index, and grand average of hydropathicity (GRAVY). Table 1 shows the various types of amino acids and their percentage composition in the hypothetical protein AZJ53_10480. Grand average of hydropathicity (GRAVY) is 0.396. It was concluded that the proteins are hydrophilic in nature.

3.3. Secondary Structure Prediction by PSIPRED

PSIPRED showed the secondary structure of the hypothetical protein along with the colored regions and keys. It indicated that amino acid residues in the protein sequence contribute to the secondary structure, as shown in Figure 3. The figure shows the types of amino acids that make up the protein. Green residues are hydrophobic in nature, pink are polar amino acids, blue are aromatic amino acids, and small non-polar residues are shown in yellow [11, 12].

Figure 3. Amino Acid Types of Protein

3.4. Localization on Subcellular Level

MEMSAT is used for the subcellular localization of hypothetical proteins, their locations, and to determine whether the predicted components belong to the cellular region, extracellular region, or the membrane. The confidence score is provided as the reliability measure adjacent to the results. It confirms the accuracy of the predicted localization, as displayed in Figure 4.

Figure 4. Localization of Protein Residues

Schematics for this hypothetical protein indicate that the yellow region in the figure indicates the extracellular region, the black region indicates the transmembrane helical region of the hypothetical protein, and the white region contributes to the cytoplasmic region of the protein.

3.5 Tertiary Structure Prediction via I-TASSER

I-TASSER only uses the templates of the highest significance in threading alignments, the significance of which is measured by Z-score, that is, the difference between the raw and average scores. The model with the best C-score, RMSD, and TM score was further confirmed and selected as the best predicted model on the basis of its parameters [13]. C-score of the model is -1.54, Z-score is 5.79, TM score is 0.33, and RMSD score is 13.9, as shown in Figure 5. On the basis of these scores, a protein model was selected and used.

Figure 5. 3D Structure Predicted by I-TASSER

3.6. 3D Structure Validation of the Protein

A Ramachandran (RC) plot was used to validate the predicted protein structure. The RC plot displays the distribution of the φ and ψ angles for each residue in the protein structure. These angles define the rotation of peptide bonds which, in turn, determines the conformational geometry of the protein backbone. The x-axis represents the φ angle, which is the rotation around the Cα-N bond. The y-axis represents the ψ angle, which is the rotation around the Cα-C bond. The RC plot consists of three regions, that is, most allowed, allowed, and disallowed. The red area represents the most allowed, yellow represents allowed, and the white region represents disallowed [14]. In Figure 6, 91% of the amino acid residues are in the most allowed region which shows that the protein is good for further research.

Figure 6. Protein Structure Validated by PROCHECK Program

3.7. Domain Prediction

InterPro was used to predict the domain and family of proteins. It showed close similarity to the viral capsid proteins in the hepatitis C virus. Pfam was used to predict the phylogenetic similarity of the protein domain [12]. It also showed significant similarity with the envelop proteins of the hepatitis C virus. For conserved domain analysis, CDNCBI server was used that also showed close similarity to this hypothetical protein. Therefore, it was confirmed that this protein is structurally and functionally related to the envelope protein of the hepatitis C virus.

3.8. Molecular Docking

The 3D structure of the protein was obtained through I-TASSER. The protein showed similarity with the proteins of hepatitis C virus. Therefore, a ligand sofosbuvir, which is effective against hepatitis C virus, was used to dock with the hypothetical protein AZJ53_10480, as mentioned in Table 2 and Figure 7.

Table 2. Affinity Energy from Docking with Ligand orientations

Figure 7. Protein Ligand Dock Complex Visualized by PyMOL

On docking, the first model was determined as the best model because it showed the best affinity, while the remaining models represented different orientations of the drugs to bind to the receptor protein in descending order of affinities. The determined affinity is better than the theoretical affinity. Therefore, the results showed a successful docking of the drug to the hypothetical protein. The docking results were visualized using PyMOL.

3.8.1. Atomic Interaction Analysis. The interaction between protein active sites and ligands was analyzed using PyMOL. Different amino acids showed hydrogen bonding with ligands at different positions. Threonine present at the position 125 showed ionic interactions with the ligand with a bond length of 2.4 angstrom and 2.1 angstrom. The results depicted the best interaction between the hypothetical protein AZJ53_10480 and sofosbuvir and can be used to design drugs against the said protein, as shown in Figure 8.

Figure 8. Analysis of Interaction between Active Sites and Ligand Binding Sites

DISCUSSION

This study was conducted to characterize a hypothetical protein AZJ53_10480 in S. pneumoniae using in silico tools. It aimed to determine the sequence, 2D and 3D structure, as well as the location of the protein in the cell, cellular or transmembrane regions, and at extracellular locations. The functions performed by the protein were also determined using I-TASSER. In order to find out ancestral relationships, homologies, and distant or closely related proteins, certain tools were used that indicated similarities with the proteins in the capsid of hepatitis C virus. Manual and automated docking via AutoDock Vina and Patch Dock were performed by using the ligand Sofosbuvir that is effective against viral proteins. The affinities were found to be quite useful, indicating higher binding affinity as compared to theoretical values. Although the characterization of protein has been achieved in this research, certain impurity has been identified as well within the protein. Hence, it should be refined in vitro in order to completely accept its functions and submission.

This study aligns with previous research on the characterization of hypothetical proteins in various bacterial species, such as Streptococcus pneumoniae [15], Streptococcus mutans [16] and Shigella dysenteriae [17]. These studies emphasized the importance of elucidating the functions of hypothetical proteins to understand bacterial pathogenesis and identify potential drug targets. Additionally, the use of in silico tools for protein characterization is supported by research on protein-DNA interactions [18], annotation of uncharacterized proteins [19], and advances in protein complex analysis [20], highlighting the significance of computational approaches in modern proteomics research.

Moreover, the purification and refinement of the hypothetical protein AZJ53_10480 can benefit from techniques such as biotinylation for efficient purification [21], affinity chromatography for one-step purification of recombinant proteins [22], and tangential flow filtration for novel purification methods [23]. These methods can aid in obtaining high purity proteins for further experimental validation and functional studies. Also, in silico characterization of the hypothetical protein AZJ53_10480 from S. pneumoniae provides valuable insights into its structure, potential functions, and interactions. Further experimental validation and purification are essential to confirm its role and potential applications, especially in the context of developing novel therapeutics against bacterial infections.

4.1. Conclusion

This study carried out the in silico characterization of a hypothetical protein AZJ53_10480 in S. pneumoniae using mutation analysis tools. To check the mutational effect on the biological function of the protein, PROVEAN was used. Using different tools for photochemical properties, subcellular localization, structure, and domain prediction, conserved region mutation analysis of the protein was performed. PSIPRED results showed that the amino acids present in the protein sequence contribute to the secondary structure. PSIPRED cartoons in the form of peaks also showed accuracy because a higher peak indicates a more confident structure. The results of manual docking by AutoDock Vina showed successful docking to the hypothetical protein.

Conflict of Interest

The author of the manuscript has no financial or non-financial conflict of interest in the subject matter or materials discussed in this manuscript.

Data Availability Statement

The data associated with this study will be provided by the corresponding author upon request.

Funding details

This research did not receive grant from any funding source or agency.