Outer membrane protein 100 of Aggregatibacter actinomycetemcomitans act as a biopharmaceutical target for photodynamic therapy: An in silico analysis

Virtual screening and computational simulation analysis of antimicrobial photodynamic therapy using propolis-benzofuran A to control of Monkeypox

BACKGROUND

Monkeypox is a viral zoonotic disease and there are no available treatments that specifically target the monkeypox virus. Antimicrobial photodynamic therapy (aPDT) is a non-invasive approach that has been introduced as a targeted adjuvant treatment against various microbial infections. In this study, we used a computational strategy to investigate the potential of aPDT using propolis-benzofuran A against the Monkeypox virus.

METHODS

In this in silico study, the evaluation of drug-likeness, molecular properties, and bioactivity of propolis-benzofuran A was carried out using SwissADME. Pro-Tox II and OSIRIS servers were used to identify the organ toxicities and toxicological endpoints of propolis-benzofuran A. Molecular docking approach was employed to screen the potential binding modes of propolis-benzofuran A ligand with the Monkeypox virus A48R protein (PDB ID: 2V54).

RESULTS

The results of the computational investigation revealed that propolis-benzofuran A obeyed all the criteria of Lipinski's rule of five and exhibited drug-likeness. The photosensitizing agent tested was categorized as toxicity class-5 and was found to be non-hepatotoxic, non-carcinogenic, non-mutagenic, and non-cytotoxic. The docking studies employing a predicted three-dimensional model of Monkeypox virus A48R protein with propolis-benzofuran A ligand exhibited good binding affinity (-7.84 kcal/mol).

DISCUSSION

The computational simulation revealed that propolis-benzofuran A had a strong binding affinity with the Monkeypox virus A48R protein. Hence, aPDT based on this natural photosensitizer can be proposed as an adjuvant treatment against the Monkeypox virus.

Differential Virulence of Aggregatibacter actinomycetemcomitans Serotypes Explained by Exoproteome Heterogeneity

Aggregatibacter actinomycetemcomitans (Aa) is a Gram-negative bacterial pathogen associated with periodontitis and nonoral diseases like rheumatoid arthritis and Alzheimer´s disease. Aa isolates with the serotypes a, b, and c are globally most prevalent. Importantly, isolates displaying these serotypes have different clinical presentations. While serotype b isolates are predominant in severe periodontitis, serotypes a and c are generally encountered in mild periodontitis or healthy individuals. It is currently unknown how these differences are reflected in the overall secretion of virulence factors. Therefore, this study was aimed at a comparative analysis of exoproteomes from different clinical Aa isolates with serotypes a, b, or c by mass spectrometry, and a subsequent correlation of the recorded exoproteome profiles with virulence. Overall, we identified 425 extracellular proteins. Significant differences in the exoproteome composition of isolates with different serotypes were observed in terms of protein identification and abundance. In particular, serotype a isolates presented more extracellular proteins than serotype b or c isolates. These differences are mirrored in their virulence in infection models based on human salivary gland epithelial cells and neutrophils. Remarkably, serotype a isolates displayed stronger adhesive capabilities and induced more lysis of epithelial cells and neutrophils than serotype b or c isolates. Conversely, serotype c isolates showed relatively low leukotoxicity, while provoking NETosis to similar extents as serotype a and b isolates. Altogether, we conclude that the differential virulence presentation by Aa isolates with the dominant serotypes a, b, or c can be explained by their exoproteome heterogeneity. IMPORTANCE Periodontitis is an inflammatory disease that causes progressive destruction of alveolar bone and supporting tissues around the teeth, ultimately resulting in tooth loss. The bacterium Aggregatibacter actinomycetemcomitans (Aa) is a prevalent causative agent of periodontitis, but this oral pathogen is also associated with serious extraoral diseases like rheumatoid arthritis and Alzheimer's disease. Clinical Aa isolates are usually distinguished by serotyping, because of known serotype-specific differences in virulence. Aa with serotype b is associated with aggressive forms of periodontitis, while isolates with serotypes a or c are usually encountered in cases of mild periodontitis or healthy individuals. The molecular basis for these differences in virulence was so far unknown. In the present study, we pinpoint serotype-specific differences in virulence factor production by clinical Aa isolates. We consider these findings important, because they provide new leads for future preventive or therapeutic approaches to fight periodontitis and associated morbidities.

Molecular Modeling and Simulation Analysis of Antimicrobial Photodynamic Therapy Potential for Control of COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can enter the host cells by binding the viral surface spike glycoprotein (SG) to angiotensin-converting enzyme 2. Since antiviral photodynamic therapy (aPDT) has been described as a new method for inhibiting viral infections, it is important to evaluate whether it can be used as a photoactivated disinfectant to control COVID-19. In this in silico study, SARS-CoV-2-SG was selected as a novel target for curcumin as a photosensitizer during aPDT to exploit its physicochemical properties, molecular modeling, hierarchical nature of protein structure, and functional analysis using several bioinformatics tools and biological databases. The results of a detailed computational investigation revealed that SARS-CoV-2-SG is most similar to 6VXX_A, with 100% query cover and identity. The predicted structure of SARS-CoV-2-SG displayed that it is a protein with a positive charge and random coil dominates other secondary structures located outside the viral cell. The protein-protein interaction network showed that SARS-CoV-2-SG interacted with ten potential interacting partners. In addition, primary screening of binding modes through molecular docking showed that curcumin desires to bind and interact with residues of SARS-CoV-2-SG as the main site to enhance the yield of aPDT. Overall, the computer simulation reveals that SARS-CoV-2-SG can be a suitable target site for interaction with curcumin during aPDT.

Comparative Transcriptome Analysis Reveals Differentially Expressed Genes Related to Antimicrobial Properties of Lysostaphin in Staphylococcus aureus

Comparative transcriptome analysis and de novo short-read assembly of S. aureus Newman strains revealed significant transcriptional changes in response to the exposure to triple-acting staphylolytic peptidoglycan hydrolase (PGH) 1801. Most altered transcriptions were associated with the membrane, cell wall, and related genes, including amidase, peptidase, holin, and phospholipase D/transphosphatidylase. The differential expression of genes obtained from RNA-seq was confirmed by reverse transcription quantitative PCR. Moreover, some of these gene expression changes were consistent with the observed structural perturbations at the DNA and RNA levels. These structural changes in the genes encoding membrane/cell surface proteins and altered gene expressions are the candidates for resistance to these novel antimicrobials. The findings in this study could provide insight into the design of new antimicrobial agents.

Computational Biology Analysis of COVID-19 Receptor-Binding Domains: A Target Site for Indocyanine Green Through Antimicrobial Photodynamic Therapy

Introduction: The receptor-binding domain (RBD) in SARS-CoV-2 binds strongly to angiotensin-converting enzyme 2 (ACE2) receptors and causes coronavirus disease 2019 (COVID-19). Antimicrobial photodynamic therapy (aPDT) is a well-established treatment option for the treatment of several viral infections. This in silico study was conducted to target the RBD of SARS-CoV-2 as a target site for aPDT. Methods: SARS-CoV-2-RBD was selected as a novel target for indocyanine green (ICG) as a photosensitizer during aPDT to exploit its molecular modeling, hierarchical nature of protein structure, and physico-chemical properties using several bioinformatic tools. The binding mode of the RBD to ICG was assessed via protein-ligand docking. Results: The results of a computational biology analysis revealed that SARS-CoV-2-RBD has 223 amino acids with a molecular weight of 25098.40 Da. RBD is most similar to 6W41 with an E-value of 4e-167, identity of 100%, and query cover of 100%. The aliphatic index of the RBD protein sequences was 71.61, suggesting that the protein is stable in a broad spectrum of temperatures. The predicted structure of RBD showed that it is a protein with a positive charge and a random coil structure (69.51%). Four ligands were modeled in this entry, including one N-acetyl-D-glucosamine (NAG), one glycerol (GOL), and two sulfate ions (SO4 ), to which ICG desires to bind in the molecular docking analysis. Conclusion: Molecular modeling and simulation analysis showed that SARS-CoV-2-RBD could be a substrate for binding to ICG during aPDT to control the spread of COVID-19.