Targeting Essential Hypothetical Proteins of Pseudomonas aeruginosa PAO1 for Mining of Novel Therapeutics: An In Silico Approach

Comparative proteomic analysis to annotate the structural association of the hypothetical proteins from the conserved domain of P. aeruginosa as novel vaccine candidates

OBJECTIVES

Pseudomonas aeruginosa, identified as an ESKAPE pathogen, contributes to severe clinical diseases worldwide and despite its prevalence an effective vaccine or treatment remains elusive. Numerous computational methods are being employed to target hypothetical proteins (HPs). Presently, no studies have predicted multi-epitope vaccines for these HPs.

RESULTS

Totally, 877 HPs from P. aeruginosa were included in the study and the data showcased here illustrate a methodical approach to prioritize the proteome by employing diverse comparative proteomics. The study employed physicochemical property assessment and conserved domain analysis to identify stable and immunologically pertinent proteins for epitope prediction. The VaxiJen2.0 antigenicity assessment aided in epitope selection, contributing to the foundational steps in vaccine development by predicting T-cell and B-cell epitopes. Potential T and B cell epitopes with high antigenicity, non-toxic categorization, and robust binding affinities were identified in the investigation. The periplasmic HP WP_132813935.1 was predicted as conserved, stable, and soluble. The T-cell peptide RTSMRALAY and the B-cell peptide MPVYLYLM were predicted to be probable non-allergen and demonstrated strong binding with MHC class I allele HLA-C*03:03.

CONCLUSIONS

This research provides a comprehensive approach to predict T and B cell epitopes for conditions associated with P. aeruginosa, offering a candidate pool for tailored vaccine development. However, the efficacy of these epitopes in vaccine development necessitates clinical validation and testing for confirmation.

PBITV3 : A robust and comprehensive tool for screening pathogenic proteomes for drug targets and prioritizing vaccine candidates

Rise of life-threatening superbugs, pandemics and epidemics warrants the need for cost-effective and novel pharmacological interventions. Availability of publicly available proteomes of pathogens supports development of high-throughput discovery platforms to prioritize potential drug-targets and develop testable hypothesis for pharmacological screening. The pipeline builder for identification of target (PBIT) was developed in 2016 and updated in 2021, with the purpose of accelerating the search for drug-targets by integration of methods like comparative and subtractive genomics, essentiality/virulence and druggability analysis. Since then, it has been used for identification of drugs and vaccine targets, safety profiling of multiepitope vaccines and mRNA vaccine construction against a broad-spectrum of pathogens. This tool has now been updated with functionalities related to systems biology and immuno-informatics and validated by analyzing 48 putative antigens of Mycobacterium tuberculosis documented in literature. PBITv3 available as both online and offline tools will enhance drug discovery against emerging drug-resistant infectious agents. PBITv3 can be freely accessed at http://pbit.bicnirrh.res.in/.

Recent advances in the characterization of essential genes and development of a database of essential genes

Over the past few decades, there has been a significant interest in the study of essential genes, which are crucial for the survival of an organism under specific environmental conditions and thus have practical applications in the fields of synthetic biology and medicine. An increasing amount of experimental data on essential genes has been obtained with the continuous development of technological methods. Meanwhile, various computational prediction methods, related databases and web servers have emerged accordingly. To facilitate the study of essential genes, we have established a database of essential genes (DEG), which has become popular with continuous updates to facilitate essential gene feature analysis and prediction, drug and vaccine development, as well as artificial genome design and construction. In this article, we summarized the studies of essential genes, overviewed the relevant databases, and discussed their practical applications. Furthermore, we provided an overview of the main applications of DEG and conducted comprehensive analyses based on its latest version. However, it should be noted that the essential gene is a dynamic concept instead of a binary one, which presents both opportunities and challenges for their future development.