Abstract
Neisseria gonorrhoeae, a World Health Organization (WHO) declared superbug and the second-most frequent cause of bacterial sexually transmitted infections worldwide is responsible for gonorrhea. Hypothetical proteins are gene products that are predicted to be encoded by a particular gene based on the DNA sequence, but their specific functions and characteristics have not been experimentally determined or verified. In the context of this research, annotating hypothetical proteins is crucial for identifying their potential as therapeutic targets. Without proper annotation, these proteins would remain vague, hindering efforts to understand their roles in disease. The methodology used aims to bridge this gap by employing algorithm-based tools and software to annotate hypothetical proteins and assess their suitability as therapeutic targets based on factors such as essentiality, virulence, subcellular localization, and druggability. Out of 716 N. gonorrhoeae hypothetical proteins reported in UniProt, assessment of crucial pathogenic factors, including essentiality, virulence, subcellular localization, and druggability, effectively filtered and prioritized the hypothetical proteins for further therapeutic exploration and lead to 5 proteins being chosen as targets. The molecular docking studies conducted identified 10 hits targeting the five targets. Conclusively, this study aided in identification of targets and hit compounds for therapeutic targeting of gonorrhea disease.
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All data generated or analysed during this study are included in this published article [and its supplementary information files].
Abbreviations
- HP:
-
Hypothetical proteins
- ENH:
-
Essential non-homologous
- ORF:
-
Open reading frame
- DEG:
-
Database of essential genes
- DUF:
-
Domains of unknown functions
- BUSCA:
-
Bologna Unified Subcellular Component Annotator
- PSSM:
-
Position specific scoring matrix
- SVM:
-
Support vector machine
- HPIDB:
-
Host pathogen interaction database
- PPI:
-
Protein–protein interactions
- I-TASSER:
-
Iterative threading assembly refinement
- SAVES:
-
Structure analysis and verification server
- RMSD:
-
Root mean square deviation
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GL planned and executed the study, Dr. HT and MKS contributed for writing and fine tuning of the manuscript and Dr. DK reviewed and suggested modifications.
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Lakhanpal, G., Tiwari, H., Shukla, M.K. et al. In silico exploration of hypothetical proteins in Neisseria gonorrhoeae for identification of therapeutic targets. In Silico Pharmacol. 12, 10 (2024). https://doi.org/10.1007/s40203-023-00186-w
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DOI: https://doi.org/10.1007/s40203-023-00186-w