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. 2021;12(2):93-104.
doi: 10.1007/s42485-021-00065-y. Epub 2021 May 18.

Discovering mycobacterial lectins as potential drug targets and vaccine candidates for tuberculosis treatment: a theoretical approach

Shobana Sundar  1 , Lokesh Thangamani  1 , Shanmughavel Piramanayagam  1 , Jeyakumar Natarajan  2
Affiliations

Discovering mycobacterial lectins as potential drug targets and vaccine candidates for tuberculosis treatment: a theoretical approach

Shobana Sundar et al. J Proteins Proteom. 2021.

Abstract

M. tuberculosis proliferates within the macrophages during infection and they are bounded by carbohydrates in the cell wall, called lectins. Despite their surface localization, the studies on exact functions of lectins are unexplored. Hence, in our study, using insilico approaches, 11 potential lectins of Mtb was explored as potential drug targets and vaccine candidates. Initially, a gene interaction network was constructed for the 11 potential lectins and identified its functional partners. A gene ontology analysis was also performed for the 11 mycobacterial lectins along with its functional partners and found most of the proteins are present in the extracellular region of the bacterium and belongs to the PE/PPE family of proteins. Further, molecular docking studies were performed for two of the potential lectins (Rv2075c and Rv1917c). A novel series of quinoxalinone and fucoidan derivatives have been made to dock against these selected lectins. Molecular docking study reveals that quinoxalinone derivatives showed better affinity against Rv2075c, whereas fucoidan derivatives have good binding affinity against Rv1917c. Moreover, the mycobacterial lectins can interact with the host and they are considered as potential vaccine candidates. Hence, immunoinformatics study was carried out for all the 11 potential lectins. B-cell and T-cell binding epitopes were predicted using insilico tools. Further, an immunodominant epitope 1062SIPAIPLSVEV1072 of Rv1917c was identified, which was predicted to bind B-cell and most of the MHC alleles. Thus, the study has explored that mycobacterial lectins could be potentially used as drug targets and vaccine candidates for tuberculosis treatment.

Supplementary information: The online version contains supplementary material available at 10.1007/s42485-021-00065-y.

Keywords: Gene network analysis; Immunoinformatics; Molecular docking; Mycobacterial lectins; Mycobacterium tuberculosis.

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Conflict of interest statement

Conflict of interestAll the authors declare that they have none conflict of interest.

Figures

Fig. 1
Fig. 1
Gene interaction network of the putative 11 mycobacterial lectins retrieved from Cytoscape. Nodes represent individual proteins in the network
Fig. 2
Fig. 2
Clustering analysis by MCODE app on the retrieved Cytoscape gene interaction network. Eight clusters were obtained and are marked as C1–C8. Nodes represent individual proteins in the network
Fig. 3
Fig. 3
Gene ontology analysis of the 11 mycobacterial lectins along with their functional partners. a Graph depicting the number of genes in different components of the cell. b Graph depicting the number of genes involved in different biochemical process. c Graph depicting the number of genes having different INTERPRO domains. d Graph depicting the number of genes having different PFAM domains
Fig. 4
Fig. 4
Homology modelling and Molecular docking studies of Rv2075c and Rv1917c. a Homology model of Rv2075c. b Molecular docking of Quinoxaline derivative against Rv2075c.The hydrogen bonds are depicted in green dotted lines and the bond length is given. c. Homology model of Rv1917c. d Molecular docking of Fucoidan derivative against Rv1917c.The hydrogen bonds are depicted in green dotted lines
Fig. 5
Fig. 5
Immunoinformatics studies. a Homology model of the peptide1062SIPAIPLSVEV1072. b Molecular docking of the peptide 1062SIPAIPLSVEV1072with TLR2 receptor. c Peptide 1062SIPAIPLSVEV1072interactions with the TLR2 receptor
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