Abstract
Background: Cathelicidin, a human host defense peptide, plays a salubrious role in innate host defense against human pathogens. Despite the extensive studies on the antimicrobial function of Cathelicidin, there is a lack of information on this peptide's deleterious single nucleotide polymorphisms (SNPs) that potentially alter the disease susceptibility and hence the current study.
Objective: To predict Cathelicidin's structural and functional deleterious non-synonymous single nucleotide polymorphisms.
Methods: The non-synonymous SNPs of Cathelicidin were investigated using computational prediction tools like SIFT, Polyphen, PROVEAN, MusiteDeep, I-Mutant, and STRING.
Results: The present study predicted 23 potentially harmful nsSNP of Cathelicidin. Among these, 14 were highly conserved, 8 were average conserved, and 1 alone was variable. Phosphorylation was observed in serine and threonine residues using post-translational modification. Further mutation 3D predicted 11 clustered and 13 covered mutations in cathelicidin variants. The structural distribution of high-risk nsSNPs predicted 80 alpha helixes, 0 random coils, 19 extended strands, and 4 beta turns. Among 23 predicted deleterious SNPs, 9 nsSNPs alone showed mutation effect based on the HOPE structural and functional analysis. The direct functional interaction pattern of Cathelicidin with other proteins, FPR2, PRTN3, TLR9, IGF1R, and JUN, was observed.
Conclusion: The identified deleterious nsSNPs could help understand the mutation effect of Cathelicidin in disease susceptibility and drug discovery.
Graphical Abstract
[http://dx.doi.org/10.1172/JCI17545] [PMID: 12782669]
[http://dx.doi.org/10.1034/j.1600-0714.2001.300601.x] [PMID: 11459317]
[http://dx.doi.org/10.1001/archotol.129.2.211] [PMID: 12578451]
[http://dx.doi.org/10.2174/138161207782110435] [PMID: 17979750]
[http://dx.doi.org/10.3390/biom7040080] [PMID: 29206168]
[http://dx.doi.org/10.1007/s11515-017-1432-8]
[http://dx.doi.org/10.3390/dj5010012] [PMID: 29563418]
[http://dx.doi.org/10.5114/ceji.2015.51359] [PMID: 26557038]
[http://dx.doi.org/10.1016/j.jmgm.2022.108368] [PMID: 36335830]
[http://dx.doi.org/10.1182/blood-2007-05-088682] [PMID: 17827388]
[http://dx.doi.org/10.3389/fimmu.2019.00420] [PMID: 30906297]
[http://dx.doi.org/10.3389/fcimb.2015.00099] [PMID: 26734583]
[http://dx.doi.org/10.1093/nar/gks539] [PMID: 22689647]
[http://dx.doi.org/10.1371/journal.pone.0046688] [PMID: 23056405]
[http://dx.doi.org/10.1093/bioinformatics/btn435] [PMID: 18757876]
[http://dx.doi.org/10.1093/bioinformatics/btl423] [PMID: 16895930]
[http://dx.doi.org/10.1093/nar/gki375] [PMID: 15980478]
[http://dx.doi.org/10.1093/nar/gkq399] [PMID: 20478830]
[http://dx.doi.org/10.1016/j.imu.2020.100447]
[http://dx.doi.org/10.1093/bioinformatics/11.6.681] [PMID: 8808585]
[http://dx.doi.org/10.1186/1471-2105-11-548] [PMID: 21059217]
[http://dx.doi.org/10.1093/nar/gkn760] [PMID: 18940858]
[http://dx.doi.org/10.1155/2015/124630] [PMID: 26495027]
[http://dx.doi.org/10.1111/j.1600-051X.2010.01664.x] [PMID: 21323710]
[http://dx.doi.org/10.1038/onc.2011.239] [PMID: 21685939]
[http://dx.doi.org/10.1111/jcpe.12879] [PMID: 29446150]
[http://dx.doi.org/10.1111/exd.14200] [PMID: 32997837]
[http://dx.doi.org/10.1128/IAI.02016-05] [PMID: 16926422]
[http://dx.doi.org/10.1371/journal.pone.0106766] [PMID: 25187958]
[http://dx.doi.org/10.1902/jop.2009.080532] [PMID: 19485828]
[http://dx.doi.org/10.1111/j.1600-0757.2009.00310.x] [PMID: 19878474]
[http://dx.doi.org/10.1021/acsomega.0c00189] [PMID: 32363280]