AbstractP-selectin is an adhesion molecule which plays an important role in the development of inflammation. It is encoded by the SELP gene located on chromosome 1q21-q24. Various single nucleotide polymorphisms (SNPs) ofSELPhave been reported to be associated with various inflammatory disease conditions. The genetics behind these diseases could be better understood by knowing the structural and functional impact of various genetic determinants ofSELP. So far, this is the first comprehensive and systematicin silicoanalysis of SNPs inSELP. A total of 2780 SNPs ofSELPwere retrieved from NCBI dbSNP. Only conserved and validated SNPs with minor allele frequency (MAF) ≥ 0.05 were subjected to further analysis. Based on these criteria, we selected 4 non-synonymous SNPs (nsSNPs) and 119 non-coding SNPs (ncSNPs). The nsSNPs were analyzed for deleterious effects using SIFT, Polyphen-2, nsSNPAnalyzer, SNP & Go, SNPs3, Mutperd and I-mutant web tools. The template prediction for variant structure modeling was performed using MUSTER and SWISS-MODEL. The functional impact of ncSNPs was analyzed by SNPinfo and RegulomeDB. Thein silicoanalysis predicted 3 nsSNPs and 21 ncSNPs as potential candidates for future case-control association studies and functional analysis ofSELP.