Zika virus (ZIKV) has been identified as a cause of adverse outcomes of pregnancy, including microcephaly and other congenital diseases. Most people infected with ZIKV do not show any symptoms.… Click to show full abstract
Zika virus (ZIKV) has been identified as a cause of adverse outcomes of pregnancy, including microcephaly and other congenital diseases. Most people infected with ZIKV do not show any symptoms. Development of a method to discriminate dengue virus (DENV) and ZIKV infections has been challenging, and efficient assays for patient management are limited, attributable to high levels of cross-reactivity among co-circulating Flaviviruses. Thus, there is an urgent need for a specific high-throughput diagnostic assay to discriminate ZIKV infections from other Flavivirus infections. Methods: A novel epitope peptide of the ZIKV envelope protein was predicted using three immune epitope database analysis tools and then further modified. A molecular docking study was conducted using three-dimensional structures of the ZIKV envelope and peptide. Experimentally, interactions between the selected peptides and virus were assessed via a fluorescence-linked sandwich immunosorbent assay (FLISA), and performance of peptide-linked sandwich FLISA was evaluated in virus-spiked human serum and urine. Results: The Z_10.8 peptide (KRAVVSCAEA) was predicted to be a suitable detector, with a higher binding affinity than other candidates based on four criteria (binding affinity, root mean square deviation, position of amine residue of lysine at the N-terminus, and interactive site) in a docking study. Z_10.8 was significantly more efficient at detecting ZIKV than the other two peptides, as shown in the direct FLISA (P < 0.001). Further, the equilibrium dissociation constant (Kd) for the Z_10.8 peptide was 706.0 ± 177.9 (mean ± SD, nM), with specificity to discriminate ZIKV from DENV. The limit of detection for the sandwich FLISA was calculated as 1×104 tissue culture infective dose (TCID)50/mL. The presence of serum or urine did not interfere with the performance of the Z_10.8-linked sandwich FLISA. Conclusion: Four criteria are suggested for the development of an in silico modeled peptide aptamer; this computerized peptide aptamer discriminated ZIKV from DENV via immunoassay.
               
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