Hossain Mohammad Uzzal, Omar Taimur Md, Oany Arafat Rahman, Kibria K M Kaderi, Shibly Abu Zaffar, Moniruzzaman Md, Ali Syed Raju, Islam Md Monirul
Bioinformatics Division, National Institute of Biotechnology, Ganakbari, Ashulia, Savar, Dhaka, 1349 Bangladesh.
2Department of Biotechnology and Genetic Engineering, Life Science Faculty, Mawlana Bhashani Science and Technology University, Santosh, Tangail, 1902 Bangladesh.
3 Biotech. 2018 Feb;8(2):81. doi: 10.1007/s13205-018-1106-5. Epub 2018 Jan 16.
Lassa virus (LASV) is responsible for an acute viral hemorrhagic fever known as Lassa fever. Sequence analyses of LASV proteome identified the most immunogenic protein that led to predict both T-cell and B-cell epitopes and further target and binding site depiction could allow novel drug findings for drug discovery field against this virus. To induce both humoral and cell-mediated immunity peptide sequence SSNLYKGVY, conserved region 41-49 amino acids were found as the most potential B-cell and T-cell epitopes, respectively. The peptide sequence might intermingle with 17 HLA-I and 16 HLA-II molecules, also cover 49.15-96.82% population coverage within the common people of different countries where Lassa virus is endemic. To ensure the binding affinity to both HLA-I and HLA-II molecules were employed in docking simulation with suggested epitope sequence. Further the predicted 3D structure of the most immunogenic protein was analyzed to reveal out the binding site for the drug design against Lassa Virus. Herein, sequence analyses of proteome identified the most immunogenic protein that led to predict both T-cell and B-cell epitopes and further target and binding site depiction could allow novel drug findings for drug discovery field against this virus.
拉沙病毒(LASV)可引发一种名为拉沙热的急性病毒性出血热。对拉沙病毒蛋白质组进行的序列分析确定了最具免疫原性的蛋白质,这有助于预测T细胞和B细胞表位,进一步描绘靶点和结合位点可为针对该病毒的药物研发领域发现新药物。为诱导体液免疫和细胞介导免疫,发现肽序列SSNLYKGVY(保守区域41 - 49个氨基酸)分别是最具潜力的B细胞和T细胞表位。该肽序列可能与17种HLA - I和16种HLA - II分子相互作用,在拉沙病毒流行的不同国家的普通人群中覆盖率也达到49.15% - 96.82%。为确保与HLA - I和HLA - II分子的结合亲和力,采用建议的表位序列进行对接模拟。此外,对最具免疫原性的蛋白质的预测三维结构进行分析,以揭示针对拉沙病毒的药物设计的结合位点。在此,蛋白质组的序列分析确定了最具免疫原性的蛋白质,这有助于预测T细胞和B细胞表位,进一步描绘靶点和结合位点可为针对该病毒的药物研发领域发现新药物。