In silico structure prediction and molecular docking analyses to reveal potential binding domain of Hepatitis B virus genotype A2

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Abstract

Hepatitis B Virus (HBV) infects the hepatocytes to cause serious liver diseases. HBeAg regulates the response of immune system to the intracellular capsid act as T-cell tolerogen. The immune response regulation may predispose to chronicity during perinatal infections to prevent the severe liver injuries. Various in silico approaches including comparative modeling, threading approach and ab initio approach were employed for the prediction of 3D structures of the selected protein followed by the validation of the predicted structures through Errat, Procheck and Anolea. The predicted 3D structure of HBeAg revealed overall quality factor of 95.9184%. Interestingly, it was observed that only 1.97% residues were present in outlier region while 98.03% in favored and allowed region. Molecular docking analyses were performed and the attempt was for the identification of novel ligands for HBeAg. The reported compound may regulate the activity and act as regulator of HBeAg. Interestingly, least binding energy of -7.1 Kcal/mol was observed in the reported compound and high binding affinity to predict the binding residues (Asp-51, Phe-53, Val-56, Arg-57, Met-95, Ala-98, Asn-103, Arg-111, Asp-112, Val-115, Val-118 and Asn-119). The function determination of the selected target protein is due to the identification of effective binding sites in protein structures. The reported compound may act as potent molecule and the predicted structure is reliable for the functional studies and structural insights.
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乙型肝炎病毒A2基因型潜在结合域的硅结构预测和分子对接分析
乙型肝炎病毒(HBV)感染肝细胞,引起严重的肝脏疾病。HBeAg作为t细胞耐受原调节免疫系统对胞内衣壳的反应。围产期感染时的免疫反应调节可使其易于发生慢性感染,从而预防严重的肝损伤。采用比较建模、线程法和从头算法等多种计算机方法预测所选蛋白质的三维结构,并通过Errat、Procheck和Anolea对预测结构进行验证。预测的HBeAg三维结构总体质量因子为95.9184%。有趣的是,在离群区残留率仅为1.97%,而在有利区和允许区残留率为98.03%。进行了分子对接分析,并试图鉴定HBeAg的新配体。所报道的化合物可能调节HBeAg的活性并起调节作用。有趣的是,在所报道的化合物中观察到最低结合能为-7.1 Kcal/mol,并且具有高结合亲和力,可以预测结合残基(Asp-51, phe53, Val-56, Arg-57, Met-95, Ala-98, Asn-103, Arg-111, Asp-112, Val-115, Val-118和Asn-119)。所选择的靶蛋白的功能确定是由于在蛋白质结构中识别有效的结合位点。所报道的化合物可能作为有效分子,预测的结构对功能研究和结构见解是可靠的。
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