Knowledge of immunodominant B-cell epitopes is essential to design powerful diagnostic strategies aiming for antibody detection. Outstanding progress in computational prediction has achieved a significant contribution to the biomedical fields, including immunodiagnosis. In silico analysis may have an even more important role when information concerning antigens from etiologic agents of neglected diseases, such as leprosy, is scarce. The aim of this study was to provide mapping of B-cell epitopes from two Mycobacterium leprae-derived antigens (Ag85B and ML2055), confirm their antigenicity, and to assess the ability of in silico immunoinformatics tools to accurately predict them. Linear B-cell epitopes predicted by ABCpred and SVMTrip servers were compared to antigenic regions of synthetic overlapping peptides that exhibited reactivity to antibodies from patients with leprosy. Our in vitro results identified several immunodominant regions that had also been indicated by in silico prediction, providing agreement between experimental and simulated data. After chemical synthesis, we used enzyme-linked immunosorbent assays to determine the effectiveness of the first identified sequence (GTNVPAEFLENFVHG) which had 72 % sensitivity and 78 % specificity (AUC = 0.79) while the second one (PVSSEAQPGDPNAPS) had 72 % sensitivity and 93.8 % specificity (AUC = 0.85). Using dot blotting, an easy-to-read visual test, both peptides could distinguish sera from patients with leprosy from those with tuberculosis and from sera of healthy volunteers. Our findings suggest that these synthetic peptides, with some refinement, may be useful as serological diagnostic antigens for leprosy. In addition, it was displayed that immunoinformatics provides reliable information for mapping potential B-cell epitopes for development of peptide-based diagnostic assays for neglected diseases.

免疫优势 B 细胞表位的知识对于设计针对抗体检测的强大诊断策略至关重要。计算预测方面的突出进展为包括免疫诊断在内的生物医学领域做出了重大贡献。当关于麻风等被忽视疾病的病原体的抗原信息稀缺时，计算机分析可能会发挥更重要的作用。本研究的目的是提供两种麻风分枝杆菌衍生抗原（Ag85B 和 ML2055）的 B 细胞表位图谱，确认它们的抗原性，并评估计算机免疫信息学工具来准确预测它们。将 ABCpred 和 SVMTrip 服务器预测的线性 B 细胞表位与对麻风患者抗体表现出反应性的合成重叠肽的抗原区域进行比较。我们的体外结果确定了几个免疫显性区域，这些区域也被计算机模拟预测，提供实验数据和模拟数据之间的一致性。化学合成后，我们使用酶联免疫吸附测定来确定第一个鉴定序列 (GTNVPAEFLENFVHG) 的有效性，该序列具有 72% 的灵敏度和 78% 的特异性 (AUC = 0.79)，而第二个 (PVSSEAQPGDPNAPS) 具有 72% 的灵敏度和 93.8 ％特异性（AUC = 0.85）。使用斑点印迹（一种易于阅读的视觉测试），两种肽都可以区分麻风患者的血清、结核病患者的血清以及健康志愿者的血清。我们的研究结果表明，这些经过改进的合成肽可能可用作麻风病的血清学诊断抗原。此外，