Structural Homology of HHV-6B Epitopes as Candidates for Molecular Mimicry Triggers of Type One Diabetes Mellitus Onset

Molecular mimicry is a mechanism by which an infectious agent may trigger an autoimmune response through structural or sequence similarity to self-antigens. Identifying potential molecular mimics is critical to understanding autoimmune disorders, including type 1 diabetes mellitus (T1DM). Human herpesvirus 6B (HHV-6B), a common childhood virus implicated in multiple autoimmune conditions, has been epidemiologically linked to a significant increased risk of T1DM for individuals with a genetic predisposition. However, the connection between HHV-6B and T1DM remains unresolved, as known HHV-6B epitopes show minimal sequence homology with T1DM autoantigens. This study explores whether HHV-6B can act as a molecular mimic by assessing structural and biding similarities between HHV-6B-derived and T1DM autoantigen-derived epitopes. Epitope peptide structures and their interactions with T1DM autoantigens were modeled using Boltz-2. Several HHV-6B epitopes studied here demonstrated high structural alignment with T1DM epitopes, but even when structural homology is lacking, the HHV-6B and T1DM epitopes fit into the same binding region of HLA molecules, suggesting a plausible mechanism for T cell cross-reactivity. These findings provide computational evidence that HHV-6B may act as a molecular mimic contributing to autoimmune responses in T1DM genetically susceptible individuals. This study demonstrates that structural modeling is a useful tool for identifying potential mimicry candidates that sequence-based methods may not find, underscoring the importance of integrating structure-based modeling including docking into molecular mimicry prediction pipelines. Structural modeling of both the 50 epitopes from the 25 candidate pairs from the Suleman studies and those three from Bach’s paper was performed with Boltz-2 (v.2.2.0), an open-source deep learning method that predicts biomolecular structures and binding sites with great accuracy. Boltz-2 requires protein inputs of at least ten amino acids, and many of the epitopes considered here (Table 1 and 2) did not meet this requirement, so each epitope sequence was expanded symmetrically using the full protein sequences from UniProt (https://www.uniprot.org/). The extended sequences are given in Table S1 of the Supplementary maerial. In all cases selected for analysis, model 0 from Boltz-2 consistently exhibited the highest confidence scores, and these models were used in subsequent analyses. The confidence scores for all the calculations average 0.74 for the structures of the isolated epitopes and 0.87 for the structures of the epitopes bound to the HLA molecules. These values are within the range of good Boltz-2 prediction.分子模拟（molecular mimicry）是指感染因子通过与自身抗原的结构或序列相似性，触发自身免疫应答的机制。鉴定潜在的分子模拟物，对于理解包括1型糖尿病（type 1 diabetes mellitus, T1DM）在内的自身免疫疾病至关重要。人类疱疹病毒6B（HHV-6B）作为一种与多种自身免疫病症相关的常见儿童病毒，流行病学研究已证实其可使具有遗传易感性的个体罹患T1DM的风险显著升高。然而，HHV-6B与T1DM之间的关联仍未明确：已知的HHV-6B表位与T1DM自身抗原的序列同源性极低。本研究通过比较HHV-6B来源表位与T1DM自身抗原来源表位的结构与结合相似性，探究HHV-6B是否可通过分子模拟发挥致病作用。研究采用Boltz-2对表位肽结构及其与T1DM自身抗原的相互作用进行建模。本研究中分析的多个HHV-6B表位展现出与T1DM表位高度的结构对齐度；即便不存在结构同源性，HHV-6B与T1DM表位仍可结合至人类白细胞抗原（HLA）分子的同一结合区域，这提示T细胞交叉反应性的潜在机制。本研究的发现提供了计算证据，表明HHV-6B可作为分子模拟因子，参与遗传易感个体中T1DM相关的自身免疫应答。本研究证明，结构建模是识别序列基方法无法发现的潜在模拟候选物的有效工具，同时强调了将包括对接（docking）在内的基于结构的建模整合至分子模拟预测流程中的重要性。 本研究针对Suleman研究中25个候选对所包含的50个表位，以及Bach论文中的3个表位，均采用Boltz-2（v.2.2.0）进行结构建模。Boltz-2是一种开源深度学习方法，可高精度预测生物分子结构与结合位点。Boltz-2要求蛋白质输入序列长度至少为10个氨基酸，而本研究中考虑的诸多表位（见表1与表2）未满足该要求，因此研究人员借助通用蛋白质资源库（UniProt，https://www.uniprot.org/）中的完整蛋白质序列，对每个表位序列进行对称式延伸。延伸后的序列详见补充材料中的表S1。在所有纳入分析的案例中，Boltz-2生成的模型0始终展现出最高的置信度得分，后续分析均采用该模型。所有计算的置信度得分平均值为：孤立表位结构0.74，与HLA分子结合的表位结构0.87，该数值处于Boltz-2预测结果的良好置信区间范围内。