Gardner Ryan, Wilkins Joshua, Mistry Sejal, Gouripeddi Ramkiran, Facelli Julio C
Weber State University and University of Wisconsin-Madison.
Department of Biomedical Informatics.
bioRxiv. 2025 Sep 4:2025.08.29.673145. doi: 10.1101/2025.08.29.673145.
Molecular mimicry, where foreign and self-peptides contain similar epitopes, can induce autoimmune responses. Identifying potential molecular mimics and studying their properties is key to understanding the onset of autoimmune diseases such as type 1 diabetes mellitus (T1DM). Previous work identified pairs of infectious epitopes (E) and T1DM epitopes (E) that demonstrated sequence homology; however, structural homology was not considered. Correlating sequence homology with structural properties is important for translational investigation of potential molecular mimics. This work compares sequence homology with structural homology by calculating the structures and electrostatic potential surfaces of the epitope pairs identified in previous work from our laboratory.
For each pair of E and E, the root mean square deviations (RMSD) were calculated between their predicted structures and their electrostatic potentials. Structures were predicted using the AlphaFold software program. Of the 53 epitope pairs considered here, only 10 did not exhibit any matching (i.e. less than 3 residues overlap). When considering all residues the RMSD ranges from 0.33 Å to 11.66 Å with an average of 2.68 Å. Twenty-two pairs (42%) have RMSD of less than 1.5 Å and 30 (58%) less than 3 Å.
Most of the E/E pairs selected by sequence homology show similar structural and electrostatic distributions, indicating that the E may also bind to the same protein targets, i.e. the major histocompatibility complex molecules, for T1DM, leading to molecular mimicry onset of the disease. These findings suggest that searching for epitope pairs using sequence homology, a much less computationally demanding approach, leads to strong candidates for molecular mimicry that should be considered for further study. But structure homology, electrostatic potential calculations and full docking calculations may be necessary to advance the in-silico molecular mimicry predictions, which may be useful to select the most promising candidates for experimental studies.
分子模拟是指外来肽和自身肽含有相似表位，可诱导自身免疫反应。识别潜在的分子模拟物并研究其特性是理解诸如1型糖尿病（T1DM）等自身免疫性疾病发病机制的关键。先前的研究确定了具有序列同源性的感染性表位（E）和T1DM表位（E）对；然而，未考虑结构同源性。将序列同源性与结构特性相关联对于潜在分子模拟物的转化研究很重要。本研究通过计算我们实验室先前工作中确定的表位对的结构和静电势表面，比较了序列同源性与结构同源性。
对于每对E和E，计算了它们预测结构之间以及静电势之间的均方根偏差（RMSD）。使用AlphaFold软件程序预测结构。在此考虑的53对表位对中，只有10对没有任何匹配（即重叠少于3个残基）。考虑所有残基时，RMSD范围为0.33 Å至11.66 Å，平均为2.68 Å。22对（42%）的RMSD小于1.5 Å，30对（58%）小于3 Å。
通过序列同源性选择的大多数E/E对显示出相似的结构和静电分布，表明E也可能与T1DM的相同蛋白质靶点即主要组织相容性复合体分子结合，从而导致该疾病的分子模拟发病。这些发现表明，使用序列同源性搜索表位对是一种计算要求低得多的方法，可产生用于分子模拟的有力候选物，应考虑对其进行进一步研究。但可能需要结构同源性、静电势计算和完全对接计算来推进计算机模拟分子模拟预测，这可能有助于选择最有前景的候选物用于实验研究。
