人肠道病毒71型和柯萨奇病毒A16型B细胞线性表位的生物信息学预测

A bioinformatics method for prediction of B cellular linear epitopes for human enterovirus 71 and Coxsackievirus A16

发展了人肠道病毒B细胞线性表位(简称线性表位)的生物信息学预测算法,系统性地预测和比较了人肠道病毒71型(Enterovirus71,EV71)和柯萨奇病毒A16型(CoxsackievirusA16,CVA16)的线性表位.结果显示:EV71和CVA16结构蛋白(Viral Protein, VP)上都有16个线性表位,2种肠道病毒的线性表位的位置高度一致,但氨基酸序列保守性较低,大多数表位都存在至少3个氨基酸残基的差异,提示2种病毒的线性表位具有血清型特异性,这很可能是两者不能交叉反应的原因.线性表位主要分布在β链之间的环上和C-末端,分别有13个(81.3%)和2个(12.5%)表位.与文献报道相比较,16个线性表位中,分别有6个(37.5%) EV71和12个(75%) CVA16的表位已被实验验证.特别是实验研究重点关注的VP1,6个预测表位中,分别有4个(66.7%) EV71的预测表位和5个(83.3%)CVA16的预测表位已被实验所验证.说明算法具有较高的预测可靠度.线性表位的实验研究主要集中在VP1,预测结果提示VP2和VP3也能形成表位,应该加以重视.生物信息学算法通过预测和筛选潜在的线性表位,能够大大降低实验负荷,为包括EV71和CVA16在内的人肠道病毒的研究提供有力支持.对肠道病毒线性表位的预测,有助于更好地监测和预警手足口病疫情,辅助疫苗的研发和准备.

A bioinformatics method was developed to predict the B cellular linear epitopes for human enteroviruses. The linear epitopes of enterovirus 71 (EV71) and coxsackievirus A16 (CVA16) were systematically predicted and compared. The results show that both EV71 and CVA16 had 16 linear epitopes in structural proteins (VPs). Although the positions of the epitopes were highly accordant, the homologies of the amino acid sequences were less conservative and there were at least three mutations for the majority of the epitopes. This implied that the epitopes were serotype-specific and caused the low titers of cross-reactivity. The loops between the β strands (13/16, 81.3%) and the C-terminals (2/16, 12.5%) were discovered as being enrichment of the epitopes. Among 16 epitopes, 6 (37.5%) of EV71 epitopes and 12 (75%) of CVA16 epitopes had been verified by the previously reported experiments. According to 6 predicted epitopes in VP1, 4 of EV71 (66.7%) and 5 of CVA16 (83.3%) had been verified respectively. The evidences showed that the bioinformatics prediction method was reliable. Since most of previous studies focused on the epitopes of VP1, the current studies suggested that more studies should focus on VP2 and VP3. The bioinformatics method could predict and filter the potential epitopes that would reduce the strength of the experiments. It may help the studies on human enteroviruses including EV71 and CVA16. Furthermore, the prediction of the linear epitopes of the enteroviruses could also support the surveillance and the early warning of the breaks of the hand, foot and mouth disease as well as the R&D and preparation of vaccines.