Miller Craig R, Johnson Erin L, Burke Aran Z, Martin Kyle P, Miura Tanya A, Wichman Holly A, Brown Celeste J, Ytreberg F Marty
Department of Biological Sciences, University of Idaho, Moscow, ID, United States; Department of Mathematics, University of Idaho, Moscow, ID, United States; Center for Modeling Complex Interactions, University of Idaho, Moscow, ID, United States; Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID, United States.
Center for Modeling Complex Interactions, University of Idaho , Moscow, ID , United States.
PeerJ. 2016 Feb 16;4:e1674. doi: 10.7717/peerj.1674. eCollection 2016.
The 2014 Ebola virus (EBOV) outbreak in West Africa is the largest in recorded history and resulted in over 11,000 deaths. It is essential that strategies for treatment and containment be developed to avoid future epidemics of this magnitude. With the development of vaccines and antibody-based therapies using the envelope glycoprotein (GP) of the 1976 Mayinga strain, one important strategy is to anticipate how the evolution of EBOV might compromise these efforts. In this study we have initiated a watch list of potential antibody escape mutations of EBOV by modeling interactions between GP and the antibody KZ52. The watch list was generated using molecular modeling to estimate stability changes due to mutation. Every possible mutation of GP was considered and the list was generated from those that are predicted to disrupt GP-KZ52 binding but not to disrupt the ability of GP to fold and to form trimers. The resulting watch list contains 34 mutations (one of which has already been seen in humans) at six sites in the GP2 subunit. Should mutations from the watch list appear and spread during an epidemic, it warrants attention as these mutations may reflect an evolutionary response from the virus that could reduce the effectiveness of interventions such as vaccination. However, this watch list is incomplete and emphasizes the need for more experimental structures of EBOV interacting with antibodies in order to expand the watch list to other epitopes. We hope that this work provokes experimental research on evolutionary escape in both Ebola and other viral pathogens.
2014年西非埃博拉病毒(EBOV)疫情是有记录以来规模最大的一次,导致超过1.1万人死亡。制定治疗和控制策略以避免未来出现如此大规模的疫情至关重要。随着使用1976年马英加毒株包膜糖蛋白(GP)的疫苗和基于抗体的疗法的发展,一项重要策略是预测EBOV的进化可能如何影响这些努力。在本研究中,我们通过对GP与抗体KZ52之间的相互作用进行建模,启动了一份EBOV潜在抗体逃逸突变的观察清单。该观察清单是使用分子建模生成的,以估计突变引起的稳定性变化。考虑了GP的每一种可能突变,并从那些预计会破坏GP-KZ52结合但不会破坏GP折叠和形成三聚体能力的突变中生成该清单。生成的观察清单包含GP2亚基六个位点的34个突变(其中一个已在人类中出现)。如果观察清单上的突变在疫情期间出现并传播,值得关注,因为这些突变可能反映了病毒的进化反应,可能会降低疫苗接种等干预措施的有效性。然而,这份观察清单并不完整,强调需要更多EBOV与抗体相互作用的实验结构,以便将观察清单扩展到其他表位。我们希望这项工作能激发对埃博拉病毒和其他病毒病原体进化逃逸的实验研究。