Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
Sci Rep. 2017 Apr 11;7:45886. doi: 10.1038/srep45886.
Recently, progress has been made in the development of vaccines and monoclonal antibody cocktails that target the Ebola coat glycoprotein (GP). Based on the mutation rates for Ebola virus given its natural sequence evolution, these treatment strategies are likely to impose additional selection pressure to drive acquisition of mutations in GP that escape neutralization. Given the high degree of sequence conservation among GP of Ebola viruses, it would be challenging to determine the propensity of acquiring mutations in response to vaccine or treatment with one or a cocktail of monoclonal antibodies. In this study, we analyzed the mutability of each residue using an approach that captures the structural constraints on mutability based on the extent of its inter-residue interaction network within the three-dimensional structure of the trimeric GP. This analysis showed two distinct clusters of highly networked residues along the GP-GP interface, part of which overlapped with epitope surfaces of known neutralizing antibodies. This network approach also permitted us to identify additional residues in the network of the known hotspot residues of different anti-Ebola antibodies that would impact antibody-epitope interactions.
最近，在开发针对埃博拉病毒外壳糖蛋白 (GP) 的疫苗和单克隆抗体鸡尾酒方面取得了进展。基于埃博拉病毒的自然序列进化的突变率，这些治疗策略可能会施加额外的选择压力，以促使 GP 中逃避中和的突变的获得。鉴于埃博拉病毒 GP 之间的高度序列保守性，确定对疫苗或单一或鸡尾酒单克隆抗体治疗产生突变的倾向将具有挑战性。在这项研究中，我们使用一种方法分析了每个残基的可变性，该方法基于其在三聚体 GP 三维结构中的互残基相互作用网络的程度，捕获了对可变性的结构限制。该分析显示，在 GP-GP 界面上有两个截然不同的高度网络化残基簇，其中一部分与已知中和抗体的表位表面重叠。这种网络方法还使我们能够识别不同抗埃博拉抗体的已知热点残基网络中的其他残基，这些残基会影响抗体-表位相互作用。
