Influenza A Virus Escape Mutations and their Effects on Binding Affinity

神经氨酸酶 变构调节 甲型流感病毒 人口 突变 病毒 生物 病毒学 血凝素(流感) 突变 结合位点 基因 受体 遗传学 医学 环境卫生
作者
Lucas S. Burke,Karshana Kalyanaraman,Stephanie Flores,T. M. Khong,Danielle Selover,Laura Rusch‐Salazar
出处
期刊:The FASEB Journal [Wiley]
卷期号:34 (S1): 1-1
标识
DOI:10.1096/fasebj.2020.34.s1.06914
摘要

The Influenza A virus (IAV) causes a common and potentially fatal infection. The Center for Disease Control reports that 3–11% of the U.S. population is affected annually by IAV. The 2017–2018 burden of influenza led to over 950,000 patient hospitalizations and almost 80,000 deaths. The surface of IAV contains two proteins essential for infection: hemagglutinin (HA) and neuraminidase (NA). HA binds to a receptor on an epithelial host cell surface, and helps IAV penetrate the cell and release the viral RNA genome. As newly formed IAV particles leave the infected cell, NA assists in viral release and driving the infection of neighboring cells. Due to frequent, natural mutations in the IAV genome, annual IAV vaccines are engineered but are not always effective. The Schiffer Lab propagated IAV in vitro in the presence of an antibody to identify mutations of IAV that can escape immune detection. A critical asparagine located in the binding pocket of HA (N203 HA ) facilitates a hydrogen bond to sialic acid on LSTc (a human receptor analog). The N203V HA escape mutation disrupts the virus‐ligand interaction; however, an allosteric mutation on NA (E329K NA ) can compensate for the HA mutation. Our 3‐D printed model of the HA active site visually depicts the binding of the N203 residue with the LSTc. This model further illustrates that viruses can use allosteric mutations to circumvent the immune system. Physically modeling the active site of HA allows students to investigate how substrates fit into active sites and visualize mutations within proteins. Support or Funding Information The CREST Program is funded through DUE‐IUSE #1725940 awarded to Milwaukee School of Engineering Center for BioMolecular Modeling.

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