Goh's BioComputing, Singapore 548957, Republic of Singapore.
Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana 46202, United States.
J Proteome Res. 2020 Nov 6;19(11):4355-4363. doi: 10.1021/acs.jproteome.0c00672. Epub 2020 Oct 2.
A model that predicts levels of coronavirus (CoV) respiratory and fecal-oral transmission potentials based on the shell disorder has been built using neural network (artificial intelligence, AI) analysis of the percentage of disorder (PID) in the nucleocapsid, N, and membrane, M, proteins of the inner and outer viral shells, respectively. Using primarily the PID of N, SARS-CoV-2 is grouped as having intermediate levels of both respiratory and fecal-oral transmission potentials. Related studies, using similar methodologies, have found strong positive correlations between virulence and inner shell disorder among numerous viruses, including Nipah, Ebola, and Dengue viruses. There is some evidence that this is also true for SARS-CoV-2 and SARS-CoV, which have N PIDs of 48% and 50%, and case-fatality rates of 0.5-5% and 10.9%, respectively. The underlying relationship between virulence and respiratory potentials has to do with the viral loads of vital organs and body fluids, respectively. Viruses can spread by respiratory means only if the viral loads in saliva and mucus exceed certain minima. Similarly, a patient is likelier to die when the viral load overwhelms vital organs. Greater disorder in inner shell proteins has been known to play important roles in the rapid replication of viruses by enhancing the efficiency pertaining to protein-protein/DNA/RNA/lipid bindings. This paper suggests a novel strategy in attenuating viruses involving comparison of disorder patterns of inner shells (N) of related viruses to identify residues and regions that could be ideal for mutation. The M protein of SARS-CoV-2 has one of the lowest M PID values (6%) in its family, and therefore, this virus has one of the hardest outer shells, which makes it resistant to antimicrobial enzymes in body fluid. While this is likely responsible for its greater contagiousness, the risks of creating an attenuated virus with a more disordered M are discussed.
已使用神经网络（人工智能，AI）分析核衣壳（N）和膜（M）蛋白的无序百分比（PID），分别为内、外病毒壳的 N 和 M 蛋白，建立了一种预测冠状病毒（CoV）呼吸道和粪口传播潜力水平的模型。使用主要是 N 的 PID，SARS-CoV-2 被归类为具有中等水平的呼吸道和粪口传播潜力。相关研究使用类似的方法，在包括尼帕、埃博拉和登革热病毒在内的众多病毒中发现了内在壳无序性与毒力之间存在很强的正相关关系。有一些证据表明，SARS-CoV-2 和 SARS-CoV 也是如此，它们的 N PID 分别为 48%和 50%，病死率分别为 0.5-5%和 10.9%。毒力与呼吸道潜力之间的潜在关系与重要器官和体液中的病毒载量有关。只有当唾液和黏液中的病毒载量超过某些最小值时，病毒才能通过呼吸道传播。同样，当病毒载量超过重要器官时，患者更有可能死亡。已知内在壳蛋白的更大无序性在增强与蛋白质/DNA/RNA/脂质结合相关的效率方面发挥了重要作用，从而促进了病毒的快速复制。本文提出了一种通过比较相关病毒的内在壳（N）的无序模式来识别可理想突变的残基和区域的新策略，以减弱病毒。SARS-CoV-2 的 M 蛋白在其家族中具有最低的 M PID 值（6%）之一，因此，这种病毒具有最硬的外壳之一，使其对体液中的抗菌酶具有抵抗力。虽然这可能是其传染性更强的原因，但讨论了创建具有更无序 M 的减毒病毒的风险。
