| Capturing the evolution trend of virus and understanding the interaction between virus and its host plants are of great concern in crop science. In this thesis, the author tries to explain the fundamental biological processes in micro-scale by investigating corresponding protein dynamics structures using bioinformatics tools and molecular mechanics. The mechanism of how Argonaute protein recognize small RNAs and cleave target mRNA in RNA interference, as well as the binding affinity between virus protein p19and its host RNA are explored. The genetic evolution of influenza virus is mapped using the mutual information based site transition network. The entire work is divided by the following three sections.In the first section, the p19-siRNA recognition mechanism and mutation effects were studied by molecular dynamics simulations of the wild-type and mutant p19protein (W39G&W42G) binding with a21-nt siRNA duplex. Simulations with standard molecular dynamics (MD) and steered molecular dynamics have shown that the double mutant structure is indeed much less stable than the wild-type, consistent with the recent experimental findings. The free energy perturbation successfully predicted a binding affinity loss of6.98±0.95kcal/mol for the single mutation W39G, and12.8±1.0kcal/mol loss for the double mutation W39/42G. with the van der Waals interactions dominating the contribution (-90%). These results indicate that the W39/42G mutations essentially destroy the important p19-siRNA recognition by breaking the strong stacking interaction between Cyt1and Gua’19with end-capping tryptophans. These large scale simulations might provide new insights into the interactions and co-evolution relationship between RNA virus proteins and their hosts.The second section examined the recognition mechanism and cleavage activity of target mRNA by Argonaute silencing complexes. Both the recently reported11-nt and15-nt guide-target strands-Ago complexes are modeled. Our simulations show comparable results for both the11-and15-nt nucleic-acid strands, whose A-form-like helix duplex gradually distorts as the number of mismatches at the seed region increases and the complex can survive no more than two mismatches. In the extreme four-mismatch mutant complex, the hydrogen bonds between the nucleic-acid duplex and L1/L2segments of Ago protein are broken, which introduce a bending motion of the PAZ domain along the L1/L2"hinge-like" connection region and result in the opening of the nucleic-acid-binding channel. These long-range interactions between the seed region and PAZ domain, mediated by the L1/L2segments, reveals the central role of the seed region in the guide-target recognition-it not only determines the guide-target duplex’s nucleation, and propagation, but also controls the dynamics of the large conformational changes in the PAZ domain. The catalytic activities of RNA guided mRNA cleavage are also investigated in our simulation by replacing the guide DNA by corresponding RNA strand in the Ago-DNA-mRNA complexes. Similar behaviors are found for the Ago-RNA-mRNA complexes, which support the hypothesis that small RNAs might also be used as the guide strand for Thermus thermophilus Ago-like proteins and may also have larger tolerance for the mismatches in the seed region.In the final section, the antigenic and genetic evolution pathways of influenza virus is predicted by mutual information model. The mutual information method was used to design a site transition network (STN) for each amino acid site in the hemagglutinin (HA) sequence. The STN network indicates that most of the dynamic interactions are positioned around the epitopes and the RBD regions, with strong preferences in both the mutation sites and amino acid types being mutated to. The network also shows that antigenic changes accumulate over time, with occasional large changes due to multiple co-occurring mutations at antigenic sites. The cluster analysis by subdividing the STN into several subnetworks reveals a more detailed view about the features of the antigenic change:The characteristic inner sites and the connecting inter-subnetwork sites are both responsible for the drifts. A novel5-step prediction algorithm based on the STN shows a reasonable accuracy in reproducing historical HA mutations. For example, our method can reproduce the2003-2004A/H3N2mutations with～70%accuracy. The method also predicts seven possible mutations for the next antigenic drift in the coming season. The site transition network approach also agrees well with the phylogenetic tree and antigenic maps based on HA inhibition assays. |
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