Zika virus (ZIKV) is a member of the Flavivirus genus of positive-sense single-stranded RNA viruses, which includes Dengue, West Nile, Yellow Fever, and other mosquito-borne arboviruses. Infection by ZIKV can be difficult to distinguish from infection by other mosquito-borne Flaviviruses due to high sequence similarity, serum antibody cross-reactivity, and virus co-circulation in endemic areas. Indeed, existing serological methods are not able to consistently differentiate ZIKV from other Flaviviruses, which makes it extremely difficult to accurately calculate the incidence rate of Zika-associated Guillain-Barre in adults, microcephaly in newborns, or asymptomatic infections within a geographical area. In order to identify Zika-specific peptide regions that could be used as serology reagents, we have applied comparative genomics and protein structure analyses to identify amino acid residues that distinguish each of 10 Flavivirus species and subtypes from each other by calculating the specificity, sensitivity, and surface exposure of each residue in relevant target proteins. For ZIKV we identified 104 and 116 15-mer peptides in the E glycoprotein and NS1 non-structural protein, respectively, that contain multiple diagnostic sites and are located in surface-exposed regions in the tertiary protein structure. These sensitive, specific, and surface-exposed peptide regions should serve as useful reagents for seroprevalence studies to better distinguish between prior infections with any of these mosquito-borne Flaviviruses. The development of better detection methods and diagnostic tools will enable clinicians and public health workers to more accurately estimate the true incidence rate of asymptomatic infections, neurological syndromes, and birth defects associated with ZIKV infection.

The Protein Data Bank (PDB) now contains more than 120,000 three-dimensional (3D) structures of biological macromolecules. To allow an interpretation of how PDB data relates to other publicly available annotations, we developed a novel data integration platform that maps 3D structural information across various datasets. This integration bridges from the human genome across protein sequence to 3D structure space. We developed novel software solutions for data management and visualization, while incorporating new libraries for web-based visualization using SVG graphics.

Availability and implementation

The new views are available from http://www.rcsb.org and software is available from https://github.com/rcsb/.

Contact

andreas.prlic@rcsb.orgSupplementary information: Supplementary data are available at Bioinformatics online.

The Protein Data Bank (PDB; http://wwpdb.org) was established in 1971 as the first open access digital data resource in biology with seven protein structures as its initial holdings. The global PDB archive now contains more than 126,000 experimentally determined atomic level three-dimensional (3D) structures of biological macromolecules (proteins, DNA, RNA), all of which are freely accessible via the Internet. Knowledge of the 3D structure of the gene product can help in understanding its function and role in disease. Of particular interest in the PDB archive are proteins for which 3D structures of genetic variant proteins have been determined, thus revealing atomic-level structural differences caused by the variation at the DNA level. Herein, we present a systematic and qualitative analysis of such cases. We observe a wide range of structural and functional changes caused by single amino acid differences, including changes in enzyme activity, aggregation propensity, structural stability, binding, and dissociation, some in the context of large assemblies. Structural comparison of wild type and mutated proteins, when both are available, provide insights into atomic-level structural differences caused by the genetic variation.