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Crystallographic molecular replacement using an in silico-generated search model of SARS-CoV-2 ORF8.

ABSTRACT: The majority of crystal structures are determined by the method of molecular replacement (MR). The range of application of MR is limited mainly by the need for an accurate search model. In most cases, pre-existing experimentally determined structures are used as search models. In favorable cases, ab initio predicted structures have yielded search models adequate for MR. The ORF8 protein of SARS-CoV-2 represents a challenging case for MR using an ab initio prediction because ORF8 has an all β-sheet fold and few orthologs. We previously determined experimentally the structure of ORF8 using the single anomalous dispersion (SAD) phasing method, having been unable to find an MR solution to the crystallographic phase problem. Following a report of an accurate prediction of the ORF8 structure, we assessed whether the predicted model would have succeeded as an MR search model. A phase problem solution was found, and the resulting structure was refined, yielding structural parameters equivalent to the original experimental solution.

SUBMITTER: Flower TG

PROVIDER: S-EPMC7980513 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

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Crystallographic molecular replacement using an in silico-generated search model of SARS-CoV-2 ORF8.

Flower Thomas G TG Hurley James H JH

Protein science : a publication of the Protein Society 20210304 4

The majority of crystal structures are determined by the method of molecular replacement (MR). The range of application of MR is limited mainly by the need for an accurate search model. In most cases, pre-existing experimentally determined structures are used as search models. In favorable cases, ab initio predicted structures have yielded search models adequate for MR. The ORF8 protein of SARS-CoV-2 represents a challenging case for MR using an ab initio prediction because ORF8 has an all β-she ...[more]

PMID: 33625752

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Project description:SARS-CoV-2 is the causative agent of a new type of coronavirus infection, COVID-19, which has rapidly spread worldwide. The overall genome sequence homology between SARS-CoV-2 and SARS-CoV is 79%. However, the homology of the ORF8 protein between these two coronaviruses is low, at ~26%. Previously, it has been suggested that infection by the ORF8-deleted variant of SARS-CoV-2 results in less severe symptoms than in the case of wild-type SARS-CoV-2. Although we found that ORF8 is involved in the proteasome autoimmunity system, the precise role of ORF8 in infection and pathology has not been fully clarified. In this study, we determined a new network of ORF8-interacting proteins by performing in silico analysis of the binding proteins against the previously described 47 ORF8-binding proteins. We used as a dataset 431 human protein candidates from Uniprot that physically interacted with 47 ORF8-binding proteins, as identified using STRING. Homology and phylogenetic profile analyses of the protein dataset were performed on 446 eukaryotic species whose genome sequences were available in KEGG OC. Based on the phylogenetic profile results, clustering analysis was performed using Ward's method. Our phylogenetic profiling showed that the interactors of the ORF8-interacting proteins were clustered into three classes that were conserved across chordates (Class 1: 152 proteins), metazoans (Class 2: 163 proteins), and eukaryotes (Class 3: 114 proteins). Following the KEGG pathway analysis, classification of cellular localization, tissue-specific expression analysis, and a literature study on each class of the phylogenetic profiling cluster tree, we predicted that the following: protein members in Class 1 could contribute to COVID-19 pathogenesis via complement and coagulation cascades and could promote sarcoidosis; the members of Class 1 and 2, together, may contribute to the downregulation of Interferon-β; and Class 3 proteins are associated with endoplasmic reticulum stress and the degradation of human leukocyte antigen.

Dataset Information

Crystallographic molecular replacement using an in silico-generated search model of SARS-CoV-2 ORF8.

Publications

Crystallographic molecular replacement using an in silico-generated search model of SARS-CoV-2 ORF8.

Similar Datasets

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