Last two decades have witnessed several global infectious outbreaks. Among these, coronavirus is identified as a prime culprit ranging from its involvement in severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS) to COVID-19. These infections involved in huge healthcare and economic cost incurred globally. Every time, coronavirus improved its infection ability and surprised the medical practitioners and researchers. Currently, COVID-19 is also causing numerous infections and stalled global activities. Global efforts are underway to identify potential viral targets for management of these outbreaks, but significant progress in prevention of these outbreaks is not yet achieved. We explored host-pathogen protein-protein interactions of MERS, SARS and COVID-19, and identified host targets common among all recent coronavirus outbreaks. Further, we tried to understand their potential for management of coronavirus. The common proteins involved in coronavirus host-pathogen interactions indicate their indispensable role in the pathogenesis and therefore targeting these proteins can give strategies to prevent current and future coronavirus outbreaks. Viral variability necessitates development of new therapeutic modalities for every outbreak, in contrast targeting necessary human proteins required by all coronaviruses can provide us a clue to prevent current and future coronavirus outbreaks. We found that targeting FURIN and TMPRSS2 can provide good results due to their common involvement in current and previous outbreaks. We also listed some known molecules against these two targets for their potential drug repurposing evaluation. Although, several recent studies undergoing with targeting these proteins for management of coronavirus, but safety evaluation and risk assessment must be given prime importance while targeting human proteins.

MOTIVATION: The outbreak of COVID-2019 initiated at Wuhan, China has become a global threat by rapid transmission and severe fatalities. Recent studies have uncovered whole genome sequence of SARS-CoV-2 (causing COVID-2019). In addition, lung metagenomic studies on infected patients revealed overrepresented Prevotella spp. producing certain proteins in abundance. We performed host-pathogen protein-protein interaction analysis between SARS-CoV-2 and overrepresented Prevotella proteins with human proteome. We also performed functional overrepresentation analysis of interacting proteins to understand their role in COVID-2019 severity. RESULTS: It was found that overexpressed Prevotella proteins can promote viral infection. As per the results, Prevotella proteins, but not viral proteins, are involved in multiple interactions with NF-kB, which is involved in increasing clinical severity of COVID-2019. Prevotella may have role in COVID-2019 outbreak and should be given importance for understanding disease mechanisms and improving treatment outcomes. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Microbial pathogenesis involves several aspects of host-pathogen interactions, including microbial proteins targeting host subcellular compartments and subsequent effects on host physiology. Such studies are supported by experimental data, but recent detection of bacterial proteins localization through computational eukaryotic subcellular protein targeting prediction tools has also come into practice. We evaluated inter-kingdom prediction certainty of these tools. The bacterial proteins experimentally known to target host subcellular compartments were predicted with eukaryotic subcellular targeting prediction tools, and prediction certainty was assessed. The results indicate that these tools alone are not sufficient for inter-kingdom protein targeting prediction. The correct prediction of pathogen's protein subcellular targeting depends on several factors, including presence of localization signal, transmembrane domain and molecular weight, etc., in addition to approach for subcellular targeting prediction. The detection of protein targeting in endomembrane system is comparatively difficult, as the proteins in this location are channelized to different compartments. In addition, the high specificity of training data set also creates low inter-kingdom prediction accuracy. Current data can help to suggest strategy for correct prediction of bacterial protein's subcellular localization in host cell.