Midostaurin for COVID-19

AbstractCorona virus 19 (Covid-19) has caused many problems in public health, economic, and even cultural and social fields since the beginning of the epidemic. However, in order to provide therapeutic solutions, many researches have been conducted and various omics data have been published. But there is still no early diagnosis method and comprehensive treatment solution. In this manuscript, by collecting important genes related to COVID-19 and using centrality and controllability analysis in PPI networks and signaling pathways related to the disease; hub and driver genes have been identified in the formation and progression of the disease. Next, by analyzing the expression data, the obtained genes have been evaluated. The results show that in addition to the significant difference in the expression of most of these genes, their expression correlation pattern is also different in the two groups of COVID-19 and control. Finally, based on the drug-gene interaction, drugs affecting the identified genes are presented in the form of a bipartite graph, which can be used as the potential drug combinations.

ABSTRACTAn outbreak of the novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, has infected over 290,000 people since the end of 2019, killed over 12,000, and caused worldwide social and economic disruption1,2. There are currently no antiviral drugs with proven efficacy nor are there vaccines for its prevention. Unfortunately, the scientific community has little knowledge of the molecular details of SARS-CoV-2 infection. To illuminate this, we cloned, tagged and expressed 26 of the 29 viral proteins in human cells and identified the human proteins physically associated with each using affinity-purification mass spectrometry (AP-MS), which identified 332 high confidence SARS-CoV-2-human protein-protein interactions (PPIs). Among these, we identify 66 druggable human proteins or host factors targeted by 69 existing FDA-approved drugs, drugs in clinical trials and/or preclinical compounds, that we are currently evaluating for efficacy in live SARS-CoV-2 infection assays. The identification of host dependency factors mediating virus infection may provide key insights into effective molecular targets for developing broadly acting antiviral therapeutics against SARS-CoV-2 and other deadly coronavirus strains.

We use state-of-the-art computer-aided drug design (CADD) techniques to identify prospective inhibitors of the main protease enzyme, Mpro of the COVID-19 virus. With the high-resolution X-ray crystallography structure of this viral enzyme recently being solved, CADD provides a veritable tool for rapidly screening diverse sets of compounds with the aim of identifying ligands capable of forming energetically favorable complexes with Mpro . From our screening of 1,082,653 compounds derived from the ZINC, the DrugBank, and our in-house African natural product libraries, and a rescreening protocol incorporating enzyme dynamics via ensemble docking, we have been able to identify a range of prospective Mpro inhibitors, which include FDA-approved drugs, drug candidates in clinical trials, as well as natural products. The top-ranking compounds are characterized by the presence of an extended ring system combined with functional groups that allow the ligands to adapt flexibly to the Mpro active site as, for example, present in the biflavonoid amentoflavone, one of the most promising compounds identified here. This particular chemical architecture leads to considerable stronger binding than found for reference compounds with in vitro demonstrated M pro inhibition and anticoronavirus activity. The compounds determined in this work thus represent a good starting point for the design of inhibitors of SARS-CoV-2 replication.