RESULTS: We developed DeSigN, a web-based tool for predicting drug efficacy against cancer cell lines using gene expression patterns. The algorithm correlates phenotype-specific gene signatures derived from differentially expressed genes with pre-defined gene expression profiles associated with drug response data (IC50) from 140 drugs. DeSigN successfully predicted the right drug sensitivity outcome in four published GEO studies. Additionally, it predicted bosutinib, a Src/Abl kinase inhibitor, as a sensitive inhibitor for oral squamous cell carcinoma (OSCC) cell lines. In vitro validation of bosutinib in OSCC cell lines demonstrated that indeed, these cell lines were sensitive to bosutinib with IC50 of 0.8-1.2 μM. As further confirmation, we demonstrated experimentally that bosutinib has anti-proliferative activity in OSCC cell lines, demonstrating that DeSigN was able to robustly predict drug that could be beneficial for tumour control.
CONCLUSIONS: DeSigN is a robust method that is useful for the identification of candidate drugs using an input gene signature obtained from gene expression analysis. This user-friendly platform could be used to identify drugs with unanticipated efficacy against cancer cell lines of interest, and therefore could be used for the repurposing of drugs, thus improving the efficiency of drug development.
OBJECTIVES: Pioneering research on molecular mechanisms underlying the viral transmission, molecular pathogenicity, and potential treatments will be highlighted in this review. The development of antiviral drugs specific to SARS-CoV-2 is a complicated and tedious process. To accelerate scientific discoveries and advancement, researchers are consolidating available data from associated coronaviruses into a single pipeline, which can be readily made available to vaccine developers.
METHODS: In order to find studies evaluating the COVID-19 virus epidemiology, repurposed drugs and potential vaccines, web searches and bibliographical bases have been used with keywords that matches the content of this review.
RESULTS: The published results of SARS-CoV-2 structures and interactomics have been used to identify potential therapeutic candidates. We illustrate recent publications on SARS-CoV-2, concerning its molecular, epidemiological, and clinical characteristics, and focus on innovative diagnostics technologies in the production pipeline. This objective of this review is to enhance the comprehension of the unique characteristics of SARS-CoV-2 and strengthen future control measures.
Lay Summary: An innovative analysis is evaluating the nature of the COVID-19 pandemic. The aim is to increase knowledge of possible viral detection methods, which highlights several new technology limitations and advantages. We have assessed some drugs currently for patients (Lopinavir, Ritonavir, Anakinra and Interferon beta 1a), as the feasibility of COVID-19 specific antivirals is not presently known. The study explores the race toward vaccine development and highlights some significant trials and candidates in various clinical phases. This research addresses critical knowledge gaps by identifying repurposed drugs currently under clinical trials. Findings will be fed back rapidly to the researchers interested in COVID 19 and support the evidence and potential of possible therapeutics and small molecules with their mode of action.