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.
METHODS: As a preliminary step, a molecular docking study was performed to investigate the potency of seventy-one compounds from four classes of inhibitors. The molecular characteristics of the best-performing five compounds were predicted by estimating the drug-likeness and drug score. Molecular dynamics simulations (MD) over 100 ns were performed to inspect the relative stability of the best compound within the Omicron receptor-binding site.
RESULTS: The current findings point out the crucial roles of Q493R, G496S, Q498R, N501Y, and Y505H in the RBD region of SARS-CoV-2 Omicron. Raltegravir, hesperidin, pyronaridine, and difloxacin achieved the highest drug scores compared with the other compounds in the four classes, with values of 81%, 57%, 18%, and 71%, respectively. The calculated results showed that raltegravir and hesperidin had high binding affinities and stabilities to Omicron with ΔGbinding of - 75.7304 ± 0.98324 and - 42.693536 ± 0.979056 kJ/mol, respectively. Further clinical studies should be performed for the two best compounds from this study.
SOURCES OF DATA: Recent published literature.
AREAS OF AGREEMENT: Corticosteroids and immunomodulators that antagonize the interleukin-6 (IL-6) receptor have been shown to play a critical role in modulating inflammation and improving clinical outcomes in hospitalized patients. Inhaled budesonide reduces the time to recovery in older patients with mild-to-moderate COVID-19 managed in the community.
AREAS OF CONTROVERSY: The clinical benefit of remdesivir remains controversial with conflicting evidence from different trials. Remdesivir led to a reduction in time to clinical recovery in the ACTT-1 trial. However, the World Health Organization SOLIDARITY and DISCOVERY trial did not find a significant benefit on 28-day mortality and clinical recovery.
GROWING POINTS: Other treatments currently being investigated include antidiabetic drug empagliflozin, antimalarial drug artesunate, tyrosine kinase inhibitor imatinib, immunomodulatory drug infliximab, antiviral drug favipiravir, antiparasitic drug ivermectin and antidepressant drug fluvoxamine.
AREAS TIMELY FOR DEVELOPING RESEARCH: The timing of therapeutic interventions based on postulated mechanisms of action and the selection of clinically meaningful primary end points remain important considerations in the design and implementation of COVID-19 therapeutic trials.