Transcriptomics, Cheminformatics, and Systems Pharmacology Strategies Unveil the Potential Bioactives to Combat COVID-19

Abstract

Coronavirus disease (COVID-19) is a viral disease caused by the SARS-CoV-2 virus and is becoming a global threat again because of the higher transmission rate and lack of proper therapeutics as well as the rapid mutations in the genetic pattern of SARS-CoV-2. Despite vaccinations, the prevalence and recurrence of this infection are still on the rise, which urges the identification of potential global therapeutics for a complete cure. Plant-based alternative medicine is becoming popular worldwide because of its higher efficiency and minimal side effects. Yet, identifying the potential medicinal plants and formulating a plant-based medicine is still a bottleneck. Hence, in this study, the systems pharmacology, transcriptomics, and cheminformatics approaches were employed to uncover the multi-targeted mechanisms and to screen the potential phytocompounds from significant medicinal plants to treat COVID-19. These approaches have identified 30 unique COVID-19 human immune genes targeted by the 25 phytocompounds present in four selected ethnobotanical plants. Differential and co-expression profiling and pathway enrichment analyses delineate the molecular signaling and immune functional regulations of the COVID-19 unique genes. In addition, the credibility of these compounds was analyzed by the pharmacological features. The current holistic finding is the first to explore whether the identified potential bioactives could reform into a drug candidate to treat COVID-19. Furthermore, the molecular docking analysis was employed to identify the important bioactive compounds; thus, an ultimately significant medicinal plant was also determined. However, further laboratory evaluation and clinical validation are required to determine the efficiency of a therapeutic formulation against COVID-19.

Tumor-targeted delivery of lnc antisense RNA against RCAS1 by live-attenuated tryptophan-auxotrophic Salmonella inhibited 4T1 breast tumors and metastasis in mice

“…Moreover, based on the previous literature, 26 , 27 we selected important cancer-related genes, cell-cycle regulatory genes, and cytokine genes and analyzed their interconnections using in silico network analyses: STRING, GeneMANIA, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. 28 , 29 The network analyses indicated that most of the selected genes are highly interlinked and involved in regulating apoptosis, lymphocyte differentiation, cytokine-mediated signaling pathways, and stress responses. Moreover, the analyses also identified genes connected with RCAS1 ( Figures 5 A–5C).…”

Computational analysis of the phytocompounds of Mimusops elengi against spike protein of SARS CoV2 – An Insilico model

“…From the supplementary tables 2 and 3, it was clear that genes IL6, MMP9, ICAM1, and DPP4 were found to be common to both the phytocompound targeted receptors and COVID-19-associated signatures. So, these receptors were chosen for docking analysis to analyze the binding affinity between the targets and their respective phytocompounds [ 35 ]. Molecular docking studies were crucial in identifying the interactions of target compounds with their receptors at the atomic level.…”

Potential Anti-SARS-CoV-2 Molecular Strategies

“…Since nature is an inexhaustible source of remedies and therapeutic scaffolds, new potential drugs to be used in the fight against COVID-19 were often searched for from natural sources, especially plants [12][13][14], using highly diverse approaches such as transcriptomics, cheminformatics, and systems pharmacology with a holistic view [15]. Natural inhibitors of SARS-CoV-2 nonstructural protein (nsp10) were screened from a database containing 310 naturally isolated metabolites through various in silico selection methods including molecular similarity assessment, molecular fingerprint, docking studies, toxicity, ADMET (absorption, distribution, metabolism, excretion, and toxicity), and density-functional theory [16].…”