The COVID-19 pandemic has reached over 100 million worldwide. Due to the multi-targeted nature of the virus, it is clear that drugs providing anti-COVID-19 effects need to be developed at an accelerated rate, and a combinatorial approach may stand to be more successful than a single drug therapy. Among several targets and pathways that are under investigation, the renin-angiotensin system (RAS) and specifically angiotensin-converting enzyme (ACE), and Ca 2+ -mediated SARS-CoV-2 cellular entry and replication are noteworthy. A combination of ACE inhibitors and calcium channel blockers (CCBs), a critical line of therapy for pulmonary hypertension, has shown therapeutic relevance in COVID-19 when investigated independently. To that end, we conducted in silico modeling using BIOiSIM, an AI-integrated mechanistic modeling platform by utilizing known preclinical in vitro and in vivo datasets to accurately simulate systemic therapy disposition and site-of-action penetration of the CCBs and ACEi compounds to tissues implicated in COVID-19 pathogenesis.
【저자키워드】 COVID-19, Drug repurposing, artificial intelligence, ACE inhibitors, calcium channel blockers, 【초록키워드】 SARS-CoV-2, therapy, COVID-19 pandemic, drug, in vitro, in silico, virus, hypertension, ACE inhibitors, calcium channel blockers, RAS, drug therapy, Replication, renin-angiotensin system, COVID-19 pathogenesis, therapeutic, pathway, target, ACE inhibitor, dataset, cellular entry, in vivo, systemic therapy, Critical, platform, calcium, ACEi, Angiotensin-converting enzyme, pulmonary hypertension, Combination, CCB, angiotensin, ACE, Pathways, Renin, calcium channel, tissue, tissues, enzyme, Compound, penetration, CCBs, blocker, Effect, approach, shown, investigated, conducted, reached, implicated, accelerated, 【제목키워드】 repurposing, drug, pulmonary, development,