ABSTRACT
The inflammatory protease caspase-1 is associated with the release of cytokines. An excessive number of cytokines (a "cytokine storm") is a dangerous consequence of COVID-19 infection and has been indicated as being among the causes of death by COVID-19. The anti-inflammatory drug colchicine (which is reported in the literature to be a caspase-1 inhibitor) and the corticosteroid drugs, dexamethasone and methylprednisolone, are among the most effective active compounds for COVID-19 treatment. The SERM raloxifene has also been used as a repurposed drug in COVID-19 therapy. In this study, inhibition of caspase-1 by these four compounds was analyzed using computational methods. Our aim was to see if the inhibition of caspase-1, an important biomolecule in the inflammatory response that triggers cytokine release, could shed light on how these drugs help to alleviate excessive cytokine production. We also measured the antioxidant activities of dexamethasone and colchicine when scavenging the superoxide radical using cyclic voltammetry methods. The experimental findings are associated with caspase-1 active site affinity towards these compounds. In evaluating our computational and experimental results, we here formulate a mechanism for caspase-1 inhibition by these drugs, which involves the active site amino acid Cys285 residue and is mediated by a transfer of protons, involving His237 and Ser339. It is proposed that the molecular moiety targeted by all of these drugs is a carbonyl group which establishes a S(Cys285)-C(carbonyl) covalent bond.
Subject(s)
Anti-Inflammatory Agents/pharmacology , COVID-19 Drug Treatment , Caspase 1/drug effects , Caspase Inhibitors/pharmacology , Coronavirus 3C Proteases/drug effects , Anti-Inflammatory Agents/chemistry , COVID-19/metabolism , Caspase 1/chemistry , Caspase 1/metabolism , Caspase Inhibitors/chemistry , Colchicine/chemistry , Colchicine/pharmacology , Coronavirus 3C Proteases/antagonists & inhibitors , Coronavirus 3C Proteases/chemistry , Coronavirus 3C Proteases/metabolism , Dexamethasone/pharmacology , Humans , Models, Molecular , Molecular Docking Simulation , Pentacyclic Triterpenes/pharmacology , Protein Interaction Domains and Motifs , Raloxifene Hydrochloride/chemistry , Raloxifene Hydrochloride/pharmacology , Viral Protease Inhibitors/chemistry , Viral Protease Inhibitors/pharmacologyABSTRACT
Inflammation involves a complex biological response of the body tissues to damaging stimuli. When dysregulated, inflammation led by biomolecular mediators such as caspase-1 and tumor necrosis factor-alpha (TNF-alpha) can play a detrimental role in the progression of different medical conditions such as cancer, neurological disorders, autoimmune diseases, and cytokine storms caused by viral infections such as COVID-19. Computational approaches can accelerate the search for dual-target drugs able to simultaneously inhibit the aforementioned proteins, enabling the discovery of wide-spectrum anti-inflammatory agents. This work reports the first multicondition model based on quantitative structure-activity relationships and a multilayer perceptron neural network (mtc-QSAR-MLP) for the virtual screening of agency-regulated chemicals as versatile anti-inflammatory therapeutics. The mtc-QSAR-MLP model displayed accuracy higher than 88%, and was interpreted from a physicochemical and structural point of view. When using the mtc-QSAR-MLP model as a virtual screening tool, we could identify several agency-regulated chemicals as dual inhibitors of caspase-1 and TNF-alpha, and the experimental information later retrieved from the scientific literature converged with our computational results. This study supports the capabilities of our mtc-QSAR-MLP model in anti-inflammatory therapy with direct applications to current health issues such as the COVID-19 pandemic.