Berberine modulates cardiovascular diseases as a multitarget-mediated alkaloid with insights into its downstream signals using in silico prospective screening approaches

Abstract

Atherosclerosis is potentially correlated with several cardiac disorders that are greatly associated with cellular oxidative stress generation, inflammation, endothelial cells dysfunction, and many cardiovascular complications. Berberine is a natural isoquinoline alkaloid compound that widely modulates pathogenesis of atherosclerosis through its different curative potentials. This in silico screening study was designed to confirm the potent restorative properties of berberine chloride as a multitarget-mediated alkaloid against the CVDs and their complications through screening, identifying, visualizing, and evaluating its binding models, affinities, and interactions toward several CVDs-related targets as direct and/or indirect-mediated signals via inhibiting cellular ER stress and apoptotic signals and activating autophagy pathway. The drug-likeness properties of berberine were predicted using the computational QSAR/ADMET and Lipinski’s RO5 analyses as well as in silico molecular docking simulations. The potent berberine-binding modes, residues-interaction patterns, and free energies of binding scores towards several CVDs-related targets were estimated using molecular docking tools. Furthermore, the pharmacokinetic properties and toxicological features of berberine were clearly determined. According to this in silico virtual screening study, berberine chloride could restore cardiac function and improve pathogenic features of atherosclerotic CVDs through alleviating ER stress and apoptotic signals, activating autophagy, improving insulin sensitivity, decreasing hyperglycemia and dyslipidemia, increasing intracellular RCT signaling, attenuating oxidative stress and vascular inflammation, and upregulating cellular antioxidant defenses in many cardiovascular tissues. In this in silico study, berberine chloride greatly modulated several potent CVDs-related targets, including SIGMAR1, GRP78, CASP3, BECN1, PIK3C3, SQSTM1/p62, LC3B, GLUT3, INSR, LDLR, LXRα, PPARγ, IL1β, IFNγ, iNOS, COX-2, MCP-1, IL10, GPx1, and SOD3.