Combined Ligand and Structure Guided Protocol for the Virtual Screening of Activators of NRF2-Associated Cellular Process in Cardiovascular Diseases.

Abstract

NRF2 (NF-E2 p45-related factor 2) is a transcriptional factor that controls the production of antioxidant and cytoprotective enzymes that are produced in response to oxidative stress. NRF2 and its primary inhibitor, the E3 ligase adaptor Kelch-like ECH-associated protein 1 (KEAP-1), are essential for redox and metabolic processes to occur. The binding of NRF2 to KEAP-1 in the cytoplasm keeps NRF2 at a low level. Stressors, such as free radicals, however, promote NRF2 translocation to the cell nucleus. Nuclear NRF2 accumulates in the nucleus, allowing it to bind to the antioxidant response element (ARE) of genes that code for antioxidant proteins. Several studies have shown that excessive synthesis of free fatty acids produces significant reactive oxygen species (ROS) production, which reduces NO bioavailability and results in decreased expression of NRF2, resulting in a poor anti-oxidative response. Furthermore, it results in endothelial dysfunction, atherosclerosis, myocardial ischemia-reperfusion injury, hypertension, diabetic vascular disease, and other NO-mediated cardiovascular diseases emerge. As a result, inhibiting KEAP-1 or activating NRF2 is a viable strategy for avoiding endothelial dysfunction caused by the NRF2 pathway. Therefore, in present project, various molecular models were built to probe the 3D structural features of NRF2- KEAP-1 modulator that shields NRF2 from degradation and allows it to move into the nucleus where it controls antioxidant genes. Briefly, the GRIND model for the KEAP1 was developed against the dataset of 91 inhibitors to extract the features that had a positive and negative impact on the activity of the inhibitors. One feature NI- N1 at a distance of 2.80 – 3.20 Å positively impacted the activity and other O-O feature at a distance of 2 – 2.40 Å showing the negative impact on the activity. This model is important since it can help in the development of new drugs/compounds based on these features.