Screening of novel and selective inhibitors for neuronal nitric oxide synthase (nNOS) via structure-based drug design techniques

Abstract

The overproduction of nitric oxide (NO) by neuronal nitric oxide synthase (nNOS) is the main cause of several neurodegenerative diseases such as Alzheimer’s Disease (AD), Parkinson’s Disease (PD), and Multiple Sclerosis (MS). NO is produced in many cell types by three isoforms of NOS (nNOS, iNOS, and eNOS) and has various biological functions, generally, for its significant reactivity with proteins. NOS isoforms share a high sequence and structure similarity, specifically in the active site, which makes the development and design of nNOS inhibitors extremely challenging; mainly, no-selective inhibitors can affect iNOS and eNOS physiological roles. To date, there is no selective inhibitor against nNOS in the market with desirable ADMET (absorption, distribution, metabolism, elimination, and toxicity) properties, and pass the blood-brain barrier (BBB). With improvement of computational drug design techniques and accessibility of the X-ray crystal structures, development of novel drugs became less expensive and faster. Our research benefited from the structure-based drug design approaches to investigate proficient and selective inhibitors against nNOS. After structure-based virtual screening, the selective top-ranked compounds were filtered according to the ADMET prediction; then, the candidates with a high affinity with a suitable ADMET profile were subject to 100 ns molecular dynamics (MD) simulations. The stability through the 100 ns run has been evident for some nominated inhibitors, which are valuable lead compounds that can be optimized to reach the greatest physicochemical properties in addition to the selectivity.