Computational Screening of Natural Products Against SOD1 to Identify Potential ALS Therapeutics

Abstract Neurodegenerative diseases are becoming more common and encompass multiple disorders that result in the loss of neurons, aging of the brain, and eventually lead to death. Amyotrophic lateral sclerosis (ALS) is the most common and devastating neurological disease driven by a gradual loss of motor neurons. It is essential to use cutting-edge technology in drug discovery as conventional methods become slower and more costly. In silico strategies provide a reliable, quick, and affordable alternative to the clumsy in vitro methods to improve our understanding of how drugs affect protein structure and related activities. Natural products have strong anti-inflammatory and antioxidant activities. In the present work, we test natural compounds against the SOD1 protein to combat the ALS disease. After identification of the protein, we performed structure-based pharmacophore screening and ADMET analyses of the top hit compounds based on RMSD. Molecular docking and molecular dynamics simulation analyses were applied, and the top two novel compounds reported against ALS showed effective binding properties. The dynamics simulation experiments were conducted at a 100 ns scale to identify the protein's behavior toward the recognized two ligands, Scytonine and Raocyclamide_A. The novel compounds Scytonine and Raocyclamide_A are non-toxic and meet the requirements of ADMET and BBB likeness parameters. The findings from this study will aid researchers in understanding the chemical compounds that interact with our target SOD1 protein. Furthermore, a future path in the realm of drug discovery may involve studying these molecules in vivo/vitro will help to design and test therapeutic medications.