Molecular descriptor-based QSPR analysis of physicochemical properties in neuromuscular drugs

Neuromuscular diseases are conditions that affect the nerves controlling voluntary muscles, leading to a decline in muscle function. These diseases disrupt the communication between neurons and muscles, causing symptoms like muscle weakening, atrophy and loss of muscle control. These disorders can arise from various factors, including infections, autoimmune responses, genetic mutations, and environmental influences. To tackle these genetically driven dysfunctions, the pharmaceutical industry explores improving drug design through quantitative structure property relationship models. These models link molecular structure with physicochemical properties for the development of new drugs. Degree-based topological indices, derived from structural graphs, enable systematic analysis of neuromuscular drugs without the need for empirical data. This study focuses on the quantitative structure property relationship analysis of molecular descriptors and physicochemical properties of neuromuscular drug structures like astaxanthin, drotaverine, risdiplam, riluzole, edaravone, along with a total of 15 drug structures. This approach employs regression models to offer a time-efficient and cost-effective way to characterize chemical structures and optimize drug design for treating these conditions.