A computational approach to study hereditary spastic paraplegia and associated SINO syndrome.

SINO syndrome, a condition related to hereditary spastic paraplegia (HSP), is often associated to KIDINS220 mutations. With this study our research group aims to predict the effects of KIDINS220 mutations, and eventually, through virtual screening, identify promising therapeutic molecules in a drug repurposing perspective. To achieve this, a comprehensive database was created to collect and catalogue the genetic, chemical, and clinical data associated with various KIDINS220 mutations. AlphaFold was then used for structural prediction coupled with 3DVarPro, an innovative tool developed in our lab, to map mutations onto the 3D structures. To investigate the effects of mutations, molecular dynamics simulations was performed on a single protein domain, comparing wild-type and mutant forms (K224E and D70G). Molecular dynamics trajectories were also analysed using MDpocket to identify protein binding pockets, which were used to screen for potential protein ligands. Overall, in this study we present a workflow for identifying possible therapeutic molecules to treat HSP and related conditions like SINO syndrome. It provides a valuable starting point for future research which aim to develop novel treatments for these and other rare diseases.