Decoding of novel missense TSC2 gene variants using in-silico methods - Shruthi Sudarshan; Manoj Kumar; Punit Kaur; Atin Kumar; Sethuraman G.; Savita Sapra; Sheffali Gulati; Neerja Gupta; Madhulika Kabra; Madhumita Roy Chowdhury (BMC, 2019)
Abstract Background Mutations in TSC1 or TSC2 gene cause tuberous sclerosis complex (TSC), an autosomal dominant disorder characterized by the formation of non-malignant hamartomas in multiple vital organs. TSC1 and TSC2 gene products form TSC heterodimer that senses specific cell growth conditions to control mTORC1 signalling. Methods In the present study 98 TSC patients were tested for variants in TSC1 and TSC2 genes and 14 novel missense variations were identified. The pathogenecity of these novel variations was determined by applying different bioinformatics tools involving computer aided protein modeling. Results Protein modelling could be done only for ten variants which were within the functional part of the protein. Homology modeling is the most reliable method for structure prediction of a protein. Since no sequence homology structure was available for the tuberin protein, three dimensional structure was modeled by a combination of homology modeling and the predictive fold recognition and threading method using Phyre2 threading server. The best template structures for model building of the TSC1 interacting domain, tuberin domain and GAP domain are the crystal structures of clathrin adaptor core protein, Rap1GAP catalytic domain and Ser/Thr kinase Tor protein respectively. Conclusions In this study, an attempt has been made to assess the impact of each novel missense variant based on their TSC1-TSC2 hydrophobic interactions and its effect on protein function.