Computational Identification Of Human TGFΒ1 Gene: SNPS And Prediction Of Their Effect On Protein Functions Of Preeclampsia Patients

Growth factor (TGF-β1) belongs to the superfamily (TGF-β) as it has different roles and functions and participates in various physiological, biological, and pathological processes. The protein (TGF-β1) works to regulate cellular processes through pathways in which there is a connection to membrane receptors, which are of two types, I and II. Gene expression (TGF-β1) as well as its receptors can occur in the human placenta. This study aimed to identify some molecular parameters that could be considered accurate diagnostic parameters. Predictive bioinformatics techniques were used to predict whether the change occurring in the amino acid within the protein chain would affect the function of the protein in the future and thus the occurrence of the disease. The disease database, in which mutations were found, will be used and registered in the future. Mutations that occurred in the coding region that changed the amino acid in the protein were identified and tabulated in special tables. After that, the protein’s sequence was obtained, and four predictive bioinformatics algorithms were applied. The results of this study showed that most of the mutations affect the natural protein. The effect may be on the physical and chemical properties, and it may be on the structural stability of the protein. Conclusions The candidate mutations in this study are mutations that can be considered diagnostic molecular indicators of preeclampsia.