ABSTRACT
The glucocorticoid resistance hereditary condition may emerge from the occurrence of point mutations in the glucocorticoid receptor (GR), which could impair its functionality. Because the main feature of such pathology is the resistance of the hypothalamic-pituitary-adrenal axis to the hormone cortisol, we used the GR ligand binding domain three-dimensional structure to perform computational analysis for eight variants known to cause this clinical condition (I559â¯N, V571A, D641V, G679S, F737L, I747â¯M, L753F and L773P), aiming to understand, on the atom scale, how they cause glucocorticoid resistance. We observed that the mutations generated a reduced affinity to cortisol and they alter some loop conformations, which could be a consequence from changes in protein motion, which in turn could result from the reduced stability of mutant GR structures. Therefore, the analyzed mutations compromise the GR ligand binding domain structure and cortisol binding, which could characterize the glucocorticoid resistance phenotype.
Subject(s)
Glucocorticoids/chemistry , Models, Molecular , Mutation, Missense , Protein Interaction Domains and Motifs , Receptors, Glucocorticoid/chemistry , Receptors, Glucocorticoid/genetics , Amino Acid Sequence , Binding Sites , Evolution, Molecular , Glucocorticoids/pharmacology , Humans , Ligands , Molecular Docking Simulation , Molecular Dynamics Simulation , Polymorphism, Single Nucleotide , Protein Binding , Protein Interaction Domains and Motifs/genetics , Structure-Activity RelationshipABSTRACT
Insulin-like growth factor 1 receptor (IGF1R) acts as a critical mediator of cell proliferation and survival. Many single nucleotide polymorphisms (SNPs) found in the IGF1R gene have been associated with various diseases, including both breast and prostate cancer. The genetics of these diseases could be better understood by knowing the functions of these SNPs. In this study, we performed a comprehensive analysis of the functional and structural impact of all known SNPs in this gene using publicly available computational prediction tools. Out of a total of 2412 SNPs in IGF1R retrieved from dbSNP, we found 32 nsSNPs, 58 sSNPs, 83 mRNA 3' UTR SNPs, and 2225 intronic SNPs. Among the nsSNPs, a total of six missense nsSNPs were found to be damaging by both a sequence homology-based tool (SIFT) and a structural homology-based method (PolyPhen), and one nonsense nsSNP was found. Further, we modeled mutant proteins and compared the total energy values with the native IGF1R protein, and showed that a mutation from arginine to cysteine at position 1216 (rs61740868) on the surface of the protein caused the greatest impact on stability. Also, the FASTSNP tool suggested that 31 sSNPs and 3 intronic SNPs might affect splicing regulation. Based on our investigation, we report potential candidate SNPs for future studies on IGF1R mutations.
