Computational screening and structural analysis of Gly201Arg and Gly201Asp missense mutations in human cyclin-dependent kinase 4 protein.

The regulatory proteins, cyclins, and cyclin-dependent kinases (CDKs) control the cell cycle progression. CDK4 gene mutations are associated with certain cancers such as melanoma, breast cancer, and rhabdomyosarcoma. Therefore, understanding the mechanisms of cell cycle control and cell proliferation is essential in developing cancer treatment regimens. In this study, we obtained cancer-causing CDK4 mutations from the COSMIC database and subjected them to a series of in silico analyses to identify the most significant mutations. An overall of 238 mutations (119 missense mutations) retrieved from the COSMIC database were investigated for the pathogenic and destabilizing properties using the PredictSNP and iStable algorithms. Further, the amino acid position of the most pathogenic and destabilizing mutations were analyzed to understand the nature of amino acid conservation across the species during the evolution. We observed that the missense mutations G201R and G201D were more significant and the Glycine at position 201 was found to highly conserved. These significant mutations were subjected to molecular dynamics simulation analysis to understand the protein's structural changes. The results from molecular dynamics simulations revealed that both G201R and G201D of CDK4 are capable of altering the protein's native form. On comparison among the most significant mutations, G201R disrupted the protein structure higher than the protein with G201D.

Mutations in G6PC2 gene with increased risk for development of type 2 diabetes: Understanding via computational approach.

An increase in the fast blood glucose (FBG) levels has been linked to an increased risk of developing a chronic condition, type 2 diabetes (T2D). The mutation in the G6PC2 gene was identified to have a lead role in the modulation of FBG levels. The abnormal regulation of this enzyme influences glucose-stimulated insulin secretion (GSIS), which controls the insulin levels corresponding to the system's glucose level. This study focuses on the mutations at the G6PC2 gene, which cause the variation from normal expression levels and increase the risk of T2D. We examined the non-synonymous single nucleotide polymorphisms (nsSNPs) present in the G6PC2 and subjected them to pathogenicity, stability, residue conservation, and membrane simulation. The individual representation of surrounding amino acids in the mutant (I63T) model showed the loss of hydrophobic interactions compared to the native G6PC2. In addition, the trajectory results from the membrane simulation exhibited reduced stability, and the least compactness was identified for the I63T mutant model. Our study shed light on the structural and conformational changes at the transmembrane region due to the I63T mutation in G6PC2. Additionally, the Gibbs free energy landscape analysis against the two principal components showed structural differences and decreased the conformational stability of the I63T mutant model compared to the native. Like those presented in this study, dynamical simulations may indeed be crucial to comprehending the structural insights of G6PC2 mutations in cardiovascular-associated mortality and T2D.

Analysis of Differentially Expressed Genes and Molecular Pathways in Familial Hypercholesterolemia Involved in Atherosclerosis: A Systematic and Bioinformatics Approach.

Background and Aims: Familial hypercholesterolemia (FH) is one of the major risk factor for the progression of atherosclerosis and coronary artery disease. This study focused on identifying the dysregulated molecular pathways and core genes that are differentially regulated in FH and to identify the possible genetic factors and potential underlying mechanisms that increase the risk to atherosclerosis in patients with FH. Methods: The Affymetrix microarray dataset (GSE13985) from the GEO database and the GEO2R statistical tool were used to identify the differentially expressed genes (DEGs) from the white blood cells (WBCs) of five heterozygous FH patients and five healthy controls. The interaction between the DEGs was identified by applying the STRING tool and visualized using Cytoscape software. MCODE was used to determine the gene cluster in the interactive networks. The identified DEGs were subjected to the DAVID v6.8 webserver and ClueGo/CluePedia for functional annotation, such as gene ontology (GO) and enriched molecular pathway analysis of DEGs. Results: We investigated the top 250 significant DEGs (p-value < 0.05; fold two change ≥ 1 or ≤ -1). The GO analysis of DEGs with significant differences revealed that they are involved in critical biological processes and molecular pathways, such as myeloid cell differentiation, peptidyl-lysine modification, signaling pathway of MyD88-dependent Toll-like receptor, and cell-cell adhesion. The analysis of enriched KEGG pathways revealed the association of the DEGs in ubiquitin-mediated proteolysis and cardiac muscle contraction. The genes involved in the molecular pathways were shown to be differentially regulated by either activating or inhibiting the genes that are essential for the canonical signaling pathways. Our study identified seven core genes (UQCR11, UBE2N, ADD1, TLN1, IRAK3, LY96, and MAP3K1) that are strongly linked to FH and lead to a higher risk of atherosclerosis. Conclusion: We identified seven core genes that represent potential molecular biomarkers for the diagnosis of atherosclerosis and might serve as a platform for developing therapeutics against both FH and atherosclerosis. However, functional studies are further needed to validate their role in the pathogenesis of FH and atherosclerosis.

Computational model to analyze and characterize the functional mutations of NOD2 protein causing inflammatory disorder - Blau syndrome.

Blau syndrome (BS), which affects the eyes, skin, and joints, is an autosomal dominant genetic inflammatory disorder. BS is caused by mutations in the NOD2 gene. However, there are no direct treatments, and treatment with conventional anti-inflammatory drugs such as adrenal glucocorticoids, anti-metabolites, and biological agents such as anti-TNF and infliximab have all been attempted with varying degrees of success. In this study, we tried to identify all the reported mutations in the NOD2 protein that cause BS. Collectively, 114 missense mutations were extracted from the UniProt, ClinVar, and HGMD databases. The mutations were further subjected to pathogenic, stability, and conservation analyses. According to these computational analyses, six missense mutations (R334Q, R334W, E383G, E383K, R426H, and T605P) were found to be highly deleterious, destabilizing, and positioned in the conserved position. ADP to ATP conversion plays a crucial role in switching the closed-form of NOD2 protein to the open-form, thus activating the protein. Accordingly, the mutations in the ADP binding sites have received more attention in comparison to the mutations in the non-ADP binding positions. Interestingly, the W490L mutation is positioned in the ADP binding site and exhibits highly deleterious and destabilizing properties. Additionally, W490L was also found to be conserved, with a ConSurf score of 7. Therefore, we further performed homology modeling to determine the 3D structure of native NOD2 and the W490L mutant. Molecular docking analysis was carried out to understand the change in the interaction of ADP with the NOD2 protein. We observed that ADP had a stronger interaction with the native NOD2 protein compared to the W490L mutant. Finally, ADP complexed with native NOD2 and W490L mutant were subjected to molecular dynamics simulations, and the trajectories were analyzed. In the simulations, we observed decreased deviation and fluctuations in native NOD2, whereas decreased compactness and inter- and intramolecular hydrogen bonds were observed in the W490L mutant. This study is expected to serve as a platform for developing targeted drug therapy for BS.