Unraveling Extremely Damaging IRAK4 Variants and Their Potential Implications for IRAK4 Inhibitor Efficacy.

Interleukin-1-receptor-associated kinase 4 (IRAK4) possesses a crucial function in the toll-like receptor (TLR) signaling pathway, and the dysfunction of this molecule could lead to various infectious and immune-related diseases in addition to cancers. IRAK4 genetic variants have been linked to various types of diseases. Therefore, we conducted a comprehensive analysis to recognize the missense variants with the most damaging impacts on IRAK4 with the employment of diverse bioinformatics tools to study single-nucleotide polymorphisms' effects on function, stability, secondary structures, and 3D structure. The residues' location on the protein domain and their conservation status were investigated as well. Moreover, docking tools along with structural biology were engaged in analyzing the SNPs' effects on one of the developed IRAK4 inhibitors. By analyzing IRAK4 gene SNPs, the analysis distinguished ten variants as the most detrimental missense variants. All variants were situated in highly conserved positions on an important protein domain. L318S and L318F mutations were linked to changes in IRAK4 secondary structures. Eight SNPs were revealed to have a decreasing effect on the stability of IRAK4 via both I-Mutant 2.0 and Mu-Pro tools, while Mu-Pro tool identified a decreasing effect for the G198E SNP. In addition, detrimental effects on the 3D structure of IRAK4 were also discovered for the selected variants. Molecular modeling studies highlighted the detrimental impact of these identified SNP mutant residues on the druggability of the IRAK4 ATP-binding site towards the known target inhibitor, HG-12-6, as compared to the native protein. The loss of important ligand residue-wise contacts, altered protein global flexibility, increased steric clashes, and even electronic penalties at the ligand-binding site interfaces were all suggested to be associated with SNP models for hampering the HG-12-6 affinity towards IRAK4 target protein. This given model lays the foundation for the better prediction of various disorders relevant to IRAK4 malfunction and sheds light on the impact of deleterious IRAK4 variants on IRAK4 inhibitor efficacy.

Computational Analysis of Deleterious SNPs in NRAS to Assess Their Potential Correlation With Carcinogenesis.

The NRAS gene is a well-known oncogene that acts as a major player in carcinogenesis. Mutations in the NRAS gene have been linked to multiple types of human tumors. Therefore, the identification of the most deleterious single nucleotide polymorphisms (SNPs) in the NRAS gene is necessary to understand the key factors of tumor pathogenesis and therapy. We aimed to retrieve NRAS missense SNPs and analyze them comprehensively using sequence and structure approaches to determine the most deleterious SNPs that could increase the risk of carcinogenesis. We also adopted structural biology methods and docking tools to investigate the behavior of the filtered SNPs. After retrieving missense SNPs and analyzing them using six in silico tools, 17 mutations were found to be the most deleterious mutations in NRAS. All SNPs except S145L were found to decrease NRAS stability, and all SNPs were found on highly conserved residues and important functional domains, except R164C. In addition, all mutations except G60E and S145L showed a higher binding affinity to GTP, implicating an increase in malignancy tendency. As a consequence, all other 14 mutations were expected to increase the risk of carcinogenesis, with 5 mutations (G13R, G13C, G13V, P34R, and V152F) expected to have the highest risk. Thermodynamic stability was ensured for these SNP models through molecular dynamics simulation based on trajectory analysis. Free binding affinity toward the natural substrate, GTP, was higher for these models as compared to the native NRAS protein. The Gly13 SNP proteins depict a differential conformational state that could favor nucleotide exchange and catalytic potentiality. A further application of experimental methods with all these 14 mutations could reveal new insights into the pathogenesis and management of different types of tumors.

Integrative analysis of WDR12 as a potential prognostic and immunological biomarker in multiple human tumors.

Background: Mammalian WD-repeat protein 12 (WDR12), a family member of proteins containing repeats of tryptophan-aspartic acid (WD), is a potential homolog of yeast Ytm1p and consists of seven repeats of WD. Aim of the study: This study aims to investigate the potential oncogenic effects of WDR12 in various human malignancies throughout a pan-cancer analysis that has been carried out to examine the various patterns in which this gene is expressed and behaves in tumor tissues. Methods: Herein, we used The Cancer Genome Atlas (TCGA) and various computational tools to explore expression profiles, prognostic relevance, genetic mutations, immune cell infiltration, as well as the functional characteristics of WDR12 in multiple human cancers. Results: We found that WDR12 was inconsistently expressed in various cancers and that variations in WDR12 expression predicted survival consequences for cancer patients. Furthermore, we observed a significant correlation between WDR12 gene mutation levels and the prognosis of some tumors. Furthermore, significant correlations were found between WDR12 expression patterns and cancer-associated fibroblast (CAF) infiltration, myeloid-derived suppressor cells (MDSCs), tumor mutation burden, microsatellite instability and immunoregulators. Ultimately, pathway enrichment analysis revealed that WDR12-related pathways are involved in carcinogenesis. Conclusions: The findings of our study are stisfactory, demonstrating that WDR12 could serve as a promising reliable prognostic biomarker, as well as a therapeutic target for novel cancer therapeutic approaches.