Computational Insights into the Deleterious Impacts of Missense Variants on N-Acetyl-d-glucosamine Kinase Structure and Function

Identification and analysis of oncogenic non-synonymous single nucleotide polymorphisms in the human NRAS gene: An exclusive in silico study

BACKGROUND

N-ras protein is encoded by the NRAS gene and operates as GDP-GTP-controlled on/off switching. N-ras interacts with cellular signaling networks that regulate various cellular activities including cell proliferation and survival. The nonsynonymous single nucleotide polymorphism (nsSNPs)-mediated alteration can substantially disrupt the structure and activity of the corresponding protein. N-ras has been reported to be associated with numerous diseases including cancers due to the nsSNPs. A comprehensive study on the NRAS gene to unveil the potentially damaging and oncogenic nsSNPs is yet to be accomplished. Hence, this extensive in silico study is intended to identify the disease-associated, specifically oncogenic nsSNPs of the NRAS gene.

RESULTS

Out of 140 missense variants, 7 nsSNPs (I55R, G60E, G60R, Y64D, L79F, D119G, and V152F) were identified to be damaging utilizing 10 computational tools that works based on different algorithms with high accuracy. Among those, G60E, G60R, and D119G variants were further filtered considering their location in the highly conserved region and later identified as oncogenic variants. Interestingly, G60E and G60R variants were revealed to be particularly associated with lung adenocarcinoma, rhabdomyosarcoma, and prostate adenocarcinoma. Therefore, D119G could be subjected to detailed investigation for identifying its association with specific cancer.

CONCLUSION

This in silico study identified the deleterious and oncogenic missense variants of the human NRAS gene that could be utilized for designing further experimental investigation. The outcomes of this study would be worthwhile in future research for developing personalized medicine.

Impact of nsSNPs in human AIM2 and IFI16 gene: a comprehensive in silico analysis

AIM2 and IFI16 are the most studied members of AIM2-like receptors (ALRs) in humans and share a common N-Terminal PYD domain and C-terminal HIN domain. The HIN domain binds to dsDNA in response to the invasion of bacterial and viral DNA, and the PYD domain directs apoptosis-associated speck-like protein via protein-protein interactions. Hence, activation of AIM2 and IFI16 is crucial for protection against pathogenic assaults, and any genetic variation in these inflammasomes can dysregulate the human immune system. In this study, different computational tools were used to identify the most deleterious and disease-causing non-synonymous single nucleotide polymorphisms (nsSNPs) in AIM2 and IFI16 proteins. Molecular dynamic simulation was performed for the top damaging nsSNPs to study single amino acid substitution-induced structural alterations in AIM2 and IFI16. The observed results suggest that the variants G13V, C304R, G266R, and G266D for AIM2, and G13E and C356F are deleterious and affect structural integrity. We hope that the suggested deleterious nsSNPs and structural dynamics of AIM2 and IFI16 variants will guide future research to better understand the function of these variants with large-scale studies and may assist in fresher therapeutics focusing on these polymorphisms.Communicated by Ramaswamy H. Sarma.

Insights into Omicron's Low Fusogenicity through In Silico Molecular Studies on Spike-Furin Interactions

The Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant and its subvariants have a unique set of mutations. Two of those mutations (N679 K and P681 H) reside close to the S1 /S2 furin cleavage site (FCS; 685-686). When these mutations reside together, they exert less-efficient membrane fusion than wild type and most other variants of concern such as the Delta variant. Here, we in silico targeted these mutations to find out which of the amino acids and interactions change plays the key role in fusion. To comprehend the epistatic effect of N679 K and P681 H mutations on the spike protein, we in silico constructed three types of spike protein sequences by changing the respective amino acids on 679 and 681 positions (P681 H, N679 K, K679 N-H681 P variants). We then analyzed the binding affinity of furin and spike (Furin-Wild, Furin-Omicron, Furin-P681 H, Furin-N679 K, and Furin-K679 N/H681 P) complexes. Omicron and P681 H variants showed a similar higher binding energy trend compared to the wild type and N679 K. The variation in hydrogen, hydrophobic, and salt bridge bonds between spike protein and furin provided an explanation for the observed low fusogenicity of Omicron. The fate of the epistasis in furin binding and possible cleavage depends on the efficient interaction between FCS in spike and furin catalytic triad, and in addition, the loss of the hydrogen bond between Arg 681 (spike) and Asn 295 (furin) along with inhibitor-like ineffective higher affinity plays an important role in the enzymatic activity.

Dynamic insights into the effects of nonsynonymous polymorphisms (nsSNPs) on loss of TREM2 function

Single nucleotide variations in Triggering Receptor Expressed on Myeloid Cells 2 (TREM2) are associated with many neurodegenerative diseases, including Nasu-Hakola disease (NHD), frontotemporal dementia (FTD), and late-onset Alzheimer's disease because they disrupt ligand binding to the extracellular domain of TREM2. However, the effects of nonsynonymous single nucleotide polymorphisms (nsSNPs) in TREM2 on disease progression remain unknown. In this study, we identified several high-risk nsSNPs in the TREM2 gene using various deleterious SNP predicting algorithms and analyzed their destabilizing effects on the ligand recognizing region of the TREM2 immunoglobulin (Ig) domain by molecular dynamics (MD) simulation. Cumulative prediction by all tools employed suggested the three most deleterious nsSNPs involved in loss of TREM2 function are rs549402254 (W50S), rs749358844 (R52C), and rs1409131974 (D104G). MD simulation showed that these three variants cause substantial structural alterations and conformational remodeling of the apical loops of the TREM2 Ig domain, which is responsible for ligand recognition. Detailed analysis revealed that these variants substantially increased distances between apical loops and induced conformation remodeling by changing inter-loop nonbonded contacts. Moreover, all nsSNPs changed the electrostatic potentials near the putative ligand-interacting region (PLIR), which suggested they might reduce specificity or loss of binding affinity for TREM2 ligands. Overall, this study identifies three potential high-risk nsSNPs in the TREM2 gene. We propose further studies on the molecular mechanisms responsible for loss of TREM2 function and the associations between TREM2 nsSNPs and neurodegenerative diseases.

Genome interpretation using in silico predictors of variant impact

Estimating the effects of variants found in disease driver genes opens the door to personalized therapeutic opportunities. Clinical associations and laboratory experiments can only characterize a tiny fraction of all the available variants, leaving the majority as variants of unknown significance (VUS). In silico methods bridge this gap by providing instant estimates on a large scale, most often based on the numerous genetic differences between species. Despite concerns that these methods may lack reliability in individual subjects, their numerous practical applications over cohorts suggest they are already helpful and have a role to play in genome interpretation when used at the proper scale and context. In this review, we aim to gain insights into the training and validation of these variant effect predicting methods and illustrate representative types of experimental and clinical applications. Objective performance assessments using various datasets that are not yet published indicate the strengths and limitations of each method. These show that cautious use of in silico variant impact predictors is essential for addressing genome interpretation challenges.

Structural Consequence of Non-Synonymous Single-Nucleotide Variants in the N-Terminal Domain of LIS1

Disruptive neuronal migration during early brain development causes severe brain malformation. Characterized by mislocalization of cortical neurons, this condition is a result of the loss of function of migration regulating genes. One known neuronal migration disorder is lissencephaly (LIS), which is caused by deletions or mutations of the LIS1 (PAFAH1B1) gene that has been implicated in regulating the microtubule motor protein cytoplasmic dynein. Although this class of diseases has recently received considerable attention, the roles of non-synonymous polymorphisms (nsSNPs) in LIS1 on lissencephaly progression remain elusive. Therefore, the present study employed combined bioinformatics and molecular modeling approach to identify potential damaging nsSNPs in the LIS1 gene and provide atomic insight into their roles in LIS1 loss of function. Using this approach, we identified three high-risk nsSNPs, including rs121434486 (F31S), rs587784254 (W55R), and rs757993270 (W55L) in the LIS1 gene, which are located on the N-terminal domain of LIS1. Molecular dynamics simulation highlighted that all variants decreased helical conformation, increased the intermonomeric distance, and thus disrupted intermonomeric contacts in the LIS1 dimer. Furthermore, the presence of variants also caused a loss of positive electrostatic potential and reduced dimer binding potential. Since self-dimerization is an essential aspect of LIS1 to recruit interacting partners, thus these variants are associated with the loss of LIS1 functions. As a corollary, these findings may further provide critical insights on the roles of LIS1 variants in brain malformation.