Determining the role of missense mutations in the POU domain of HNF1A that reduce the DNA-binding affinity: A computational approach

Identification of high-risk non-synonymous SNPs (nsSNPs) in DNAH1 and DNAH17 genes associated with male infertility: a bioinformatics analysis

Male infertility is a significant reproductive issue affecting a considerable number of couples worldwide. While there are various causes of male infertility, genetic factors play a crucial role in its development. We focused on identifying and analyzing the high-risk nsSNPs in DNAH1 and DNAH17 genes, which encode proteins involved in sperm motility. A total of 20 nsSNPs for DNAH1 and 10 nsSNPs for DNAH17 were analyzed using various bioinformatics tools including SIFT, PolyPhen-2, CADD, PhD-SNPg, VEST-4, and MutPred2. As a result, V1287G, L2071R, R2356W, R3169C, R3229C, E3284K, R4096L, R4133C, and A4174T in DNAH1 gene and C1803Y, C1829Y, R1903C, and L3595P in DNAH17 gene were identified as high-risk nsSNPs. These nsSNPs were predicted to decrease protein stability, and almost all were found in highly conserved amino acid positions. Additionally, 4 nsSNPs were observed to alter post-translational modification status. Furthermore, the interaction network analysis revealed that DNAH1 and DNAH17 interact with DNAH2, DNAH3, DNAH5, DNAH7, DNAH8, DNAI2, DNAL1, CFAP70, DNAI3, DNAI4, ODAD1, and DNAI7, demonstrating the importance of DNAH1 and DNAH17 proteins in the overall functioning of the sperm motility machinery. Taken together, these findings revealed the detrimental effects of identified high-risk nsSNPs on protein structure and function and highlighted their potential relevance to male infertility. Further studies are warranted to validate these findings and to elucidate the underlying mechanisms.

Characterization of missense nonsynonymous single-nucleotide polymorphism of runt-related transcription factor-2 gene - An in silico approach

OBJECTIVES

Single-nucleotide polymorphism (SNP) codes for multiple amino acids, impacting protein functions and disease prognosis. Runt-related transcription factor-2 (RUNX2), a transcription factor linked to osteoblast differentiation, regulates cell proliferation in endothelium and osteoblastic cells. Understanding Runx2's role in nonosseous tissues is rapidly advancing. This study aims to identify harmful SNPs of the RUNX2 gene that may alter disease susceptibility using computational techniques.

METHODS

The study uses various in silico methods to identify nonsynonymous SNPs (nsSNPs) of the RUNX2 gene, which could potentially alter protein structure and functions, with further analyses by I-Mutant, ConSurf, Netsurf 3.0, GeneMANIA, and Have (y)Our Protein Explained.

RESULTS

Six missense nsSNPs were identified as potentially harmful, disease-causing, and damaging. Four were found to be unstable, while five were conserved. All six nsSNPs had a coiled secondary structure. Five nsSNPs were found to be destabilized.

CONCLUSION

The RUNX2 gene's deleterious missense nsSNPs were identified by this study, and they may be exploited in future experimental studies. These high-risk nsSNPs might be considered target molecules in therapeutic and diagnostic therapies in teeth and bone development.

Computational analysis of the functional and structural impact of the most deleterious missense mutations in the human Protein C

Protein C (PC) is a vitamin K-dependent factor that plays a crucial role in controlling anticoagulant processes and acts as a cytoprotective agent to promote cell survival. Several mutations in human PC are associated with decreased protein production or altered protein structure, resulting in PC deficiency. In this study, we conducted a comprehensive analysis of nonsynonymous single nucleotide polymorphisms in human PC to prioritize and confirm the most high-risk mutations predicted to cause disease. Of the 340 missense mutations obtained from the NCBI database, only 26 were classified as high-risk mutations using various bioinformatic tools. Among these, we identified that 12 mutations reduced the stability of protein, and thereby had the greatest potential to disturb protein structure and function. Molecular dynamics simulations revealed moderate alterations in the structural stability, flexibility, and secondary structural organization of the serine protease domain of human PC for five missense mutations (L305R, W342C, G403R, V420E, and W444C) when compared to the native structure that could maybe influence its interaction with other molecules. Protein-protein interaction analyses demonstrated that the occurrence of these five mutations can affect the regular interaction between PC and activated factor V. Therefore, our findings assume that these mutants can be used in the identification and development of therapeutics for diseases associated with PC dysfunction, although assessment the effect of these mutations need to be proofed in in-vitro.

Lysine 117 Residue Is Essential for the Function of the Hepatocyte Nuclear Factor 1α

Hepatocyte nuclear factor 1α (HNF1α) plays essential roles in controlling development and metabolism; its mutations are clearly linked to the occurrence of maturity-onset diabetes of the young (MODY3) in humans. Lysine 117 (K117) to glutamic acid (E117) mutation in the HNF1α gene has been clinically associated with MODY3, but no functional data on this variant are available. Here, we addressed the role of lysine 117 in HNF1α function using a knock-in animal model and site-directed mutagenesis. HNF1α K117E homozygous mice exhibited dwarfism, hepatic dysfunction, renal Fanconi syndrome, and progressive wasting syndrome. These phenotypes were very similar to those of mice with complete HNF1α deficiency, suggesting that K117 is critical to HNF1α functions. K117E homozygotes developed diabetes in the early postnatal period. The relative deficiency of serum insulin levels and the normal response to insulin treatment in homozygous mice were markedly similar to those in the MODY3 disorder in humans. Moreover, K117E heterozygous mutant causes age-dependent glucose intolerance, which is similar to the pathogenesis of MODY3 as well. K117 mutants significantly reduced the overall transactivation and DNA binding capacity of HNF1α by disrupting dimerization. Collectively, our findings reveal a previously unappreciated role of POU domain of HNF1α in homodimerization and provide important clues for identifying the molecular basis of HNF1α-related diseases such as MODY3.

ARTICLE HIGHLIGHTS

HNF1α K117E homozygous mice exhibited dwarfism, hepatic dysfunction, renal Fanconi syndrome, and progressive wasting syndrome. K117E homozygotes developed diabetes in the early postnatal period. K117E heterozygous mutant causes age-dependent glucose intolerance, which is similar to the pathogenesis of maturity-onset diabetes of the young. K117 mutants significantly reduced the overall transactivation and DNA binding capacity of HNF1α by disrupting dimerization.

Enhanced stability of a disaggregated Aβ fibril on removal of ligand inhibits refibrillation: An all atom Molecular Dynamics simulation study

The extraneuronally deposited senile plaques, composed of neurotoxic aggregates of Aβ fibril, define Alzheimer's disease (AD). Natural compounds have been tested for their destabilization potential on Aβ fibril, thereby curing AD. However, the resultant destabilized Aβ fibril, needs to be checked for its irreversibility to the native organized state after removal of the ligand. Herein, we assessed the stability of a destabilized fibril after the ligand (ellagic acid represented as REF) is removed from the complex. The study has been conducted via Molecular Dynamics (MD) simulation of 1 μs for both Aβ-Water (control) and Aβ-REF″ (test or REF removed) system. The increased value of RMSD, R_g, SASA, lower β-sheet content and reduced number of H-bonds explains enhanced destabilization observed in Aβ-REF″ system. The increased inter-chain distance demonstrates breaking of the residual contacts, testifying the drift of terminal chains from the pentamer. The increased SASA along with the ∆G_ps(polar solvation energy) accounts for the reduced interaction amongst residues, and more with solvent molecules, governing irreversibility to native state. The higher Gibb's free energy of the misaligned structure of Aβ-REF″ ensures irreversibility to the organized structure due to its inability to cross such high energy barrier. The observed stability of the disaggregated structure, despite ligand elimination, establishes the effectiveness of the destabilization technique as a promising therapeutic approach towards treating AD.

Resistance and Molecular Characteristics of Methicillin-Resistant Staphylococcus aureus and Heterogeneous Vancomycin-Intermediate Staphylococcus aureus

Objective

To investigate the molecular epidemiology of Staphylococcus aureus (S. aureus) isolated from patients in the Yellow River Delta region and to construct antibiotic resistance profiles in different genetic backgrounds.

Methods

Antibiotics susceptibility testing, staphylococcal protein A (spa) typing and accessory gene regulator (agr) typing were performed for all the 204 strains. Isolates with the positive mecA gene and heterogeneous vancomycin-intermediate S. aureus (hVISA) were subjected to multilocus sequence typing (MLST) and Staphylococcal chromosomal cassettes mec (SCCmec) typing.

Results

Thirty-nine MRSA strains were identified by mecA gene. Twenty-two hVISA isolates including 9 MRSA and 13 methicillin-sensitive S. aureus (MSSA) strains were confirmed, the rest isolates (n = 182) were vancomycin-susceptible S. aureus (VSSA). 94.9% of MRSA and 63.6% of hVISA belonged to agrI. Fifty-seven distinct spa types including 5 novel types were mainly t309 (30.9%), t078 (11.8%) and t437 (11.8%). Fourteen sequence types (STs) containing 3 new STs were classified into 3 clone complexes (CCs) and 7 singletons among MRSA and hVISA isolates. Most MRSA isolates (87.2%) belonged to type Ⅳ SCCmec.

Conclusion

The predominant genotype among MRSA population was ST59-t437-agrI-IVa (53.8%), followed by ST72-t2431-agrI-IVF (15.4%). ST72 and CC5 (ST5/965/7197) were the most common hVISA clones. Both CC59 (ST59/7437) and ST72 clones were resistant to erythromycin and clindamycin among MRSA population. Strains of MSSA with phenotypic hVISA (MS-hVISA) exhibited a striking genetic diversity accompanied by the diversification of drug resistance patterns.

Drug repurposing combined with MM/PBSA based validation strategies towards MEK inhibitors screening

Emergence of oncogenic mutations in the MAPK pathway gaining more impact in the recent years. Importantly, MEK is a core element of this pathway as it is easy to inhibit and is a gatekeeper of multiple malignancies. Therefore, we performed in-silico strategy to screen repurposed candidate for MEK protein using a library of 11,808 compounds from different clusters in the DrugBank database. Glide docking, Prime-MM/GBSA and QikProp analysis were implemented to retrieve the hits with high precision. The stability of the binding mode and binding affinity of the resultant hit were explored using molecular dynamic simulations and MM/PBSA approach. The results highlight that Nebivolol (DB04861) not only achieved a stable conformation in the MEK binding pocket but also displayed highest binding affinity than the other molecules investigated in our study. Taken together, we hypothesized that Nebivolol is an excellent candidate for the inhibition of MEK in NSCLC patients in future.Communicated by Ramaswamy H. Sarma.

Unraveling the Structural Changes in the DNA-Binding Region of Tumor Protein p53 (TP53) upon Hotspot Mutation p53 Arg248 by Comparative Computational Approach

The vital tissue homeostasis regulator p53 forms a tetramer when it binds to DNA and regulates the genes that mediate essential biological processes such as cell-cycle arrest, senescence, DNA repair, and apoptosis. Missense mutations in the core DNA-binding domain (109-292) simultaneously cause the loss of p53 tumor suppressor function and accumulation of the mutant p53 proteins that are carcinogenic. The most common p53 hotspot mutation at codon 248 in the DNA-binding region, where arginine (R) is substituted by tryptophan (W), glycine (G), leucine (L), proline (P), and glutamine (Q), is reported in various cancers. However, it is unclear how the p53 Arg248 mutation with distinct amino acid substitution affects the structure, function, and DNA binding affinity. Here, we characterized the pathogenicity and protein stability of p53 hotspot mutations at codon 248 using computational tools PredictSNP, Align GVGD, HOPE, ConSurf, and iStable. We found R248W, R248G, and R248P mutations highly deleterious and destabilizing. Further, we subjected all five R248 mutant-p53-DNA and wt-p53-DNA complexes to molecular dynamics simulation to investigate the structural stability and DNA binding affinity. From the MD simulation analysis, we observed increased RMSD, RMSF, and Rg values and decreased protein-DNA intermolecular hydrogen bonds in the R248-p53-DNA than the wt-p53-DNA complexes. Likewise, due to high SASA values, we observed the shrinkage of proteins in R248W, R248G, and R248P mutant-p53-DNA complexes. Compared to other mutant p53-DNA complexes, the R248W, R248G, and R248P mutant-p53-DNA complexes showed more structural alteration. MM-PBSA analysis showed decreased binding energies with DNA in all five R248-p53-DNA mutants than the wt-p53-DNA complexes. Henceforth, we conclude that the amino acid substitution of Arginine with the other five amino acids at codon 248 reduces the p53 protein's affinity for DNA and may disrupt cell division, resulting in a gain of p53 function. The proposed study influences the development of rationally designed molecular-targeted treatments that improve p53-based therapeutic outcomes in cancer.

HNF1A Mutations and Beta Cell Dysfunction in Diabetes

Understanding the genetic factors of diabetes is essential for addressing the global increase in type 2 diabetes. HNF1A mutations cause a monogenic form of diabetes called maturity-onset diabetes of the young (MODY), and HNF1A single-nucleotide polymorphisms are associated with the development of type 2 diabetes. Numerous studies have been conducted, mainly using genetically modified mice, to explore the molecular basis for the development of diabetes caused by HNF1A mutations, and to reveal the roles of HNF1A in multiple organs, including insulin secretion from pancreatic beta cells, lipid metabolism and protein synthesis in the liver, and urinary glucose reabsorption in the kidneys. Recent studies using human stem cells that mimic MODY have provided new insights into beta cell dysfunction. In this article, we discuss the involvement of HNF1A in beta cell dysfunction by reviewing previous studies using genetically modified mice and recent findings in human stem cell-derived beta cells.

HNF1A POU Domain Mutations Found in Japanese Liver Cancer Patients Cause Downregulation of HNF4A Promoter Activity with Possible Disruption in Transcription Networks

Hepatocyte nuclear factor 1A (HNF1A) is the master regulator of liver homeostasis and organogenesis and regulates many aspects of hepatocyte functions. It acts as a tumor suppressor in the liver, evidenced by the increased proliferation in HNF1A knockout (KO) hepatocytes. Hence, we postulated that any loss-of-function variation in the gene structure or composition (mutation) could trigger dysfunction, including disrupted transcriptional networks in liver cells. From the International Cancer Genome Consortium (ICGC) database of cancer genomes, we identified several HNF1A mutations located in the functional Pit-Oct-Unc (POU) domain. In our biochemical analysis, we found that the HNF1A POU-domain mutations Y122C, R229Q and V259F suppressed HNF4A promoter activity and disrupted the binding of HNF1A to its target HNF4A promoter without any effect on the nuclear localization. Our results suggest that the decreased transcriptional activity of HNF1A mutants is due to impaired DNA binding. Through structural simulation analysis, we found that a V259F mutation was likely to affect DNA interaction by inducing large conformational changes in the N-terminal region of HNF1A. The results suggest that POU-domain mutations of HNF1A downregulate HNF4A gene expression. Therefore, to mimic the HNF1A mutation phenotype in transcription networks, we performed siRNA-mediated knockdown (KD) of HNF4A. Through RNA-Seq data analysis for the HNF4A KD, we found 748 differentially expressed genes (DEGs), of which 311 genes were downregulated (e.g., HNF1A, ApoB and SOAT2) and 437 genes were upregulated. Kyoto Encyclopedia of Genes and Genomes (KEGG) mapping revealed that the DEGs were involved in several signaling pathways (e.g., lipid and cholesterol metabolic pathways). Protein–protein network analysis suggested that the downregulated genes were related to lipid and cholesterol metabolism pathways, which are implicated in hepatocellular carcinoma (HCC) development. Our study demonstrates that mutations of HNF1A in the POU domain result in the downregulation of HNF1A target genes, including HNF4A, and this may trigger HCC development through the disruption of HNF4A–HNF1A transcriptional networks.

HNF1A：From Monogenic Diabetes to Type 2 Diabetes and Gestational Diabetes Mellitus

Diabetes, a disease characterized by hyperglycemia, has a serious impact on the lives and families of patients as well as on society. Diabetes is a group of highly heterogeneous metabolic diseases that can be classified as type 1 diabetes (T1D), type 2 diabetes (T2D), gestational diabetes mellitus (GDM), or other according to the etiology. The clinical manifestations are more or less similar among the different types of diabetes, and each type is highly heterogeneous due to different pathogenic factors. Therefore, distinguishing between various types of diabetes and defining their subtypes are major challenges hindering the precise treatment of the disease. T2D is the main type of diabetes in humans as well as the most heterogeneous. Fortunately, some studies have shown that variants of certain genes involved in monogenic diabetes also increase the risk of T2D. We hope this finding will enable breakthroughs regarding the pathogenesis of T2D and facilitate personalized treatment of the disease by exploring the function of the signal genes involved. Hepatocyte nuclear factor 1 homeobox A (HNF1α) is widely expressed in pancreatic β cells, the liver, the intestines, and other organs. HNF1α is highly polymorphic, but lacks a mutation hot spot. Mutations can be found at any site of the gene. Some single nucleotide polymorphisms (SNPs) cause maturity-onset diabetes of the young type 3 (MODY3) while some others do not cause MODY3 but increase the susceptibility to T2D or GDM. The phenotypes of MODY3 caused by different SNPs also differ. MODY3 is among the most common types of MODY, which is a form of monogenic diabetes mellitus caused by a single gene mutation. Both T2D and GDM are multifactorial diseases caused by both genetic and environmental factors. Different types of diabetes mellitus have different clinical phenotypes and treatments. This review focuses on HNF1α gene polymorphisms, HNF1A-MODY3, HNF1A-associated T2D and GDM, and the related pathogenesis and treatment methods. We hope this review will provide a valuable reference for the precise and individualized treatment of diabetes caused by abnormal HNF1α by summarizing the clinical heterogeneity of blood glucose abnormalities caused by HNF1α mutation.

Identification of deleterious single nucleotide polymorphism (SNP)s in the human TBX5 gene & prediction of their structural & functional consequences: An in silico approach

T-box transcription factor 5 gene (TBX5) encodes the transcription factor TBX5, which plays a crucial role in the development of heart and upper limbs. Damaging single nucleotide variants in this gene alter the protein structure, disturb the functions of TBX5, and ultimately cause Holt-Oram Syndrome (HOS). By analyzing the available single nucleotide polymorphism information in the dbSNP database, this study was designed to identify the most deleterious TBX5 SNPs through insilico approaches and predict their structural and functional consequences.

Fifty-eight missense substitutions were found damaging by sequence homology-based tools: SIFT and PROVEAN, and structure homology-based tool PolyPhen-2. Various disease association meta-predictors further scrutinized these SNPs. Additionally, conservation profile of the amino acid residues, their surface accessibility, stability, and structural integrity of the native protein upon mutations were assessed. From these analyses, finally 5 SNPs were detected as the most damaging ones: [rs1565941579 (P85S), rs1269970792 (W121R), rs772248871 (V153D), rs769113870 (E208D), and rs1318021626 (I222N)]. Analyses of stop-lost, nonsense, UTR, and splice site SNPs were also conducted.

Through integrative bioinformatics analyses, this study has identified the SNPs that are deleterious to the TBX5 protein structure and have the potential to cause HOS. Further wet-lab experiments can validate these findings.

•

Deleterious SNPs in the human TBX5 gene responsible for Holt-Oram Syndrome have been identified.

•

58 missense and 2 nonsense SNPs were identified as deleterious.

•

86 3′ UTR SNPs were predicted to be located on miRNA target sites.

•

Possible effects of missense SNPs on the TBX5 protein structure have been studied.

The structural, functional, and dynamic effect of Tau tubulin kinase1 upon a mutation: A neuro-degenerative hotspot

Alzheimer's disease (AD) is a progressive disorder that causes brain cells to degenerate and die. AD is one of the common causes of dementia that leads to a decline in thinking, behavioral and social skills that disrupts a person's ability to function independently. Tau-tubulin kinase1 (TTBK1) is a crucial disease regulating AD protein, which is majorly responsible for the phosphorylation and accumulation of tau protein at specific Serine/Threonine residues found in paired helical filaments, suggesting its role in tauopathy. TTBK1 involvement in many diseases and the restricted expression of TTBK1 to the central nervous system (CNS) makes TTBK1 an attractive therapeutic target for tauopathies. The genetic variations in TTBK1 are primarily involved in the TTBK1 pathogenesis. This study highlighted the destabilizing, damaging and deleterious effect of the mutation R142Q on TTBK1 structure through computational predictions and molecular dynamics simulations. The protein deviation, fluctuations, conformational dynamics, solvent accessibility, hydrogen bonding, and the residue-residue mapping confirmed the mutant effect to cause structural aberrations, suggesting overall destabilization due to the protein mutation. The presence of well-defined free energy minima was observed in TTBK1-wild type, as opposed to that in the R142Q mutant, reflecting structural deterioration. The overall findings from the study reveal that the presence of R142Q mutation on TTBK1 is responsible for the structural instability, leading to disruption of its biological functions. The mutation could be used as future diagnostic markers in treating AD.

Polymorphisms at site 469 of B-RAF protein associated with skin melanoma may be correlated with dabrafenib resistance: An in silico study

Melanoma is a type of skin cancer. Numerous genes and their proteins are strongly associated with melanoma susceptibility. This study aims to use an in silico method to identify genetic variants in the melanoma susceptibility gene. The COSMIC database was queried for genes and cross-referenced with three environment-gene interaction databases (EGP, SeattleSNPs and CTD) to identify shared genes. The majority of approved skin melanoma drugs were found to act on the protein serine/threonine-protein kinase (B-RAF) encoded by the BRAF gene, which was also present in all three referenced databases. Comprehensive computational analysis was performed to predict deleterious genetic variants associated with skin melanoma, and the nsSNPs G469V and G469E were prioritized based on their predicted deleterious effects. Molecular dynamic simulation analysis of the B-RAF protein mutants G469V and G469E reveals that variations in the amino acid conformation at the drug binding site result in inconsistency in drug interaction. Additionally, this analysis showed that the G469V and G469E mutants have lower binding energy for dabrafenib than the wild type. The population with the highest frequency of each deleterious and pathogenic variant has been determined. The study's findings would support the development of more effective treatment strategies for skin melanoma. Communicated by Ramaswamy H. Sarma.

Mechanistic insights on nsSNPs on binding site of renin and cytochrome P450 proteins: A computational perceptual study for pharmacogenomics evaluation

Past several decades, therapeutic investigations lead to the discovery of numerous antihypertensive drugs. Although it has been proved for their potency, altered efficacy is common norms in several conditions due to genetic variations. Cytochrome P450 plays a crucial role in drug metabolism and responsible for the pharmacokinetic and pharmacodynamic properties of the drug molecules. Here, we report the deleterious point mutations in the genes associated with the altered response of antihypertensive drug molecules and their metabolizers. Missense variants were filtered as potential nonsynonymous single nucleotide polymorphisms among the available data for the target genes (REN, CYP2D6, CYP3A4). The key objective of the work is to identify the deleterious single nucleotide polymorphisms (SNPs) responsible for the drug response and metabolism for the application of personalized medication. The molecular docking studies revealed that Aliskiren and other clinically approved drug molecules have a high binding affinity with both wild and mutant structures of renin, CYP2D6, and CYP3A4 proteins. The docking (Glide XP) score was observed to have in the range of -8.896 to -11.693 kcal/mol. The molecular dynamics simulation studies were employed to perceive the structural changes and conformational deviation through various analyses. Each studied SNPs was observed to have disparate scoring in the binding affinity to the specific drug molecules. As a prospective plan, we assume this study might be applied to identify the risky SNPs associated with hypertension from the patients to recommend the suitable drug for personalized hypertensive treatment. Further, extensive clinical pharmacogenomics studies are required to support the findings.

A Review of Functional Characterization of Single Amino Acid Change Mutations in HNF Transcription Factors in MODY Pathogenesis

Mutations in HNF transcription factor genes cause the most common subtypes of maturity-onset of diabetes of youth (MODY), a monogenic form of diabetes mellitus. Mutations in the HNF1-α, HNF4-α, and HNF1-β genes are primarily considered as the cause of MODY3, MODY1, and MODY5 subtypes, respectively. Although patients with different subtypes display similar symptoms, they may develop distinct diabetes-related complications and require different treatments depending on the type of the mutation. Genetic analysis of MODY patients revealed more than 400 missense/nonsense mutations in HNF1-α, HNF4-α, and HNF1-β genes, however only a small portion of them are functionally characterized. Evaluation of nonsense mutations are more direct as they lead to premature stop codons and mostly in mRNA decay or nonfunctional truncated proteins. However, interpretation of the single amino acid change (missense) mutation is not such definite, as effect of the variant may vary depending on the location and also the substituted amino acid. Mutations with benign effect on the protein function may not be the pathologic variant and further genetic testing may be required. Here, we discuss the functional characterization analysis of single amino acid change mutations identified in HNF1-α, HNF4-α, and HNF1-β genes and evaluate their roles in MODY pathogenesis. This review will contribute to comprehend HNF nuclear family-related molecular mechanisms and to develop more accurate diagnosis and treatment based on correct evaluation of pathologic effects of the variants.

Bioinformatic and computational analysis for predominant mutations of the Nrf2/Keap1 complex in pediatric leukemia

The levels of reactive oxygen species (ROS) are tightly controlled and regulated by Nuclear Factor Erythroid-2-Like 2 (Nrf2) transcription factor, which is the main regulator of antioxidant responses and its suppressor protein Kelch-like ECH-associated protein 1 (Keap1). Our previous study has identified six novel changes in Nrf2/Keap1 pathway in pediatric ALL, which were described for the first time. These changes in the pathway are likely to alter the evolutionary process of amino acids and cause structural changes in the final products of genes. In this study, we aimed to compare the pathogenicity of eight determined mutations reported in our previous study by utilizing different programs with different algorithms and molecular dynamics simulation. Since it is too difficult to handle each existing mutation in a wet laboratory, in silico methods may give suggestion to choose the important mutations for further analysis and to establish the appropriate patient population and conduct wet laboratory studies. For this purpose, four different algorithms were used to evaluate the effects of single amino acid mutation. In addition, root-mean-square deviation, root-mean-square fluctuation and free-energy landscape analyses were performed to observe stability, flexibility and energetically favorable conformations, respectively, for each amino acid mutation. As a result, our study emphasizes the importance of Keap1 mutations in pediatric ALL Nrf2/Keap1 pathway, a total of eight mutations, two of which were shown for the first time in our study. Especially the mutations in the Keap1 Broad-Complex, Tramtrack and Bric-à-brac domain are worthy of attention.Communicated by Ramaswamy H. Sarma.

Functional Analyses of HNF1A-MODY Variants Refine the Interpretation of Identified Sequence Variants

CONTEXT

While rare variants of the hepatocyte nuclear factor-1 alpha (HNF1A) gene can cause maturity-onset diabetes of the young (HNF1A-MODY), other variants can be risk factors for the development of type 2 diabetes. As has been suggested by the American College of Medical Genetics (ACMG) guidelines for variant interpretation, functional studies provide strong evidence to classify a variant as pathogenic.

OBJECTIVE

We hypothesized that a functional evaluation can improve the interpretation of the HNF1A variants in our Czech MODY Registry.

DESIGN, SETTINGS, AND PARTICIPANTS

We studied 17 HNF1A variants that were identified in 48 individuals (33 female/15 male) from 20 Czech families with diabetes, using bioinformatics in silico tools and functional protein analyses (transactivation, protein expression, DNA binding, and nuclear localization).

RESULTS

Of the 17 variants, 12 variants (p.Lys120Glu, p.Gln130Glu, p.Arg131Pro, p.Leu139Pro, p.Met154Ile, p.Gln170Ter, p.Glu187SerfsTer40, p.Phe215SerfsTer18, p.Gly253Arg, p.Leu383ArgfsTer3, p.Gly437Val, and p.Thr563HisfsTer85) exhibited significantly reduced transcriptional activity or DNA binding (< 40%) and were classified as (likely) pathogenic, 2/17 variants were (likely) benign and 3/17 remained of uncertain significance. Functional analyses allowed for the reclassification of 10/17 variants (59%). Diabetes treatment was improved in 20/29 (69%) carriers of (likely) pathogenic HNF1A variants.

CONCLUSION

Functional evaluation of the HNF1A variants is necessary to better predict the pathogenic effects and to improve the diagnostic interpretation and treatment, particularly in cases where the cosegregation or family history data are not available or where the phenotype is more diverse and overlaps with other types of diabetes.

Novel insights into genetics and clinics of the HNF1A-MODY

MODY (Maturity Onset Diabetes of the Young) is a type of diabetes resulting from a pathogenic effect of gene mutations. Up to date, 13 MODY genes are known. Gene HNF1A is one of the most common causes of MODY diabetes (HNF1A-MODY; MODY3). This gene is polymorphic and more than 1200 pathogenic and non-pathogenic HNF1A variants were described in its UTRs, exons and introns. For HNF1A-MODY, not just gene but also phenotype heterogeneity is typical. Although there are some clinical instructions, HNF1A-MODY patients often do not meet every diagnostic criteria or they are still misdiagnosed as type 1 and type 2 diabetics. There is a constant effort to find suitable biomarkers to help with in distinguishing of MODY3 from Type 1 Diabetes (T1D) and Type 2 Diabetes (T2D). DNA sequencing is still necessary for unambiguous confirmation of clinical suspicion of MODY. NGS (Next Generation Sequencing) methods brought discoveries of multiple new gene variants and new instructions for their pathogenicity classification were required. The most actual problem is classification of variants with uncertain significance (VUS) which is a stumbling-block for clinical interpretation. Since MODY is a hereditary disease, DNA analysis of family members is helpful or even crucial. This review is updated summary about HNF1A-MODY genetics, pathophysiology, clinics functional studies and variant classification.

Comprehensive in silico screening and molecular dynamics studies of missense mutations in Sjogren-Larsson syndrome associated with the ALDH3A2 gene

Sjögren-Larsson syndrome (SLS) is an autoimmune disorder inherited in an autosomal recessive pattern. To date, 80 missense mutations have been identified in association with the Aldehyde Dehydrogenase 3 Family Member A2 (ALDH3A2) gene causing SLS. Disruption of the function of ALDH3A2 leads to excessive accumulation of fat in the cells, which interferes with the normal function of protective membranes or materials that are necessary for the body to function normally. We retrieved 54 missense mutations in the ALDH3A2 from the OMIM, UniProt, dbSNP, and HGMD databases that are known to cause SLS. These mutations were examined with various in silico stability tools, which predicted that the mutations p.S308N and p.R423H that are located at the protein-protein interaction domains are the most destabilizing. Furthermore, to determine the atomistic-level differences within the protein-protein interactions owing to mutations, we performed macromolecular simulation (MMS) using GROMACS to validate the motion patterns and dynamic behavior of the biological system. We found that both mutations (p.S380N and p.R423H) had significant effects on the protein-protein interaction and disrupted the dimeric interactions. The computational pipeline provided in this study helps to elucidate the potential structural and functional differences between the ALDH3A2 native and mutant homodimeric proteins, and will pave the way for drug discovery against specific targets in the SLS patients.

Bioinformatics classification of mutations in patients with Mucopolysaccharidosis IIIA

Mucopolysaccharidosis (MPS) IIIA, also known as Sanfilippo syndrome type A, is a severe, progressive disease that affects the central nervous system (CNS). MPS IIIA is inherited in an autosomal recessive manner and is caused by a deficiency in the lysosomal enzyme sulfamidase, which is required for the degradation of heparan sulfate. The sulfamidase is produced by the N-sulphoglucosamine sulphohydrolase (SGSH) gene. In MPS IIIA patients, the excess of lysosomal storage of heparan sulfate often leads to mental retardation, hyperactive behavior, and connective tissue impairments, which occur due to various known missense mutations in the SGSH, leading to protein dysfunction. In this study, we focused on three mutations (R74C, S66W, and R245H) based on in silico pathogenic, conservation, and stability prediction tool studies. The three mutations were further subjected to molecular dynamic simulation (MDS) analysis using GROMACS simulation software to observe the structural changes they induced, and all the mutants exhibited maximum deviation patterns compared with the native protein. Conformational changes were observed in the mutants based on various geometrical parameters, such as conformational stability, fluctuation, and compactness, followed by hydrogen bonding, physicochemical properties, principal component analysis (PCA), and salt bridge analyses, which further validated the underlying cause of the protein instability. Additionally, secondary structure and surrounding amino acid analyses further confirmed the above results indicating the loss of protein function in the mutants compared with the native protein. The present results reveal the effects of three mutations on the enzymatic activity of sulfamidase, providing a molecular explanation for the cause of the disease. Thus, this study allows for a better understanding of the effect of SGSH mutations through the use of various computational approaches in terms of both structure and functions and provides a platform for the development of therapeutic drugs and potential disease treatments.

Genetic Study of Hepatocyte Nuclear Factor 1 Alpha Variants in Development of Early-Onset Diabetes Type 2 and Maturity-Onset Diabetes of the Young 3 in Iran

Background:

Maturity-onset diabetes of the young (MODY) is a clinically and genetically heterogeneous group of diabetes characterized by noninsulin-dependent, autosomal-dominant disorder with strong familial history, early age of onset, and pancreatic beta-cell dysfunction. Mutations in at least 14 different genes are responsible for various MODY subtypes. Heterozygous mutations in the hepatocyte nuclear factor 1 alpha (HNF1A) gene are responsible for the MODY3 subtype, which is a common subtype of MODY in different studied populations. To date, more than 450 different variants of this gene have been reported as disease causing for MODY3. This study was carried out to evaluate HNF1A mutations in Iranian diabetic families fulfilling MODY criteria.

Materials and Methods:

Polymerase chain reaction and Sanger sequencing were performed. All the ten exons of the HNF1A gene were sequenced in ten families, followed by cosegregation analysis and in silico evaluation. Computational protein modeling was accomplished for the identified mutation.

Results:

MODY3 was confirmed in two large families by detecting a mutation (p.G253E) in coding regions of HNF1A. Compound heterozygous state for two common variants in HNF1A (p.I27 L and p.S487N) was detected in affected members of 5 families, and in one family, a rare benign variant in the coding sequence for Kozak sequence was detected. Two new nonpathogenic variants were found in noncoding regions of HNF1A.

Conclusion:

It seems that HNF1A mutations are a common cause of MODY in Iranian diabetic patients. Identified common variants in heterozygous state can cause diabetes Type II in earlier ages. The role of rare variant rs3455720 is unknown, and more investigation is needed to uncover the function of this variant.

SOD1 in amyotrophic lateral sclerosis development - in silico analysis and molecular dynamics of A4F and A4V variants

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease that is characterized by the selective loss of motor neurons. Approximately 5% to 10% of patients with ALS have a family history of the disease, and approximately 20% of familial amyotrophic lateral sclerosis (fALS) cases are associated with mutations in Cu/Zn superoxide dismutase (SOD1). In this study, we evaluated the structural and functional effects of human A4F and A4V SOD1 protein mutations. We performed an in silico analysis using prediction algorithms of nonsynonymous single-nucleotide polymorphisms (nsSNPs) associated with the fALS development. Our structural conservation results show that the mutations analyzed (A4V and A4F) were in a highly conserved region. Molecular dynamics simulations using the Linux GROMACS package revealed how these mutations affect protein structure, protein stability, and aggregation. These results suggest that there might be an effect on the SOD1 function. Understanding the molecular basis of disease provides new insights useful for rational drug design and advancing our understanding of the ALS development.

Molecular insights of the G2019S substitution in LRRK2 kinase domain associated with Parkinson's disease: A molecular dynamics simulation approach

The G2019S substitution in the Leucine-rich repeat kinase 2 (LRRK2) is significantly associated with Parkinson's disease (PD). This substitution was identified in both familial and sporadic forms of PD with a higher frequency. Few computational studies have reported the impact of G2019S substitution on inhibitors of the kinase domain of LRRK2. However, no computational study deeply investigated the possible impact of the G2019S substitution on the kinase domain in its Apo conformation. Therefore, in this study, we used 200 ns molecular dynamic simulation using the GROMACS 5.1.4 package software to investigate the impact of the G2019S substitution on the structure of the kinase domain of LRRK2. Our results indicate that the G2019S substitution affects the dynamics and stability of LRRK2 by decreasing the flexibility and increasing the compactness of the kinase domain and showing its tendency to be in an active conformation for long time interval because of the high energy barrier between active and inactive conformation. This study predicts the molecular pathogenicity mechanism of the G2019S on patients with PD and provides a potential platform for developing therapeutics for patients with PD that harbor this amino acid substitution.

Understanding the structure-function relationship of HPRT1 missense mutations in association with Lesch-Nyhan disease and HPRT1-related gout by in silico mutational analysis

The nucleotide salvage pathway is used to recycle degraded nucleotides (purines and pyrimidines); one of the enzymes that helps to recycle purines is hypoxanthine guanine phosphoribosyl transferase 1 (HGPRT1). Therefore, defects in this enzyme lead to the accumulation of DNA and nucleotide lesions and hence replication errors and genetic disorders. Missense mutations in hypoxanthine phosphoribosyl transferase 1 (HPRT1) are associated with deficiencies such as Lesch-Nyhan disease and chronic gout, which have manifestations such as arthritis, neurodegeneration, and cognitive disorders. In the present study, we collected 88 non-synonymous single nucleotide polymorphisms (nsSNPs) from the UniProt, dbSNP, ExAC, and ClinVar databases. We used a series of sequence-based and structure-based in silico tools to prioritize and characterize the most pathogenic and stabilizing or destabilizing nsSNPs. Moreover, to obtain the structural impact of the pathogenic mutations, we mapped the mutations to the crystal structure of the HPRT protein. We further subjected these mutant proteins to a 50 ns molecular dynamics simulation (MDS). The MDS trajectory showed that all mutant proteins altered the structural conformation and dynamic behavior of the HPRT protein and corroborated its association with LND and gout. This study provides essential information regarding the use of HPRT protein mutants as potential targets for therapeutic development.

In Silico Analysis of Coding/Noncoding SNPs of Human RETN Gene and Characterization of Their Impact on Resistin Stability and Structure

Resistin (RETN) is a gene coding for proinflammatory adipokine called resistin secreted by macrophages in humans. Single nucleotide polymorphisms (SNPs) in RETN are linked to obesity and insulin resistance in various populations. Using dbSNP, 78 nonsynonymous SNPs (nsSNPs) were retrieved and tested on a PredictSNP 1.0 megaserver. Among these, 15 nsSNPs were predicted as highly deleterious and thus subjected to further analyses, such as conservation, posttranscriptional modifications, and stability. The 3D structure of human resistin was generated by homology modeling using Swiss model. Root-mean-square deviation (RMSD), hydrogen bonds (h-bonds), and interactions were estimated. Furthermore, UTRscan served to identify UTR functional SNPs. Among the 15 most deleterious nsSNPs, 13 were predicted to be highly conserved including variants in posttranslational modification sites. Stability analysis predicted 9 nsSNPs (I32S, C51Y, G58E, G58R, C78S, G79C, W98C, C103G, and C104Y) which can decrease protein stability with at least three out of the four algorithms used in this study. These nsSNPs were chosen for structural analysis. Both variants C51Y and C104Y showed the highest RMS deviations (1.137 Å and 1.308 Å, respectively) which were confirmed by the important decrease in total h-bonds. The analysis of hydrophobic and hydrophilic interactions showed important differences between the native protein and the 9 mutants, particularly I32S, G79C, and C104Y. Six SNPs in the 3'UTR (rs920569876, rs74176247, rs1447199134, rs943234785, rs76346269, and rs78048640) were predicted to be implicated in polyadenylation signal. This study revealed 9 highly deleterious SNPs located in the human RETN gene coding region and 6 SNPs within the 3'UTR that may alter the protein structure. Interestingly, these SNPs are worth to be analyzed in functional studies to further elucidate their effect on metabolic phenotype occurrence.

Novel Mechanisms for IGF-I Regulation by Glucagon in Carp Hepatocytes: Up-Regulation of HNF1α and CREB Expression via Signaling Crosstalk for IGF-I Gene Transcription

Glucagon, a key hormone for glucose homeostasis, can exert functional crosstalk with somatotropic axis via modification of IGF-I expression. However, its effect on IGF-I regulation is highly variable in different studies and the mechanisms involved are largely unknown. Using grass carp as a model, the signal transduction and transcriptional mechanisms for IGF-I regulation by glucagon were examined in Cyprinid species. As a first step, the carp HNF1α, a liver-enriched transcription factor, was cloned and confirmed to be a single-copy gene expressed in the liver. In grass carp hepatocytes, glucagon treatment could elevate IGF-I, HNF1α, and CREB mRNA levels, induce CREB phosphorylation, and up-regulate HNF1α and CREB protein expression. The effects on IGF-I, HNF1α, and CREB gene expression were mediated by cAMP/PKA and PLC/IP₃/PKC pathways with differential coupling with the MAPK and PI3K/Akt cascades. During the process, protein:protein interaction between HNF1α and CREB and recruitment of RNA Pol-II to IGF-I promoter also occurred with a rise in IGF-I primary transcript level. In parallel study to examine grass carp IGF-I promoter activity expressed in αT3 cells, similar pathways for post-receptor signaling were also confirmed in glucagon-induced IGF-I promoter activation and the trans-activating effect by glucagon was mediated by the binding sites for HNF1α and CREB located in the proximal region of IGF-I promoter. Our findings, as a whole, shed light on a previously undescribed mechanism for glucagon-induced IGF-I gene expression by increasing HNF1α and CREB production via functional crosstalk of post-receptor signaling. Probably, by protein:protein interaction between the two transcription factors and subsequent transactivation via their respective cis-acting elements in the IGF-I promoter, IGF-I gene transcription can be initiated by glucagon at the hepatic level.

Computational modelling approaches as a potential platform to understand the molecular genetics association between Parkinson's and Gaucher diseases

Gaucher's disease (GD) is a genetic disorder in which glucocerebroside accumulates in cells and specific organs. It is broadly classified into type I, type II and type III. Patients with GD are at high risk of Parkinson's disease (PD), and the clinical and pathological presentation of GD patients with PD is almost identical to idiopathic PD. Several experimental models like cell culture, animal models, and transgenic mice models were used to understand the molecular mechanism behind GD and PD association; however, such mechanism remains unclear. In this context, based on literature reports, we identified the most common mutations K198T, E326K, T369M, N370S, V394L, D409H, L444P, and R496H, in the Glucosylceramidase (GBA) protein that are known to cause GD1, and represent a risk of developing PD. However, to date, no computational analyses have designed to elucidate the potential functional role of GD mutations with increased risk of PD. The present computational pipeline allows us to understand the structural and functional significance of these GBA mutations with PD. Based on the published data, the most common and severe mutations were E326K, N370S, and L444P, which further selected for our computational analysis. PredictSNP and iStable servers predicted L444P mutant to be the most deleterious and responsible for the protein destabilization, followed by the N370S mutation. Further, we used the structural analysis and molecular dynamics approach to compare the most frequent deleterious mutations (N370S and L444P) with the mild mutation E326K. The structural analysis demonstrated that the location of E326K and N370S in the alpha helix region of the protein whereas the mutant L444P was in the starting region of the beta sheet, which might explain the predicted pathogenicity level and destabilization effect of the L444P mutant. Finally, Molecular Dynamics (MD) at 50 ns showed the highest deviation and fluctuation pattern in the L444P mutant compared to the two mutants E326K and N370S and the native protein. This was consistent with more loss of intramolecular hydrogen bonds and less compaction of the radius of gyration in the L444P mutant. The proposed study is anticipated to serve as a potential platform to understand the mechanism of the association between GD and PD, and might facilitate the process of drug discovery against both GD and PD.

Impact of missense mutations in survival motor neuron protein (SMN1) leading to Spinal Muscular Atrophy (SMA): A computational approach

Spinal muscular atrophy (SMA) is a neuromuscular disorder caused by the mutations in survival motor neuron 1 gene (SMN1). The molecular pathology of missense mutations in SMN1 is not thoroughly investigated so far. Therefore, we collected all missense mutations in the SMN1 protein, using all possible search terms, from three databases (PubMed, PMC and Google Scholar). All missense mutations were subjected to in silico pathogenicity, conservation, and stability analysis tools. We used statistical analysis as a QC measure for validating the specificity and accuracy of these tools. PolyPhen-2 demonstrated the highest specificity and accuracy. While PolyPhen-1 showed the highest sensitivity; overall, PolyPhen2 showed better measures in comparison to other in silico tools. Three mutations (D44V, Y272C, and Y277C) were identified as the most pathogenic and destabilizing. Further, we compared the physiochemical properties of the native and the mutant amino acids and observed loss of H-bonds and aromatic stacking upon the cysteine to tyrosine substitution, which led to the loss of aromatic rings and may reduce protein stability. The three mutations were further subjected to Molecular Dynamics Simulation (MDS) analysis using GROMACS to understand the structural changes. The Y272C and Y277C mutants exhibited maximum deviation pattern from the native protein as compared to D44V mutant. Further MDS analysis predicted changes in the stability that may have been contributed due to the loss of hydrogen bonds as observed in intramolecular hydrogen bond analysis and physiochemical analysis. A loss of function/structural impact was found to be severe in the case of Y272C and Y277C mutants in comparison to D44V mutation. Correlating the results from in silico predictions, physiochemical analysis, and MDS, we were able to observe a loss of stability in all the three mutants. This combinatorial approach could serve as a platform for variant interpretation and drug design for spinal muscular dystrophy resulting from missense mutations.

Computational approach to unravel the impact of missense mutations of proteins (D2HGDH and IDH2) causing D-2-hydroxyglutaric aciduria 2

The 2-hydroxyglutaric aciduria (2-HGA) is a rare neurometabolic disorder that leads to the development of brain damage. It is classified into three categories: D-2-HGA, L-2-HGA, and combined D,L-2-HGA. The D-2-HGA includes two subtypes: type I and type II caused by the mutations in D2HGDH and IDH2 proteins, respectively. In this study, we studied six mutations, four in the D2HGDH (I147S, D375Y, N439D, and V444A) and two in the IDH2 proteins (R140G, R140Q). We performed in silico analysis to investigate the pathogenicity and stability changes of the mutant proteins using pathogenicity (PANTHER, PhD-SNP, SIFT, SNAP, and META-SNP) and stability (i-Mutant, MUpro, and iStable) predictors. All the mutations of both D2HGDH and IDH2 proteins were predicted as disease causing except V444A, which was predicted as neutral by SIFT. All the mutants were also predicted to be destabilizing the protein except the mutants D375Y and N439D. DSSP plugin of the PyMOL and Molecular Dynamics Simulations (MDS) were used to study the structural changes in the mutant proteins. In the case of D2HGDH protein, the mutations I147S and V444A that are positioned in the beta sheet region exhibited higher Root Mean Square Deviation (RMSD), decrease in compactness and number of intramolecular hydrogen bonds compared to the mutations N439D and D375Y that are positioned in the turn and loop region, respectively. While the mutants R140Q and R140QG that are positioned in the alpha helix region of the protein. MDS results revealed the mutation R140Q to be more destabilizing (higher RMSD values, decrease in compactness and number of intramolecular hydrogen bonds) compared to the mutation R140G of the IDH2 protein. This study is expected to serve as a platform for drug development against 2-HGA and pave the way for more accurate variant assessment and classification for patients with genetic diseases.

Structural analysis of missense mutations in galactokinase 1 (GALK1) leading to galactosemia type-2

Galactosemia type 2 is an autosomal recessive disorder characterized by the deficiency of galactokinase (GALK) enzyme due to missense mutations in GALK1 gene, which is associated with various manifestations such as hyper galactosemia and formation of cataracts. GALK enzyme catalyzes the adenosine triphosphate (ATP)-dependent phosphorylation of α-d-galactose to galactose-1-phosphate. We searched 4 different literature databases (Google Scholar, PubMed, PubMed Central, and Science Direct) and 3 gene-variant databases (Online Mendelian Inheritance in Man, Human Gene Mutation Database, and UniProt) to collect all the reported missense mutations associated with GALK deficiency. Our search strategy yielded 32 missense mutations. We used several computational tools (pathogenicity and stability, biophysical characterization, and physiochemical analyses) to prioritize the most significant mutations for further analyses. On the basis of the pathogenicity and stability predictions, 3 mutations (P28T, A198V, and L139P) were chosen to be tested further for physicochemical characterization, molecular docking, and simulation analyses. Molecular docking analysis revealed a decrease in interaction between the protein and ATP in all the 3 mutations, and molecular dynamic simulations of 50 ns showed a loss of stability and compactness in the mutant proteins. As the next step, comparative physicochemical changes of the native and the mutant proteins were carried out using essential dynamics. Overall, P28T and A198V were predicted to alter the structure and function of GALK protein when compared to the mutant L139P. This study demonstrates the power of computational analysis in variant classification and interpretation and provides a platform for developing targeted therapeutics.

A profound computational study to prioritize the disease-causing mutations in PRPS1 gene

Charcot-Marie-Tooth disease (CMT) is one of the most commonly inherited congenital neurological disorders, affecting approximately 1 in 2500 in the US. About 80 genes were found to be in association with CMT. The phosphoribosyl pyrophosphate synthetase 1 (PRPS1) is an essential enzyme in the primary stage of de novo and salvage nucleotide synthesis. The mutations in the PRPS1 gene leads to X-linked Charcot-Marie-Tooth neuropathy type 5 (CMTX5), PRS super activity, Arts syndrome, X-linked deafness-1, breast cancer, and colorectal cancer. In the present study, we obtained 20 missense mutations from UniProt and dbSNP databases and applied series of comprehensive in silico prediction methods to assess the degree of pathogenicity and stability. In silico tools predicted four missense mutations (D52H, M115 T, L152P, and D203H) to be potential disease causing mutations. We further subjected the four mutations along with native protein to 50 ns molecular dynamics simulation (MDS) using Gromacs package. The resulting trajectory files were analyzed to understand the stability differences caused by the mutations. We used the Root Mean Square Deviation (RMSD), Radius of Gyration (Rg), solvent accessibility surface area (SASA), Covariance matrix, Principal Component Analysis (PCA), Free Energy Landscape (FEL), and secondary structure analysis to assess the structural changes in the protein upon mutation. Our study suggests that the four mutations might affect the PRPS1 protein function and stability of the structure. The proposed study may serve as a platform for drug repositioning and personalized medicine for diseases that are caused by the PRPS1 deficiency.

Genotype-phenotype correlation in patients with isovaleric acidaemia: comparative structural modelling and computational analysis of novel variants

Isovaleric acidaemia (IVA) is an autosomal recessive inborn error of leucine metabolism. It is caused by a deficiency in the mitochondrial isovaleryl-CoA dehydrogenase (IVD) enzyme. In this study, we investigated eight patients with IVA. The patients' diagnoses were confirmed by urinary organic acid analysis and the blood C5-Carnitine value. A molecular genetic analysis of the IVD gene revealed nine different variants: five were missense variants (c.1193G > A; p. R398Q, c.1207T > A; p. Y403N, c.872C > T; p. A291V, c.749G > C; p. G250A, c.1136T > C; p.I379T), one was a frameshift variant (c.ins386 T; p. Y129fs), one was a splicing variant (c.465 + 2T > C), one was a polymorphism (c.732C > T; p. D244D), and one was an intronic benign variant (c.287 + 14T > C). Interestingly, all variants were in homozygous form, and four variants were novel (p. Y403N, p. Y129fs, p. A291V, p. G250A) and absent from 200 normal chromosomes. We performed protein modelling and dynamics analyses, pathogenicity and stability analyses, and a physiochemical properties analysis of the five missense variants (p.Y403N, R398Q, p.A291V, p.G250A, and p.I379T). Variants p.I379T and p.R398Q were found to be the most deleterious and destabilizing compared to variants p.A291V and p.Y403N. However, the four variants were predicted to be severe by the protein dynamic and in silico analysis, which was consistent with the patients' clinical phenotypes. The p.G250A variant was computationally predicted as mild, which was consistent with the severity of the clinical phenotype. This study reveals a potentially meaningful genotype-phenotype correlation for our patient cohort and highlights the development and use of this computational analysis for future assessments of genetic variants in the clinic.

Comparative computational assessment of the pathogenicity of mutations in the Aspartoacylase enzyme

Aspartoacylase (ASPA) is a zinc-dependent abundant enzyme in the brain, which catalyzes the conversion of N-acetyl aspartate (NAA) into acetate and aspartate. Mutations in the ASPA gene are associated with the development of Canavan disease (CD), leading to the deficiency of ASPA activity. Patients with CD were characterized by degeneration of the white matter of the brain. We reported earlier on two patients with severe form of CD that both had two novel missense mutations in the ASPA: c.427 A > G; p. I143V and c.557 T > A; p. V186D (Zaki et al. 2017a), patient 1 harbored both mutations (p.I143V and p.V186D) in a heterozygous form together with four other mutations, and patient 2 had both mutations in homozygous form. Wijayasinghe et al. (2014) crystallized the 3D structures of four different ASPA mutants (p.K213E, p.Y231C, p.E285A, and p.F295S). In this study, we used in silico prediction methods and molecular dynamics simulation (MDS) to understand the structural impact of all these mutations. Moreover, we used molecular docking (MD) to investigate the binding patterns of the NAA substrate to the native and mutant proteins. Among the mutations, p.E285A (crystallized mutant) was predicted to be the most deleterious for the protein function and the least deleteriousness mutant was the p.I143V (novel mutant). Among the novel mutations, p.V186D was observed to be disruptive for both the zinc binding and NAA binding than the p.I143V. This study provides practical insights on the effect of these mutations on the ASPA function and might serve as a platform for drug design for CD treatment.

Probing the Protein-Protein Interaction Network of Proteins Causing Maturity Onset Diabetes of the Young

Protein-protein interactions (PPIs) play vital roles in various cellular pathways. Most of the proteins perform their responsibilities by interacting with an enormous number of proteins. Understanding these interactions of the proteins and their interacting partners has shed light toward the field of drug discovery. Also, PPIs enable us to understand the functions of a protein by understanding their interacting partners. Consequently, in the current study, PPI network of the proteins causing MODY (Maturity Onset Diabetes of the Young) was drawn, and their correlation in causing a disease condition was marked. MODY is a monogenic type of diabetes caused by autosomal dominant inheritance. Extensive research on transcription factor and their corresponding genetic pathways have been studied over the last three decades, yet, very little is understood about the molecular modalities of highly dynamic interactions between transcription factors, genomic DNA, and the protein partners. The current study also reveals the interacting patterns of the various transcription factors. Consequently, in the current work, we have devised a PPI analysis to understand the plausible pathway through which the protein leads to a deformity in glucose uptake.

An Integrated Computational Framework to Assess the Mutational Landscape of α-L-Iduronidase IDUA Gene

Mucopolysaccharidosis type I is a lysosomal genetic disorder caused due to the deficiency of the α-L-iduronidase enzyme (IDUA). Mutations associated with IDUA lead to mild to severe forms of diseases characterized by different clinical features. In the present study, we first performed a comprehensive analysis using various in silico prediction tools to screen and prioritize the missense mutations or nonsynonymous SNPs (nsSNPs) associated with IDUA. Subsequently, statistical analysis was empowered to examine the predictive ability and accuracy of the in silico prediction tool results supporting the disease phenotype ranging from mild to severe. Till date, no study has been carried out in IDUA in analyzing the impact of the nsSNPs at the structural level. In this context with the aid of pathogenic and stability prediction in silico tools, we identified nsSNPs R89Q, R89W, and P533R to be most deleterious and disease-causing having impact on the function of the protein. Extensive molecular dynamics analysis was performed using Gromacs to understand the deleterious nature of the mutants. Variations observed between the trajectory files of native and mutants R89Q, R89W, and P533R using Gromacs utilities enabled us to measure the adverse effects on the protein and could be the underlying reasons for the disease pathogenesis. These findings may be helpful in understanding the genotype-phenotype relationship and molecular basis of the disease to design drugs for better treatment. J. Cell. Biochem. 119: 555-565, 2018. © 2017 Wiley Periodicals, Inc.