Expression analysis and mapping of Viral-Host Protein interactions of Poxviridae suggests a lead candidate molecule targeting Mpox.

BACKGROUND: Monkeypox (Mpox) is an important human pathogen without etiological treatment. A viral-host interactome study may advance our understanding of molecular pathogenesis and lead to the discovery of suitable therapeutic targets. METHODS: GEO Expression datasets characterizing mRNA profile changes in different host responses to poxviruses were analyzed for shared pathway identification, and then, the Protein-protein interaction (PPI) maps were built. The viral gene expression datasets of Monkeypox virus (MPXV) and Vaccinia virus (VACV) were used to identify the significant viral genes and further investigated for their binding to the library of targeting molecules. RESULTS: Infection with MPXV interferes with various cellular pathways, including interleukin and MAPK signaling. While most host differentially expressed genes (DEGs) are predominantly downregulated upon infection, marked enrichments in histone modifiers and immune-related genes were observed. PPI analysis revealed a set of novel virus-specific protein interactions for the genes in the above functional clusters. The viral DEGs exhibited variable expression patterns in three studied cell types: primary human monocytes, primary human fibroblast, and HeLa, resulting in 118 commonly deregulated proteins. Poxvirus proteins C6R derived protein K7 and K7R of MPXV and VACV were prioritized as targets for potential therapeutic interventions based on their histone-regulating and immunosuppressive properties. In the computational docking and Molecular Dynamics (MD) experiments, these proteins were shown to bind the candidate small molecule S3I-201, which was further prioritized for lead development. RESULTS: MPXV circumvents cellular antiviral defenses by engaging histone modification and immune evasion strategies. C6R-derived protein K7 binding candidate molecule S3I-201 is a priority promising candidate for treating Mpox.

Genomic insights and advanced machine learning: characterizing autism spectrum disorder biomarkers and genetic interactions.

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by altered brain connectivity and function. In this study, we employed advanced bioinformatics and explainable AI to analyze gene expression associated with ASD, using data from five GEO datasets. Among 351 neurotypical controls and 358 individuals with autism, we identified 3,339 Differentially Expressed Genes (DEGs) with an adjusted p-value (≤ 0.05). A subsequent meta-analysis pinpointed 342 DEGs (adjusted p-value ≤ 0.001), including 19 upregulated and 10 down-regulated genes across all datasets. Shared genes, pathogenic single nucleotide polymorphisms (SNPs), chromosomal positions, and their impact on biological pathways were examined. We identified potential biomarkers (HOXB3, NR2F2, MAPK8IP3, PIGT, SEMA4D, and SSH1) through text mining, meriting further investigation. Additionally, we shed light on the roles of RPS4Y1 and KDM5D genes in neurogenesis and neurodevelopment. Our analysis detected 1,286 SNPs linked to ASD-related conditions, of which 14 high-risk SNPs were located on chromosomes 10 and X. We highlighted potential missense SNPs associated with FGFR inhibitors, suggesting that it may serve as a promising biomarker for responsiveness to targeted therapies. Our explainable AI model identified the MID2 gene as a potential ASD biomarker. This research unveils vital genes and potential biomarkers, providing a foundation for novel gene discovery in complex diseases.

The spectrum of chromosomal translocations in the Arab world: ethnic-specific chromosomal translocations and their relevance to diseases.

Chromosomal translocations (CTs) are the most common type of structural chromosomal abnormalities in humans. CTs have been reported in several studies in the Arab world, but the frequency and spectrum of these translocations are not well characterized. The aim of this study is to conduct a systematic review to estimate the frequency and spectrum of CTs in the 22 Arab countries. Four literature databases were searched: PubMed, Science Direct, Scopus, and Web of Science, from the time of inception until July 2021. A combination of broad search terms was used to collect all possible CTs reported in the Arab world. In addition to the literature databases, all captured CTs were searched in three chromosomal rearrangement databases (Mitelman Database, CytoD 1.0 Database, and the Atlas of Genetics and Cytogenetics in Oncology and Hematology), along with PubMed and Google Scholar, to check whether the CTs are unique to the Arabs or shared between Arabs and non-Arabs. A total of 9,053 titles and abstracts were screened, of which 168 studies met our inclusion criteria, and 378 CTs were identified in 15 Arab countries, of which 57 CTs were unique to Arab patients. Approximately 89% of the identified CTs involved autosomal chromosomes. Three CTs, t(9;22), t(13;14), and t(14;18), showed the highest frequency, which were associated with hematological malignancies, recurrent pregnancy loss, and follicular lymphoma, respectively. Complex CTs were commonly reported among Arabs, with a total of 44 CTs, of which 12 were unique to Arabs. This is the first study to focus on the spectrum of CTs in the Arab world and compressively map the ethnic-specific CTs relevant to cancer. It seems that there is a distinctive genotype of Arabs with CTs, of which some manifested with unique clinical phenotypes. Although ethnic-specific CTs are highly relevant to disease mechanism, they are understudied and need to be thoroughly addressed.

Therapeutic and diagnostic applications of exosomal circRNAs in breast cancer.

Circular RNAs (circRNAs) are regulatory elements that are involved in orchestrating gene expression and protein functions and are implicated in various biological processes including cancer. Notably, breast cancer has a significant mortality rate and is one of the most common malignancies in women. CircRNAs have been demonstrated to contribute to the pathogenesis of breast cancer including its initiation, progression, metastasis, and resistance to drugs. By acting as miRNA sponges, circRNAs can indirectly influence gene expression by disrupting miRNA regulation of their target genes, ultimately altering the course of cancer development and progression. Additionally, circRNAs can interact with proteins and modulate their functions including signaling pathways involved in the initiation and development of cancer. Recently, circRNAs can encode peptides that play a role in the pathophysiology of breast cancer and other diseases and their potential as diagnostic biomarkers and therapeutic targets for various cancers including breast cancer. CircRNAs possess biomarkers that differentiate, such as stability, specificity, and sensitivity, and can be detected in several biological specimens such as blood, saliva, and urine. Moreover, circRNAs play an important role in various cellular processes including cell proliferation, differentiation, and apoptosis, all of which are integral factors in the development and progression of cancer. This review synthesizes the functions of circRNAs in breast cancer, scrutinizing their contributions to the onset and evolution of the disease through their interactions with exosomes and cancer-related intracellular pathways. It also delves into the potential use of circRNA as a biomarker and therapeutic target against breast cancer. It discusses various databases and online tools that offer crucial circRNA information and regulatory networks. Lastly, the challenges and prospects of utilizing circRNAs in clinical settings associated with breast cancer are explored.

Bioinformatics investigation on blood-based gene expressions of Alzheimer's disease revealed ORAI2 gene biomarker susceptibility: An explainable artificial intelligence-based approach.

The progressive, chronic nature of Alzheimer's disease (AD), a form of dementia, defaces the adulthood of elderly individuals. The pathogenesis of the condition is primarily unascertained, turning the treatment efficacy more arduous. Therefore, understanding the genetic etiology of AD is essential to identifying targeted therapeutics. This study aimed to use machine-learning techniques of expressed genes in patients with AD to identify potential biomarkers that can be used for future therapy. The dataset is accessed from the Gene Expression Omnibus (GEO) database (Accession Number: GSE36980). The subgroups (AD blood samples from frontal, hippocampal, and temporal regions) are individually investigated against non-AD models. Prioritized gene cluster analyses are conducted with the STRING database. The candidate gene biomarkers were trained with various supervised machine-learning (ML) classification algorithms. The interpretation of the model prediction is perpetrated with explainable artificial intelligence (AI) techniques. This experiment revealed 34, 60, and 28 genes as target biomarkers of AD mapped from the frontal, hippocampal, and temporal regions. It is identified ORAI2 as a shared biomarker in all three areas strongly associated with AD's progression. The pathway analysis showed that STIM1 and TRPC3 are strongly associated with ORAI2. We found three hub genes, TPI1, STIM1, and TRPC3, in the network of the ORAI2 gene that might be involved in the molecular pathogenesis of AD. Naive Bayes classified the samples of different groups by fivefold cross-validation with 100% accuracy. AI and ML are promising tools in identifying disease-associated genes that will advance the field of targeted therapeutics against genetic diseases.

Exome sequence analysis of rare frequency variants in Late-Onset Alzheimer Disease.

Alzheimer disease (AD) is a leading cause of dementia in elderly patients who continue to live between 3 and 11 years of diagnosis. A steep rise in AD incidents is observed in the elderly population in East-Asian countries. The disease progresses through several changes, including memory loss, behavioural issues, and cognitive impairment. The etiology of AD is hard to determine because of its complex nature. The whole exome sequences of late-onset AD (LOAD) patients of Korean origin are investigated to identify rare genetic variants that may influence the complex disorder. Computational annotation was performed to assess the function of candidate variants in LOAD. The in silico pathogenicity prediction tools such as SIFT, Polyphen-2, Mutation Taster, CADD, LRT, PROVEAN, DANN, VEST3, fathmm-MKL, GERP + + , SiPhy, phastCons, and phyloP identified around 17 genes harbouring deleterious variants. The variants in the ALDH3A2 and RAD54B genes were pathogenic, while in 15 other genes were predicted to be variants of unknown significance. These variants can be potential risk candidates contributing to AD. In silico computational techniques such as molecular docking, molecular dynamic simulation and steered molecular dynamics were carried out to understand the structural insights of RAD54B with ATP. The simulation of mutant (T459N) RAD54B with ATP revealed reduced binding strength of ATP at its binding site. In addition, lower binding free energy was observed when compared to the wild-type RAD54B. Our study shows that the identified uncommon variants are linked to AD and could be probable predisposing genetic factors of LOAD.

Genetic epidemiology of male infertility (MI) in Arabs: a systematic review.

Although Male Infertility (MI) in Arabs is fairly common, there is a dearth in published reports of genetic epidemiology of MI among Arabs. This study aimed to review the existing literature reporting the variants that are associated with MI in the 22 Arab countries. We searched four literature databases (PubMed, Science Direct, Scopus, and Web of Science) from the time of inception until April 2021 using broad search terms to capture all reported genetic data related to Arab patients with MI. Our search strategy identified 3488 articles, of these 34 were eligible for this systemic review. We retrieved data from nine Arab Countries (Tunisia, Algeria, Morocco, Syria, Jordan, Yemen, Iraq, Egypt and Lebanon). Only 2597 patients and 10 families with MI were identified and compared to 3721 controls. Our search strategy identified 25 genes, including 89 variants: 52.7% are shared with other ethnic groups, 41.7% are unique to Arab patients, and 5.6% are common among Arabs. Azoospermia (41.18%) was the most frequently reported phenotype. This is the first systematic review to capture reported variants associated with MI among the Arab populations. Although Arabs seem to share genetic profiles with other ethnicities, they have distinctive genotype-phenotype correlations for some of genetic variants.

Comparison of potential inhibitors and targeting fat mass and obesity-associated protein causing diabesity through docking and molecular dynamics strategies.

Genome-wide association studies (GWAS) have identified an association between polymorphisms in the FTO gene and obesity. The FTO: rs9939609, an intronic variant, is considered a risk allele for developing diabesity in homozygous and heterozygous forms. This study aimed to investigate the molecular structure of the available inhibitors specific to the FTO mutations along with the rs9939609 variant. We identified the best-suited inhibitor molecules for each mutant type containing the rs9939609 risk allele. Missense mutations unique to obesity and containing the risk allele of rs9939609 were retrieved from dbSNP for this study. Further stability testing for the mutations were carried out using DynaMut and iStable tools. Three mutations (G187A, M223V, and I492V) were highly destabilizing the FTO structure. These three mutants and native FTO were docked with each of the nine-inhibitor molecules collected from literature studies with the help of PyRx and AutoDock. Further structural behavior of the mutants and native FTO were identified with molecular dynamics simulations and MM-PBSA analyses, along with the 19complex inhibitor compound. We found the compound 19complex exhibited better binding interactions and is the top candidate inhibitor for the M223V and I492V mutants. This study provided insights into the structural changes caused due to mutations in FTO, and the binding mechanism of the inhibitor molecules. It could aid in developing antiobesity drugs for treating patients with mutations and risk alleles predisposing to obesity.

Genetic polymorphisms associated with obesity in the Arab world: a systematic review.

BACKGROUND: Obesity, one of the most common chronic health conditions worldwide, is a multifactorial disease caused by complex genetic and environmental interactions. Several association studies have revealed a considerable number of candidate loci for obesity; however, the genotype-phenotype correlations remain unclear. To date, no comprehensive systematic review has been conducted to investigate the genetic risk factors for obesity among Arabs. OBJECTIVES: This study aimed to systematically review the genetic polymorphisms that are significantly associated with obesity in Arabs. METHODS: We searched four literature databases (PubMed, Science Direct, Scopus, and Google Scholar) from inception until May 2020 to obtain all reported genetic data related to obesity in Arab populations. Quality assessment and data extraction were performed individually by three investigators. RESULTS: In total, 59 studies comprising a total of 15,488 cases and 9,760 controls were included in the systematic review. A total of 76 variants located within or near 49 genes were reported to be significantly associated with obesity. Among the 76 variants, two were described as unique to Arabs, as they have not been previously reported in other populations, and 19 were reported to be distinctively associated with obesity in Arabs but not in non-Arab populations. CONCLUSIONS: There appears to be a unique genetic and clinical susceptibility profile of obesity in Arab patients.

Genetic Variants Associated With Alzheimer Disease in the 22 Arab Countries: A Systematic Review.

BACKGROUND AND AIMS: Alzheimer disease (AD) is a progressive and complex neurodegenerative disease. Approximately 70% of AD risk is attributed to genetic risk factors, including variants in amyloid precursor protein (APP), presenilin 1 (PSEN1), and presenilin 2 (PSEN2) genes. Several studies have revealed a considerable number of candidate loci and genes for AD among different ethnic populations. However, the outcomes of these studies have been inconsistent. In this study, we aimed to investigate the spectrum of variants that are associated with the onset and development of AD among 22 Arab countries. METHODOLOGY: We systematically searched 4 literature databases (Science Direct, Scopus, PubMed, and Web of Science) from the date of inception until July 2020 using various search terms to obtain all the reported genetic data on Arab AD cases. RESULTS: In total, 18 studies were included, comprising a total of 2173 individuals, of whom 888 were clinically diagnosed AD patients and were genetically tested for genes and variants associated with AD. A total of 27 variants in 8 genes were found to be associated with AD. Of these variants, 17 were unique to the Arab population and 10 were shared with other ethnic groups. CONCLUSIONS: There is a dearth of studies on the genetics of AD in the Arab world. There seems to be distinctive genetic and clinical susceptibility profiles for Arab patients with AD.

Role of non-coding RNA networks in leukemia progression, metastasis and drug resistance.

Early-stage detection of leukemia is a critical determinant for successful treatment of the disease and can increase the survival rate of leukemia patients. The factors limiting the current screening approaches to leukemia include low sensitivity and specificity, high costs, and a low participation rate. An approach based on novel and innovative biomarkers with high accuracy from peripheral blood offers a comfortable and appealing alternative to patients, potentially leading to a higher participation rate.Recently, non-coding RNAs due to their involvement in vital oncogenic processes such as differentiation, proliferation, migration, angiogenesis and apoptosis have attracted much attention as potential diagnostic and prognostic biomarkers in leukemia. Emerging lines of evidence have shown that the mutational spectrum and dysregulated expression of non-coding RNA genes are closely associated with the development and progression of various cancers, including leukemia. In this review, we highlight the expression and functional roles of different types of non-coding RNAs in leukemia and discuss their potential clinical applications as diagnostic or prognostic biomarkers and therapeutic targets.

CD44 mediates stem cell mobilization to damaged lung via its novel transcriptional targets, Cortactin and Survivin.

Beyond their role in bone and lung homeostasis, mesenchymal stem cells (MSCs) are becoming popular in cell therapy. Various insults may disrupt the repair mechanisms involving MSCs. One such insult is smoking, which is a major risk factor for osteoporosis and respiratory diseases. Upon cigarette smoke-induced damage, a series of reparatory mechanisms ensue; one such mechanism involves Glycosaminoglycans (GAG). One of these GAGs, namely hyaluronic acid (HA), serves as a potential therapeutic target in lung injury. However, much of its mechanisms of action through its major receptor CD44 remains unexplored. Our previous studies have identified and functionally validated that both cortactin (CTTN: marker of motility) and Survivin (BIRC5: required for cell survival) act as novel HA/CD44-downstream transcriptional targets underpinning cell motility. Here, human MSCs were treated with "Water-pipe" smoke to investigate the effects of cigarette smoke condensate (CSC) on these HA-CD44 novel signaling pathways. Our results show that CSC decreased the expression of both CD44 and its downstream targets CTTN and BIRC5 in MSCs, and that HA reversed these effects. Interestingly, CSC inhibited migration and invasion of MSCs upon CD44-targeted RNAi treatment. This shows the importance of CD44-HA/CTTN and CD44-HA/BIRC5 signaling pathways in MSC motility, and further suggests that these signaling pathways may provide a novel mechanism implicated in migration of MSCs during repair of lung tissue injury. These findings suggest that one should use caution before utilizing MSC from donors with history of smoking, and further pave the way towards the development of targeted therapeutic approaches against CD44-associated diseases.

Novel Comprehensive Bioinformatics Approaches to Determine the Molecular Genetic Susceptibility Profile of Moderate and Severe Asthma.

BACKGROUND: Asthma is a chronic inflammatory condition linked to hyperresponsiveness in the airways. There is currently no cure available for asthma, and therapy choices are limited. Asthma is the result of the interplay between genes and the environment. The exact molecular genetic mechanism of asthma remains elusive. AIMS: The aim of this study is to provide a comprehensive, detailed molecular etiology profile for the molecular factors that regulate the severity of asthma and pathogenicity using integrative bioinformatics tools. METHODS: The GSE43696 omnibus gene expression dataset, which contains 50 moderate cases, 38 severe cases, and 20 healthy controls, was used to investigate differentially expressed genes (DEGs), susceptible chromosomal loci, gene networks, pathways, gene ontologies, and protein-protein interactions (PPIs) using an intensive bioinformatics pipeline. RESULTS: The PPI network analysis yielded DEGs that contribute to interactions that differ from moderate-to-severe asthma. The combined interaction scores resulted in higher interactions for the genes STAT3, AGO2, COL1A1, CLCN6, and KSR for moderate asthma and JAK2, INSR, ERBB2, NR3C1, and PTK6 for severe asthma. Enrichment analysis (EA) demonstrated differential enrichment between moderate and severe asthma phenotypes; the ion transport regulation pathway was significantly enhanced in severe asthma phenotypes compared to that in moderate asthma phenotypes and involved PER2, GCR, IRS-2, KCNK7, KCNK6, NOX1, and SCN7A. The most enriched common pathway in both moderate and severe asthma is the development of the glucocorticoid receptor (GR) signaling pathway followed by glucocorticoid-mediated inhibition of proinflammatory and proconstrictory signaling in the airway of smooth muscle cell pathways. Gene sets were shared between severe and moderate asthma at 16 chromosome locations, including 17p13.1, 16p11.2, 17q21.31, 1p36, and 19q13.2, while 60 and 48 chromosomal locations were unique for both moderate and severe asthma, respectively. Phylogenetic analysis for DEGs showed that several genes have been intersected in phases of asthma in the same cluster of genes. This could indicate that several asthma-associated genes have a common ancestor and could be linked to the same biological function or gene family, implying the importance of these genes in the pathogenesis of asthma. CONCLUSION: New genetic risk factors for the development of moderate-to-severe asthma were identified in this study, and these could provide a better understanding of the molecular pathology of asthma and might provide a platform for the treatment of asthma.

Deciphering the Role of Filamin B Calponin-Homology Domain in Causing the Larsen Syndrome, Boomerang Dysplasia, and Atelosteogenesis Type I Spectrum Disorders via a Computational Approach.

Filamins (FLN) are a family of actin-binding proteins involved in regulating the cytoskeleton and signaling phenomenon by developing a network with F-actin and FLN-binding partners. The FLN family comprises three conserved isoforms in mammals: FLNA, FLNB, and FLNC. FLNB is a multidomain monomer protein with domains containing an actin-binding N-terminal domain (ABD 1-242), encompassing two calponin-homology domains (assigned CH1 and CH2). Primary variants in FLNB mostly occur in the domain (CH2) and surrounding the hinge-1 region. The four autosomal dominant disorders that are associated with FLNB variants are Larsen syndrome, atelosteogenesis type I (AOI), atelosteogenesis type III (AOIII), and boomerang dysplasia (BD). Despite the intense clustering of FLNB variants contributing to the LS-AO-BD disorders, the genotype-phenotype correlation is still enigmatic. In silico prediction tools and molecular dynamics simulation (MDS) approaches have offered the potential for variant classification and pathogenicity predictions. We retrieved 285 FLNB missense variants from the UniProt, ClinVar, and HGMD databases in the current study. Of these, five and 39 variants were located in the CH1 and CH2 domains, respectively. These variants were subjected to various pathogenicity and stability prediction tools, evolutionary and conservation analyses, and biophysical and physicochemical properties analyses. Molecular dynamics simulation (MDS) was performed on the three candidate variants in the CH2 domain (W148R, F161C, and L171R) that were predicted to be the most pathogenic. The MDS analysis results showed that these three variants are highly compact compared to the native protein, suggesting that they could affect the protein on the structural and functional levels. The computational approach demonstrates the differences between the FLNB mutants and the wild type in a structural and functional context. Our findings expand our knowledge on the genotype-phenotype correlation in FLNB-related LS-AO-BD disorders on the molecular level, which may pave the way for optimizing drug therapy by integrating precision medicine.

Sanguinarine Induces Apoptosis in Papillary Thyroid Cancer Cells via Generation of Reactive Oxygen Species.

Sanguinarine (SNG), a natural compound with an array of pharmacological activities, has promising therapeutic potential against a number of pathological conditions, including malignancies. In the present study, we have investigated the antiproliferative potential of SNG against two well-characterized papillary thyroid cancer (PTC) cell lines, BCPAP and TPC-1. SNG significantly inhibited cell proliferation of PTC cells in a dose and time-dependent manner. Western blot analysis revealed that SNG markedly attenuated deregulated expression of p-STAT3, without affecting total STAT3, and inhibited growth of PTC via activation of apoptotic and autophagy signaling cascade, as SNG treatment of PTC cells led to the activation of caspase-3 and caspase-8; cleavage of PARP and activation of autophagy markers. Further, SNG-mediated anticancer effects in PTC cells involved the generation of reactive oxygen species (ROS) as N-acetyl cysteine (NAC), an inhibitor of ROS, prevented SNG-mediated antiproliferative, apoptosis and autophagy inducing action. Interestingly, SNG also sensitized PTC cells to chemotherapeutic drug cisplatin, which was inhibited by NAC. Finally, SNG suppressed the growth of PTC thyrospheres and downregulated stemness markers ALDH2 and SOX2. Altogether, the findings of the current study suggest that SNG has anticancer potential against PTC cells as well its derived cancer stem-like cells, most likely via inactivation of STAT3 and its associated signaling molecules.

In silico and in vivo models for Qatari-specific classical homocystinuria as basis for development of novel therapies.

Homocystinuria is a rare inborn error of methionine metabolism caused by cystathionine ß-synthase (CBS) deficiency. The prevalence of homocystinuria in Qatar is 1:1,800 births, mainly due to a founder Qatari missense mutation, c.1006C>T; p.R336C (p.Arg336Cys). We characterized the structure-function relationship of the p.R336C-mutant protein and investigated the effect of different chemical chaperones to restore p.R336C-CBS activity using three models: in silico, ΔCBS yeast, and CRISPR/Cas9 p.R336C knock-in HEK293T and HepG2 cell lines. Protein modeling suggested that the p.R336C induces severe conformational and structural changes, perhaps influencing CBS activity. Wild-type CBS, but not the p.R336C mutant, was able to restore the yeast growth in ΔCBS-deficient yeast in a complementation assay. The p.R336C knock-in HEK293T and HepG2 cells decreased the level of CBS expression and reduced its structural stability; however, treatment of the p.R336C knock-in HEK293T cells with betaine, a chemical chaperone, restored the stability and tetrameric conformation of CBS, but not its activity. Collectively, these results indicate that the p.R336C mutation has a deleterious effect on CBS structure, stability, and activity, and using the chemical chaperones approach for treatment could be ineffective in restoring p.R336C CBS activity.

A computational method to characterize the missense mutations in the catalytic domain of GAA protein causing Pompe disease.

Pompe disease is an autosomal recessive lysosomal storage disease caused by acid α-glucosidase (GAA) deficiency, resulting in intralysosomal accumulation of glycogen, including cardiac, skeletal, and smooth muscle cells. The GAA gene is located on chromosome 17 (17q25.3), the GAA protein consists of 952 amino acids; of which 378 amino acids (347-726) falls within the catalytic domain of the protein and comprises of active sites (518 and 521) and binding sites (404, 600, 616, and 674). In this study, we used several computational tools to classify the missense mutations in the catalytic domain of GAA for their pathogenicity and stability. Eight missense mutations (R437C, G478R, N573H, Y575S, G605D, V642D, L705P, and L712P) were predicted to be pathogenic and destabilizing to the protein structure. These mutations were further subjected to phenotyping analysis using SNPeffect 4.0 to predict the chaperone binding sites and structural stability of the protein. The mutations R437C and G478R were found to compromise the chaperone-binding activity with GAA. Molecular docking analysis revealed that the G478R mutation to be more significant and hinders binding to the DNJ (Miglustat) compared with the R437C. Further molecular dynamic analysis for the two mutations demonstrated that the G478R mutation was acquired higher deviation, fluctuation, and lower compactness with decreased intramolecular hydrogen bonds compared to the mutant R437C. These data are expected to serve as a platform for drug design against Pompe disease and will serve as an ultimate tool for variant classification and interpretations.

An integrative bioinformatics pipeline to demonstrate the alteration of the interaction between the ALDH2*2 allele with NAD+ and Disulfiram.

Alcohol use disorder (AUD) is a multifactorial psychiatric behavior disorder. Disulfiram is the first approved drug by the Food and Drug Administration for alcohol-dependent patients, which targets the ALDH2 enzyme. Several genes are known to be involved in alcohol metabolism; mutations in any of these genes are known to be associated with AUD. The E504K mutation in the ALDH2 of the precursor protein or the E487K of the mature protein (E504K/E487K; ALDH2*2 allele) is carried by approximately 8% of the world population. In this study, we aimed to test the known inactive allele ALDH2*2, to validate the use of our extensive computational pipeline (in silico tools, molecular modeling, and molecular docking) for testing the interaction between the ALDH2*2 allele, NAD+, and Disulfiram. In silico predictions showed that the E504K variant of ALDH2 to be pathogenic and destabilizing with the maximum number of prediction in silico tools. Consequently, we studied the effect of this mutation mainly on the interaction between NAD+ -E504K and Disulfiram-E504K complexes using molecular docking technique, and molecular dynamics (MD) analysis. From the molecular docking analysis with NAD+ , we observed that the interaction affinity of the NAD+ decreases with the impact of E504K variant. On the other hand, the drug Disulfiram showed similar interaction in both the native and mutant ALDH2 proteins. Further, the comprehensive MD analysis predicted that the E504K destabilizes the protein and influences the NAD+ and Disulfiram interactions. Our findings reveal that the interaction of NAD+ to the protein is disturbed by the E504K/E487K variant whereas the drug Disulfiram has a similar effect as both native ALDH2 and ALDH2 bearing E504K/E487K variant. This study provides a platform to understand the effect of E504K/E487K on the molecular interaction with NAD+ and Disulfiram.

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.

Enhanced Identification of Transcriptional Enhancers Provides Mechanistic Insights into Diseases.

Enhancers are distal cis-regulatory DNA elements that increase the expression of target genes. Various experimental and computational approaches including chromatin signature profiling have been developed to predict enhancers on a genome-wide scale, although each method has its advantages and disadvantages. Here we overview an emerging method to identify transcribed enhancers at exceedingly high nucleotide resolution based on enhancer RNA transcripts captured by Cap Analysis of Gene Expression (CAGE) technology. We further argue that disease-causative regulatory mutations at enhancers are increasingly recognized, emphasizing the importance of enhancer identification in functional and clinical genomics including, but not limited to, genome-wide association studies (GWASs) and cancer genomics studies.