Substitution impact of highly conserved arginine residue at position 75 in GJB1 gene in association with X-linked Charcot-Marie-tooth disease: A computational study

Identification of Four Novel Candidate Genes for Non-syndromic Intellectual Disability in Pakistani Families

Intellectual disability, a genetically and clinically varied disorder and is a significant health problem, particularly in less developed countries due to larger family size and high ratio of consanguineous marriages. In the current genetic study, we investigate and find the novel disease causative factors in the four Pakistani families with severe type of non-syndromic intellectual disability. For genetic analysis whole-exome sequencing (WES) and Sanger sequencing was performed. I-TASSER and Cluspro tools were used for Protein modeling and Protein-protein docking. Sanger sequencing confirms the segregation of novel homozygous variants in all the families i.e., c.245 T > C; p.Leu82Pro in SLC50A1 gene in family 1, missense variant c.1037G > A; p.Arg346His in TARS2 gene in family 2, in family 3 and 4, nonsense mutation c.234G > A; p.Trp78Term and missense mutation c.2200G > A; p.Asp734Asn in TBC1D3 and ANAPC2 gene, respectively. In silico functional studies have found the drastic effect of these mutations on protein structure and its interaction properties. Substituted amino acids were highly conserved and present on highly conserved region throughout the species. The discovery of pathogenic variants in SLC50A1, TARS2, TBC1D1 and ANAPC2 shows that the specific pathways connected with these genes may be important in cognitive impairment. The decisive role of pathogenic variants in these genes cannot be determined with certainty due to lack of functional data. However, exome sequencing and segregation analysis of all filtered variants revealed that the currently reported variants were the only variations from the respective families that segregated with the phenotype in the family.

A computational approach to analyzing the functional and structural impacts of Tripeptidyl-Peptidase 1 missense mutations in neuronal ceroid lipofuscinosis

Neuronal ceroid-lipofuscinosis (NCLs) are a group of severe neurodegenerative conditions, most likely present in infantile, late infantile, juvenile, and adult-onset forms. Their phenotypic characteristics comprise eyesight damage, reduced motor activity and cognitive function, and sometimes tend to die in the initial stage. In recent studies, NCLs have been categorized into at least 14 genetic collections (CLN1-14). CLN2 gene encodes Tripeptidyl peptidase 1 (TPP1), which affects late infantile-onset form. In this study, we retrieved a mutational dataset screening for TPP1 protein from various databases (ClinVar, UniProt, HGMD). Fifty-six missense mutants were enumerated with computational methods to perceive the significant mutants (G475R and G501C) and correlated with clinical and literature data. A structure-based screening method was initiated to understand protein-ligand interaction and dynamic simulation. The docking procedure was performed for the native (3EDY) and mutant (G473R and G501C) structures with Gemfibrozil (gem), which lowers the lipid level, decreases the triglycerides amount in the blood circulation, and controls hyperlipidemia. The Native had an interaction score of -5.57 kcal/mol, and the mutants had respective average binding scores of -6.24 (G473R) and - 5.17 (G501C) kcal/mol. Finally, molecular dynamics simulation showed that G473R and G501C mutants had better flexible and stable orientation in all trajectory analyses. Therefore, this work gives an extended understanding of both functional and structural levels of influence for the mutant form that leads to NCL disorder.

Computational insights into dynamics and conformational stability of N-acetylmannosamine kinase mutations

The activity of UDP-GlcNAc 2-epimerase/ManNAc kinase (GNE) is essential for the biosynthesis of sialic acid, which is involved in cellular processes in health and diseases. GNE contains an N-terminal epimerase domain and a C-terminal kinase domain (N-acetylmannosamine kinase, MNK). Mutations of the GNE protein led to hypoactivity of the enzyme and cause sialurea or autosomal recessive inclusion body myopathy/Nonaka myopathy. Here, we used all-atom molecular dynamics (MD) simulations to comprehend the folding, dynamics and conformational stability of MNK variants, including the wild type (WT) and three mutants (H677R, V696M and H677R/V696M). The deleterious and destabilizing nature of MNK mutants were predicted using different prediction tools. Results predicted that mutations modulate the stability, flexibility and function of MNK. The effect of mutations on the conformational stability and dynamics of MNK was next studied through the free-energy landscape (FEL), hydrogen-bonds and secondary structure changes. The FEL results show that the mutations interfere with various conformational transitions in both WT and mutants, exposing the structural underpinnings of protein destabilization and unfolding brought on by mutation. We discover that, when compared to the other two mutations, V696M and H677R/V696M, H677R has the most harmful effects. These findings have a strong correlation with published experimental studies that demonstrate how these mutations disrupt MNK activity. Hence, this computational study describes the structural details to unravel the mutant effects at the atomistic resolution and has implications for understanding the GNE's physiological and pathological role.Communicated by Ramaswamy H. Sarma.

Computational identification and analysis of deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in the human POR gene: a structural and functional impact

Cytochrome P450 oxidoreductase (POR) protein is essential for steroidogenesis, and POR gene mutations are frequently associated with P450 Oxidoreductase Deficiency (PORD), a disorder of hormone production. To our knowledge, no previous attempt has been made to identify and analyze the deleterious/pathogenic non-synonymous single nucleotide polymorphisms (nsSNPs) in the human POR gene through an extensive computational approach. Computational algorithms and tools were employed to identify, characterize, and validate the pathogenic SNPs associated with certain diseases. To begin with, all the high-confidence SNPs were collected, and their structural and functional impacts on the protein structures were explored. The results of various in silico analyses affirm that the A287P and R457H variants of POR could destabilize the interactions between the amino acids and the hydrogen bond networks, resulting in functional deviations of POR. The literature study further confirms that the pathogenic mutations (A287P and R457H) are associated with the onset of PORD. Molecular dynamics simulations (MDS) and essential dynamics (ED) studies characterized the structural consequences of prioritized deleterious mutations, representing the structural destabilization that might disrupt POR biological function. The identified deleterious mutations at the cofactor's binding domains might interfere with the essential interactions between the protein and cofactors, thus inhibiting POR catalytic activity. The consolidated insights from the computational analyses can be used to predict potential deleterious mutants and understand the disease's pathological basis and the molecular mechanism of drug metabolism for the application of personalized medication. HIGHLIGHTSNADPH cytochrome P450 oxidoreductase (POR) mutations are associated with a broad spectrum of human diseasesIdentified and analyzed the most deleterious nsSNPs of POR through the sequence and structure-based prediction toolsInvestigated the structural and functional impacts of the most significant mutations (A287P and R457H) associated with PORDMolecular dynamics and PCA-based FEL analysis were utilized to probe the mutation-induced structural alterations in PORCommunicated by Ramaswamy H. Sarma.

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.

Identification and structural characterization of a pathogenic ARSA missense variant in two consanguineous families from Jammu and Kashmir (India) with late infantile metachromatic leukodystrophy

BACKGROUND

Metachromatic leukodystrophy (MLD) is a rare lysosomal storage disorder caused by a deficiency of Arylsulfatase A (ARSA) enzyme activity. Its clinical manifestations include progressive motor and cognitive decline. ARSA gene mutations are frequent in MLD.

METHODS AND RESULTS

In the present study, whole exome sequencing (WES) was employed to decipher the genetic cause of motor and cognitive decline in proband's of two consanguineous families from J&K (India). Clinical investigations using radiological and biochemical analysis revealed MLD-like features. WES confirmed a pathogenic variant in the ARSA gene. Molecular simulation dynamics was applied for structural characterization of the variant.

CONCLUSION

We report the identification of a pathogenic missense variant (c.1174 C > T; p.Arg390Trp) in the ARSA gene in two cases of late infantile MLD from consanguineous families in Jammu and Kashmir, India. Our study utilized genetic analysis and molecular dynamics simulations to identify and investigate the structural consequences of this mutation. The molecular dynamics simulations revealed significant alterations in the structural dynamics, residue interactions, and stability of the ARSA protein harbouring the p.Arg390Trp mutation. These findings provide valuable insights into the molecular mechanisms underlying the pathogenicity of this variant in MLD.

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.

Gene network interaction analysis to elucidate the antimicrobial resistance mechanisms in the Clostridiumdifficile

Antimicrobial resistance has caused chaos worldwide due to the depiction of multidrug-resistant (MDR) infective microorganisms. A thorough examination of antimicrobial resistance (AMR) genes and associated resistant mechanisms is vital to solving this problem. Clostridium difficile (C. difficile) is an opportunistic nosocomial bacterial strain that has acquired exogenous AMR genes that confer resistance to antimicrobials such as erythromycin, azithromycin, clarithromycin, rifampicin, moxifloxacin, fluoroquinolones, vancomycin, and others. A network of interactions, including 20 AMR genes, was created and analyzed. In functional enrichment analysis, Cellular components (CC), Molecular Functions (MF), and Biological Processes (BP) were discovered to have substantial involvement. Mutations in the rpl genes, which encode ribosomal proteins, confer resistance in Gram-positive bacteria. Full erythromycin and azithromycin cross-resistance can be conferred if more than one of the abovementioned genes is present. In the enriched BP, rps genes related to transcriptional regulation and biosynthesis were found. The genes belong to the rpoB gene family, which has previously been related to rifampicin resistance. The genes rpoB, gyrA, gyrB, rpoS, rpl genes, rps genes, and Van genes are thought to be the hub genes implicated in resistance in C. difficile. As a result, new medications could be developed using these genes. Overall, our observations provide a thorough understanding of C. difficile AMR mechanisms.

SARS-CoV-2 envelope protein attain Kac mediated dynamical interaction network to adopt 'histone mimic' at BRD4 interface

Interface mimicry, achieved by recognition of host-pathogen interactions, is the basis by which pathogen proteins can hijack the host machinery. The envelope (E) protein of SARS-CoV-2 is reported to mimic the histones at the BRD4 surface via establishing the structural mimicry; however, the underlying mechanism of E protein mimicking the histones is still elusive. To explore the mimics at dynamic and structural residual network level an extensive docking, and MD simulations were carried out in a comparative manner between complexes of H3-, H4-, E-, and apo-BRD4. We identified that E peptide is able to attain an 'interaction network mimicry', as its acetylated lysine (Kac) achieves orientation and residual fingerprint similar to histones, including water-mediated interactions for both the Kac positions. We identified Y59 of E, playing an anchor role to escort lysine positioning inside the binding site. Furthermore, the binding site analysis confirms that E peptide needs a higher volume, similar to the H4-BRD4 where both the lysine's (Kac5 and Kac8) can accommodate nicely, however, the position of Kac8 is mimicked by two additional water molecules other than four water-mediated bridging's, strengthening the possibility that E peptide could hijack host BRD4 surface. These molecular insights seem pivotal for mechanistic understanding and BRD4-specific therapeutic intervention. KEY POINTSMolecular mimicry is reported in hijacking and then outcompeting the host counterparts so that pathogens can rewire their cellular function by overcoming the host defense mechanism.The molecular recognition process is the basis of molecular mimicry. The E peptide of SARS-CoV-2 is reported to mimic host histone at the BRD4 surface by utilizing its C-terminally placed acetylated lysine (Kac63) to mimic the N-terminally placed acetylated lysine Kac5GGKac8 histone (H4) by interaction network mimicry identified through microsecond molecular dynamics (MD) simulations and post-processing extensive analysis.There are two steps to mimic: firstly, tyrosine residues help E to anchor at the BRD4 surface to position Kac and increase the volume of the pocket. Secondary, after positioning of Kac, a common durable interaction network N140:Kac5; Kac5:W1; W1:Y97; W1:W2; W2:W3; W3:W4; W4:P82 is established between Kac5, with key residues P82, Y97, N140, and four water molecules through water mediate bridge. Furthermore, the second acetylated lysine Kac8 position and its interaction as polar contact with Kac5 were also mimicked by E peptide through interaction network P82:W5; W5:Kac63; W5:W6; W6:Kac63.The binding event at BRD4/BD1 seems an induced-fit mechanism as a bigger binding site volume was identified at H4-BRD4 on which E peptide attains its better stability than H3-BRD4.We identified the tyrosine residue Y59 of E that acts like an anchor on the BRD4 surface to position Kac inside the pocket and attain the interaction network by using aromatic residues of the BRD4 surface.Communicated by Ramaswamy H. Sarma.

Computational refinement identifies functional destructive single nucleotide polymorphisms associated with human retinoid X receptor gene

Alterations in the nuclear retinoid X receptor (RXRs) signalling have been implicated in neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, stroke, multiple sclerosis and glaucoma. Single nucleotide polymorphisms (SNPs) are the main cause underlying single nucleic acid variations which in turn determine heterogeneity within various populations. These genetic polymorphisms have been suggested to associate with various degenerative disorders in population-wide analysis. This bioinformatics study was designed to investigate, search, retrieve and identify deleterious SNPs which may affect the structure and function of various RXR isoforms through a computational and molecular modelling approach. Amongst the 1,813 retrieved SNPs several were found to be deleterious with rs140464195_G139R, rs368400425_R358W and rs368586400_L383F RXRα mutant variants being the most detrimental ones causing changes in the interatomic interactions and decreasing the flexibility of the mutant proteins. Molecular genetics analysis identified seven missense mutations in RXRα/β/γ isoforms. Two novel mutations SNP IDs (rs1588299621 and rs1057519958) were identified in RXRα isoform. We used several in silico prediction tools such as SIFT, PolyPhen, I-Mutant, Protein Variation Effect Analyzer (PROVEAN), PANTHER, SNP&Go, PhD-SNP and SNPeffect to predict pathogenicity and protein stability associated with RXR mutations. The structural assessment by DynaMut tool revealed that hydrogen bonds were affected along with hydrophobic and carbonyl interactions resulting in reduced flexibility at the mutated residue positions but ultimately stabilizing the molecule as a whole. Summarizing, analysis of the missense mutations in RXR isoforms showed a mix of conclusive and inconclusive genotype-phenotype correlations suggesting the use of sophisticated computational analysis tools for studying RXR variants.Communicated by Ramaswamy H. Sarma.

Deciphering the structural and functional impact of missense mutations in Egr1-DNA interacting interface: an integrative computational approach

Early growth response-1 (Egr1) is a zinc-finger transcription factor that plays a critical role in controlling cell growth, proliferation, differentiation, angiogenesis, and apoptosis. Egr1 is induced by many growth factors, cytokines, and stress signals and is also known to be involved in several pathological conditions like cancer, neurological and ocular disorders. The DNA binding domain of Egr1 is a highly conserved Cys2His2 (C2H2) zinc finger (ZNF) domain which specifically binds to GC-rich consensus sequence GcG (G/T) GGGCG and activates transcription. As the C2H2 domain specifically recognizes its DNA target, the mutations spanning this region shall perturb DNA recognition and may hinder transcription of target genes. Therefore, in this study, the missense mutations occurring specifically at the DNA binding domain (DBD) of Egr1 were probed by computational approaches involving in silico screening of pathogenic and functional mutants coupled with extensive molecular dynamics simulations, to determine the mutants that affect its structural stability and interactions with DNA. From the pathogenicity analysis of 38 missense mutations spanning Egr1-DBD, 17 were predicted as pathogenic, and 7 amongst these were found to have functional impact on Egr1. On combined analysis of molecular dynamics simulation, Residue interaction analysis and Egr1-DNA interaction analysis results, the mutants R371C and R375C showed least impact, whilst, H382R tend to increase the structural stability, whereas R360H, H390R, E393V, and H414Y conferred greater impact by altering the structural stability and DNA interactions. Hence, this study exposes the prospects of considering these 4 deleterious mutations for clinical significance, but needs further experimental validation.HighlightsEgr1's DNA binding domain is a highly conserved Cys2His2 (C2H2) zinc finger domain that specifically recognizes its DNA target.Mutations spanning in the DNA binding domain shall perturb DNA recognition and may hinder transcription.Among the missense mutations, mutants R360H, H390R, E393V, and H414Y were inferred to have a greater impact on Egr1 by altering the structural stability and DNA interactions.

In Silico Analysis of the L-2-Hydroxyglutarate Dehydrogenase Gene Mutations and Their Biological Impact on Disease Etiology

The L-2-hydroxyglutarate dehydrogenase (L2HGDH) gene encodes an important mitochondrial enzyme. However, its altered activity results in excessive levels of L-2-hydroxyglutarate, which results in diverse psychiatric features of intellectual disability. In the current study, we executed an in-silico analysis of all reported L2HGDH missense and nonsense variants in order to investigate their biological significance. Among the superimposed 3D models, the highest similarity index for a wild-type structure was shown by the mutant Glu336Lys (87.26%), while the lowest similarity index value was shown by Arg70* (10.00%). Three large active site pockets were determined using protein active site prediction, in which the 2nd largest pocket was shown to encompass the substrate L-2-hydroxyglutarate (L2HG) binding residues, i.e., 89Gln, 195Tyr, 402Ala, 403Gly and 404Val. Moreover, interactions of wild-type and mutant L2HGDH variants with the close functional interactor D2HGDH protein resulted in alterations in the position, number and nature of networking residues. We observed that the binding of L2HG with the L2HGDH enzyme is affected by the nature of the amino acid substitution, as well as the number and nature of bonds between the substrate and protein molecule, which are able to affect its biological activity.

Prediction of Functional Consequences of Missense Mutations in ANO4 Gene

The anoctamin (TMEM16) family of transmembrane protein consists of ten members in vertebrates, which act as Ca²⁺-dependent ion channels and/or Ca²⁺-dependent scramblases. ANO4 which is primarily expressed in the CNS and certain endocrine glands, has been associated with various neuronal disorders. Therefore, we focused our study on prioritizing missense mutations that are assumed to alter the structure and stability of ANO4 protein. We employed a wide array of evolution and structure based in silico prediction methods to identify potentially deleterious missense mutations in the ANO4 gene. Identified pathogenic mutations were then mapped to the modeled human ANO4 structure and the effects of missense mutations were studied on the atomic level using molecular dynamics simulations. Our data show that the G80A and A500T mutations significantly alter the stability of the mutant proteins, thus providing new perspective on the role of missense mutations in ANO4 gene. Results obtained in this study may help to identify disease associated mutations which affect ANO4 protein structure and function and might facilitate future functional characterization of ANO4.

TK, Ahmad MN, Okashah SS, Kamaraj B, Al-Subaie AM, C. GPD, Zayed H. 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.

Investigating the structural impacts of a novel missense variant identified with whole exome sequencing in an Egyptian patient with propionic acidemia

Propionic Acidemia (PA) is an inborn error of metabolism caused by variants in the PCCA or PCCB genes, leading to mitochondrial accumulation of propionyl-CoA and its by-products. Here, we report a 2 year-old Egyptian boy with PA who was born to consanguineous parents. Biochemical analysis was performed using tandem mass spectrometry (MS/MS) on the patient's dried blood spots (DBS) followed by urine examination of amino acids using gas chromatography/mass spectrometry (GC/MS). Molecular genetic analysis was carried out using whole-exome sequencing (WES). The PCCA gene sequencing revealed a novel homozygous missense variant affecting the locus (chr13:100962160) of exon 16 of the PCCA gene, resulting in the substitution of the amino acid arginine with proline at site 476 (p.Arg476Pro). Computational analysis revealed that the novel variant might be pathogenic and attributed to decrease the stability and also has an effect on the biotin carboxylase c-terminal domain of the propionyl carboxylase enzyme. The physicochemical properties analysis using NCBI amino acid explorer study revealed restrictions in the side chain and loss of hydrogen bonds due to the variant. On the structural level, the loss of beta-sheet was observed due to the variant proline, which has further led to the loss of surrounding interactions. This loss of beta-sheet and the surrounding interactions might serve the purpose of the structural stability changes. The current study demonstrates that a combination of whole-exome sequencing (WES) and computational analysis are potent tools for validation of diagnosis and classification of disease-causing variants.

Identification of potential inhibitors against pathogenic missense mutations of PMM2 using a structure-based virtual screening approach

The autosomal recessive phosphomannomutase 2-congenital disorder of glycosylation (PMM2-CDG) is characterized by defective functioning of the PMM2 enzyme, which is necessary for the conversion of mannose-6-phosphate into mannose-1-phosphate. Here, a computational pipeline was drawn to identify the most significant mutations, and further, we used a virtual screening approach to identify a new lead compound to treat the identified significant mutations. We searched for missense mutation data related to PMM2-CDG in HGMD®, UniProt, and ClinVar. Our search yielded a total of 103 mutations, of which 91 are missense mutations. The D65Y, I132N, I132T, and F183S mutations were classified as deleterious, destabilizing, and altering the biophysical properties using the PredictSNP, iStable, and Align GVGD in silico prediction tools. Additionally, we applied a multistep protocol to screen for an alternative lead compound to the existing CID2876053 (1-(3-chlorophenyl)-3,3-bis(pyridine-2-yl)urea) with affinity to these identified significant mutants. Two compounds, CHEMBL1491007 (6-chloro-4-phenyl-3-(4-pyridin-2-ylpiperazin-1-yl)-1H-quinolin-2-one) and CHEMBL3653029 (5-chloro-4-[6-[(3-fluorophenyl)methylamino]pyridin-2-yl]-N-(piperidin-4-ylmethyl)pyridin-2-amine), exhibited the highest binding affinity with the selected mutants and were chosen for further analysis. Through molecular docking, molecular dynamics simulation, and MMPBSA analysis, we found that the known compound, i.e. CID2876053, has stronger interaction with the D65Y mutant. The newly identified lead compound CHEMBL1491007 showed stronger interaction with the I132N and I132T mutants, whereas the most deleterious mutant, F183S, showed stronger interaction with CHEMBL3653029. This study is expected to aid in the field of precision medicine, and further to in vivo and in vitro analysis of these lead compounds might shed light on the treatment of PMM2-CDG. Communicated by Ramaswamy H. Sarma.

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.

The impact of missense mutation in PIGA associated to paroxysmal nocturnal hemoglobinuria and multiple congenital anomalies-hypotonia-seizures syndrome 2: A computational study

Paroxysmal nocturnal hemoglobinuria (PNH) is an acquired clonal blood disorder that manifests with hemolytic anemia, thrombosis, and peripheral blood cytopenias. The disease is caused by the deficiency of two glycosylphosphatidylinositols (GPI)-anchored proteins (CD55 and CD59) in the hemopoietic stem cells. The deficiency of GPI-anchored proteins has been associated with the somatic mutations in phosphatidylinositol glycan class A (PIGA). However, the mutations that do not cause PNH is associated with the multiple congenital anomalies-hypotonia-seizures syndrome 2 (MCAHS2). To best of our knowledge, no computational study has been performed to explore at an atomistic level the impact of PIGA missense mutations on the structure and dynamics of the protein. Therefore, we focused our study to provide molecular insights into the changes in protein structural dynamics upon mutation. In the initial step, screening for the most pathogenic mutations from the pool of publicly available mutations was performed. Further, to get a better understanding, pathogenic mutations were mapped to the modeled structure and the resulting protein was subjected to 100 ns molecular dynamics simulation. The residues close to C- and N-terminal regions of the protein were found to exhibit greater flexibility upon mutation. Our study suggests that four mutations are highly effective in altering the structural conformation and stability of the PIGA protein. Among them, mutant G48D was found to alter protein's structural dynamics to the greatest extent, both on a local and a global scale.

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.

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 insights of K1444N substitution in GAP-related domain of NF1 gene associated with neurofibromatosis type 1 disease: a molecular modeling and dynamics approach

The NF1 gene encodes for neurofibromin protein, which is ubiquitously expressed, but most highly in the central nervous system. Non-synonymous SNPs (nsSNPs) in the NF1 gene were found to be associated with Neurofibromatosis Type 1 disease, which is characterized by the growth of tumors along nerves in the skin, brain, and other parts of the body. In this study, we used several in silico predictions tools to analyze 16 nsSNPs in the RAS-GAP domain of neurofibromin, the K1444N (K1423N) mutation was predicted as the most pathogenic. The comparative molecular dynamic simulation (MDS; 50 ns) between the wild type and the K1444N (K1423N) mutant suggested a significant change in the electrostatic potential. In addition, the RMSD, RMSF, Rg, hydrogen bonds, and PCA analysis confirmed the loss of flexibility and increase in compactness of the mutant protein. Further, SASA analysis revealed exchange between hydrophobic and hydrophilic residues from the core of the RAS-GAP domain to the surface of the mutant domain, consistent with the secondary structure analysis that showed significant alteration in the mutant protein conformation. Our data concludes that the K1444N (K1423N) mutant lead to increasing the rigidity and compactness of the protein. This study provides evidence of the benefits of the computational tools in predicting the pathogenicity of genetic mutations and suggests the application of MDS and different in silico prediction tools for variant assessment and classification in genetic clinics.

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.