Structural Analysis of G1691S Variant in the Human Filamin B Gene Responsible for Larsen Syndrome: A Comparative Computational Approach

Exploring the impact of variations in the mucolipin1 protein that result in mucolipidosis type 4 using the technique of molecular docking and dynamics simulation

Mucolipidosis type IV (MLIV) is classified as an exceptionally autosomal recessive condition due to a change in MCOLN1 that encodes the mucolipin-1 protein. ML-1 is a membrane protein comprising 6 Trans regions, which are situated at the LELs, a serine lipase area, and a nuclear localization sign. The characteristic features of the ML4 patients are mental retardation and skeletal deformities due to an increase in lipid molecules in the brain, other tissues, and organs. The fundamental goal of the work is to identify the most significant amino acid variants via a computational pipeline. The twenty-three amino acid variants that are responsible for the condition were retrieved from the public domain: L106P and L447P amino acid variants, with the following categories: extremely conserved, highly pathogenic, most interfering with protein function, more structurally unstable, and having promising Phenotyping characteristics was scrutinized from the series of bioinformatics tools that denote its significant nature. A docking and dynamics study was initiated to identify the interaction profiling and interatomic simulation between the Native, L106P, and L447P and the ligand ML-SA1 (it was known to ease the fatty acid buildup in lysosomes of cellular models of Mucolipidosis type IV) and had a score of -6.19, -5.12, and -5.21 kcal/mol, followed by a duplicate 100-ns run trajectory results, which assisted in detecting the stable nature of all the complex structures. Hence, this work helps to recognize the significant role of the scrutinized amino acid variants and, on the other hand, the stable nature of the ligand using standard computational tools.

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.

The pathogenic effect of SNPs on structure and function of human TLR4 using a computational approach

The human toll-like receptor (hTLR) 4 single nucleotide polymorphisms (SNPs) are interconnected with cancer, multiple genetic disorders and other immune-related diseases. The detrimental effect of SNPs in hTLR4 with respect to structure and function has not been explored in depth. The present study concatenates the biological consequences of the SNPs along with structural modifications predicted at the hTLR4 gene. A total of 7910 SNPs of hTLR4 were screened, and 21 damage-causing SNPs were identified. Out of 21, seven are present in the extracellular region, of which three were detected as deleterious and the fourth one as moderate. These three mutations are located in a highly conserved region and influence conformational change. The change leads to the widening of the Leucine-rich repeat (LRR) arc to a maximum of 16.9 Å and a minimum of 8.7 Å. Expansion/shortening of LRR arc, never discussed before, would cause loss of myeloid differentiation factor 2 (MD-2) interactions in the interior and diminish lipopolysaccharide (LPS) responses. Similarly, in all mutant structures, the binding region for HMGB1 and LPS is deflating or in an unsupportive conformation. Thus, SNPs affect the regular signaling cascade and might result in human sepsis, genetic disorders, cancer and other immunological related diseases.Communicated by Ramaswamy H. Sarma.

Computational screening and structural analysis of Gly201Arg and Gly201Asp missense mutations in human cyclin-dependent kinase 4 protein

The regulatory proteins, cyclins, and cyclin-dependent kinases (CDKs) control the cell cycle progression. CDK4 gene mutations are associated with certain cancers such as melanoma, breast cancer, and rhabdomyosarcoma. Therefore, understanding the mechanisms of cell cycle control and cell proliferation is essential in developing cancer treatment regimens. In this study, we obtained cancer-causing CDK4 mutations from the COSMIC database and subjected them to a series of in silico analyses to identify the most significant mutations. An overall of 238 mutations (119 missense mutations) retrieved from the COSMIC database were investigated for the pathogenic and destabilizing properties using the PredictSNP and iStable algorithms. Further, the amino acid position of the most pathogenic and destabilizing mutations were analyzed to understand the nature of amino acid conservation across the species during the evolution. We observed that the missense mutations G201R and G201D were more significant and the Glycine at position 201 was found to highly conserved. These significant mutations were subjected to molecular dynamics simulation analysis to understand the protein's structural changes. The results from molecular dynamics simulations revealed that both G201R and G201D of CDK4 are capable of altering the protein's native form. On comparison among the most significant mutations, G201R disrupted the protein structure higher than the protein with G201D.

A computational approach to analyse the amino acid variants of GLB1 protein causing GM1 Gangliosidosis

Lysosomal storage diseases comprise different forms of autosomal recessive disorders from which GM1 gangliosidosis has categorized by the accumulation of complex glycolipids associated with a range of progressive neurologic phenotypes. GM1 gangliosidosis is an inherited disorder that progressively destroys nerve cells (neurons) in the brain and spinal cord. GM1 has three main types of onsets, namely infantile (type I), juvenile (type II), and adult (type III) forms. This study provides a series of computational methods that examine the mutations that occurred in GLB1 protein. Initially, the mutational analysis started with 689 amino acid variants for a sequence-based screening and it was done with quite a few In-silico tools to narrow down the most significant variants by utilizing the standard tools; namely, Evolutionary analysis (77 variants), Pathogenicity prediction (44 variants), Stability predictions (30 variants), Biophysical functions (19 variants) and according to the binding site of protein structure with PDB ID 3THC, seven variants (Y83D, Y83H, Y270S, Y270D, W273R, W273D, and Y333H) were narrowed down. Structure based analysis was performed to understand the interacting profile of the native protein and variants with Miglustat; which is the currently used FDA drug as an alternative to enzyme replacement therapy. Molecular Docking study was done to analyze the protein interaction with Miglustat (ligand), as a result native (3THC) structure had a binding affinity of -8.18 kcal/mol and two variant structures had an average binding affinities of -2.61 kcal/mol (Y83D) and - 7.63 kcal/mol (Y270D). Finally, Molecular Dynamics Simulation was performed to know the mutational activity of the protein structures on Miglustat for 50,000 ps. The Y83D variant showed higher deviation than native protein and Y270D in all trajectory analysis. The analysis was done to the protein structures to check the structural variations happened through simulations. This study aids to understand the most deleterious mutants, the activity of the drug to the protein structure and also gives an insight on the stability of the drug with the native and selected variants.

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.

Molecular modeling and dynamic simulation of chicken Mx protein with the S631N polymorphism

Myxovirus resistance (Mx) proteins are antiviral GTPases induced by type I interferons (IFNs). In chickens, a single Mx protein variant, S631N, has been suggested to possess antiviral activity. However, the impact of this variant on chicken Mx (chMx) protein structure and conformation has not been investigated. Hence, in this study, we applied computational methods such as molecular modeling, molecular dynamic simulation, inter domain motion and residue networks to examine the structure and dynamic behavior of wild-type and mutant chMx. At first, we built 3-dimensional structural models for both wild-type and mutant chMx proteins, which revealed that the structural organization of chMx was similar to that of human Mx proteins. Subsequently, molecular dynamics simulations revealed that angle variation around the hinge1 region led to the different stalk domain conformations between the wild-type and mutant chMx proteins. Domain motion analysis further suggested that the conformational differences in the loop region surrounded by the mutant residue may lead to an inclined stalk domain conformation in the mutant compared to the wild-type protein. In addition, we performed betweenness centrality analysis from residue interaction networks, to identify the crucial residues for intramolecular signal flow in chMx. The results of this study provided information on the differences in structure and dynamics between wild-type and mutant chMx, which may aid in understanding the structural features of the S631N mutant, that may be associated with chMx protein antiviral activity.Communicated by Ramaswamy H. Sarma.

The pathogenicity, structural and functional exploration of human HMGB1 single nucleotide polymorphisms using in silico study

The human HMGB1 gene mutations have a major impact on several immune-related diseases and cancer. The detrimental effect of non-synonymous mutations of HMGB1 has not been investigated yet, hence the present study aims to examine single nucleotide polymorphisms and their implications on the structure-function of human HMGB1. The multifaceted HMGB1 protein acts as pleiotropic cytokine and regulates essential genes for coordinated cellular functions. The mutational effect on HMGB1 was analyzed by sequence-based homology methods, supervised learning methods, and structure-based methods. The study identified 58 non-synonymous mutations in human HMGB1, out of which only 2 mutations; R10T (rs61742222) and F103C (rs61733675) were classified as the SNPs with highest deleterious and disease-causing mutants. The effect of these mutations in structure of HMGB1 was scrutinized and the R10T mutant found to have a distinct structural behaviour in the B-box domain. In addition, R10T mutant predicted that it affects the MoRF function of HMGB1 and it could disrupt the DNA binding or/and protein partner interaction activity by HMGB1. F103C mutation takes place at the TLR binding and cytokine inducing region of HMGB1, hence it could affect the protein binding activity which involves in many cellular signaling. The study identified potent mutations R10T (a cancer-causing somatic mutation) and F103C (a novel mutation) and these mutations either directly or indirectly hinder DNA binding activity and TLR and cytokine binding of HMGB1. These findings will help in understanding the molecular basis of these promising mutations and functional role of human HMGB1 in cancer and immunological diseases.AbbreviationsAGERAdvanced glycosylation end product-specific receptorCXCLChemokine (C-X-C motif) liganddbSNPThe single nucleotide polymorphism databaseHMGB1High mobility group box 1LINCSLINear Constraint SolverMDSMolecular dynamics simulationMoRFMolecular recognition featuresNPTNumber of particle, Pressure and TemperatureNVTNumber of particle, Volume and TemperaturensSNPNon-synonymous SNPPBCPartial boundary conditionPCAPrincipal component analysisPMEPartial mesh EwaldRMSDRoot mean square deviationRMSFRoot mean square fluctuationSNPSingle nucleotide polymorphismSPCSingle-point chargeTLRToll-like receptorUTRUn-translated RegionCommunicated by Ramaswamy H. Sarma.

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.

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.

Novel Mutations Associated With Various Types of Corneal Dystrophies in a Han Chinese Population

Aims: To study the genetic spectra of corneal dystrophies (CDs) in Han Chinese patients using next-generation sequencing (NGS).

Methods: NGS-based targeted region sequencing was performed to evaluate 71 CD patients of Han Chinese ethnicity. A custom-made capture panel was designed to capture all coding exons and untranslated regions plus 25 bp of intronic flanking sequences of 801 candidate genes for eye diseases. The Genome Analysis Tool Kit Best Practices pipeline and an intensive computational prediction pipeline were applied for the analysis of pathogenic variants.

Results: We achieved a mutation detection rate of 59.2% by NGS. Eighteen known mutations in CD-related genes were found in 42 out of 71 patients, and these cases showed a genotype–phenotype correlation consistent with previous reports. Nine novel variants that were likely pathogenic were found in various genes, including CHST6, TGFBI, SLC4A11, AGBL1, and COL17A1. These variants were all predicted to be protein-damaging by an intensive computational analysis.

Conclusions: This study expands the spectra of genetic mutations associated with various types of CDs in the Chinese population and highlights the clinical utility of targeted NGS for genetically heterogeneous CD.

Prioritization of SNPs in y+LAT-1 culpable of Lysinuric protein intolerance and their mutational impacts using protein-protein docking and molecular dynamics simulation studies

Lysinuric protein intolerance (LPI) is a rare, yet inimical, genetic disorder characterized by the paucity of essential dibasic amino acids in the cells. Amino acid transporter y+LAT-1 interacts with 4F2 cell-surface antigen heavy chain to transport the required dibasic amino acids. Mutation in y+LAT-1 is rumored to cause LPI. However, the underlying pathological mechanism is unknown, and, in this analysis, we investigate the impact of point mutation in y+LAT-1's interaction with 4F2 cell-surface antigen heavy chain in causing LPI. Using an efficient and extensive computational pipeline, we have isolated M50K and L334R single-nucleotide polymorphisms to be the most deleterious mutations in y+LAT-1s. Docking of mutant y+LAT-1 with 4F2 cell-surface antigen heavy chain showed decreased interaction compared with native y+LAT-1. Further, molecular dynamic simulation analysis reveals that the protein molecules increase in size, become more flexible, and alter their secondary structure upon mutation. We believe that these conformational changes because of mutation could be the reason for decreased interaction with 4F2 cell-surface antigen heavy chain causing LPI. Our analysis gives pathological insights about LPI and helps researchers to better understand the disease mechanism and develop an effective treatment strategy.

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.

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

X-linked Charcot-Marie-Tooth type 1 X (CMTX1) disease is a subtype of Charcot-Marie-Tooth (CMT), which is mainly caused by mutations in the GJB1 gene. It is also known as connexin 32 (Cx32) that leads to Schwann cell abnormalities and peripheral neuropathy. CMTX1 is considered as the second most common form of CMT disease. The aim of this study is to computationally predict the potential impact of different single amino acid substitutions at position 75 of Cx32, from arginine (R) to proline (P), glutamine (Q) and tryptophan (W). This position is known to be highly conserved among the family of connexin. To understand the structural and functional changes due to these single amino acid substitutions, we employed a homology-modeling technique to build the three-dimensional structure models for the native and mutant proteins. The protein structures were further embedded into a POPC lipid bilayer, inserted into a water box, and subjected to molecular dynamics simulation for 50 ns. Our results show that the mutants R75P, R75Q and R75W display variable structural conformation and dynamic behavior compared to the native protein. Our data proves useful in predicting the potential pathogenicity of the mutant proteins and is expected to serve as a platform for drug discovery for patients with CMT.

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.

Filamin B: The next hotspot in skeletal research?

Filamin B (FLNB) is a large dimeric actin-binding protein which crosslinks actin cytoskeleton filaments into a dynamic structure. Up to present, pathogenic mutations in FLNB are solely found to cause skeletal deformities, indicating the important role of FLNB in skeletal development. FLNB-related disorders are classified as spondylocarpotarsal synostosis (SCT), Larsen syndrome (LS), atelosteogenesis (AO), boomerang dysplasia (BD), and isolated congenital talipes equinovarus, presenting with scoliosis, short-limbed dwarfism, clubfoot, joint dislocation and other unique skeletal abnormalities. Several mechanisms of FLNB mutations causing skeletal malformations have been proposed, including delay of ossification in long bone growth plate, reduction of bone mineral density (BMD), dysregulation of muscle differentiation, ossification of intervertebral disc (IVD), disturbance of proliferation, differentiation and apoptosis in chondrocytes, impairment of angiogenesis, and hypomotility of osteoblast, chondrocyte and fibroblast. Interventions on FLNB-related diseases require prenatal surveillance by sonography, gene testing in high-risk carriers, and proper orthosis or orthopedic surgeries to correct malformations including scoliosis, cervical spine instability, large joint dislocation, and clubfoot. Gene and cell therapies for FLNB-related diseases are also promising but require further studies.

TK, C. GPD, R. S, Zayed H. Determining the role of missense mutations in the POU domain of HNF1A that reduce the DNA-binding affinity: A computational approach

Maturity-onset diabetes of the young type 3 (MODY3) is a non-ketotic form of diabetes associated with poor insulin secretion. Over the past years, several studies have reported the association of missense mutations in the Hepatocyte Nuclear Factor 1 Alpha (HNF1A) with MODY3. Missense mutations in the POU homeodomain (POUH) of HNF1A hinder binding to the DNA, thereby leading to a dysfunctional protein. Missense mutations of the HNF1A were retrieved from public databases and subjected to a three-step computational mutational analysis to identify the underlying mechanism. First, the pathogenicity and stability of the mutations were analyzed to determine whether they alter protein structure and function. Second, the sequence conservation and DNA-binding sites of the mutant positions were assessed; as HNF1A protein is a transcription factor. Finally, the biochemical properties of the biological system were validated using molecular dynamic simulations in Gromacs 4.6.3 package. Two arginine residues (131 and 203) in the HNF1A protein are highly conserved residues and contribute to the function of the protein. Furthermore, the R131W, R131Q, and R203C mutations were predicted to be highly deleterious by in silico tools and showed lower binding affinity with DNA when compared to the native protein using the molecular docking analysis. Triplicate runs of molecular dynamic (MD) simulations (50ns) revealed smaller changes in patterns of deviation, fluctuation, and compactness, in complexes containing the R131Q and R131W mutations, compared to complexes containing the R203C mutant complex. We observed reduction in the number of intermolecular hydrogen bonds, compactness, and electrostatic potential, as well as the loss of salt bridges, in the R203C mutant complex. Substitution of arginine with cysteine at position 203 decreases the affinity of the protein for DNA, thereby destabilizing the protein. Based on our current findings, the MD approach is an important tool for elucidating the impact and affinity of mutations in DNA-protein interactions and understanding their function.

Analyzing the Effect of V66M Mutation in BDNF in Causing Mood Disorders: A Computational Approach

Mental disorders or mood disorders are prevalent globally irrespective of region, race, and ethnic groups. Of the types of mood disorders, major depressive disorder (MDD) and bipolar disorder (BPD) are the most prevalent forms of psychiatric condition. A number of preclinical studies emphasize the essential role of brain-derived neurotrophic factor (BDNF) in the pathophysiology of mood disorders. Additionally, BDNF is the most common growth factor in the central nervous system along with their essential role during the neural development and the synaptic elasticity. A malfunctioning of this protein is associated with many types of mood disorders. The variant methionine replaces valine at 66th position is strongly related to BPD, and an individual with a homozygous condition of this allele is at a greater risk of developing MDD. There are very sparse reports suggesting the structural changes of the protein occurring upon the mutation. Consequently, in this study, we applied a computational pipeline to understand the effects caused by the mutation on the protein's structure and function. With the use of in silico tools and computational macroscopic methods, we identified a decrease in the alpha-helix nature, and an overall increase in the random coils that could have probably resulted in deformation of the protein.