Canavan disease (CD) is a rare fatal childhood neurological autosomal recessive genetic disease caused by mutations in the ASPA gene, which lead to catalytic deficiency of the ASPA enzyme, which catalyzes the hydrolysis of N-acetyl-L-aspartate (NAA) into aspartate and acetate. CD occurs frequently among Ashkenazi Jewish population, however it has been reported in many other ethnic groups with significantly lower frequency. Here, we report on two Egyptian patients diagnosed with CD, the first patient harbors five missense mutations (c.427 A &gt; G; p. I143V, c.502C &gt; T; p. R168C, c.530 T &gt; C; p. I177T, c.557 T &gt; C; p. V186D c.548C &gt; T; p. P183L) and a silent mutation (c.693 C &gt; T; p. Y231Y). The second patient was found to be homozygous for two missense mutations (c.427 A &gt; G; p. I143V and c.557 T &gt; A; p. V186D). Furthermore, molecular modeling of the novel mutation p. P183L provides an instructive explanation of the mutational impact on the protein structure that can affect the function of the ASPA. Here, the clinical, radiological, and biochemical profile of the two patients are reviewed in details. © 2016, Springer Science+Business Media New York.

Krishnamoorthy A

Department of Software Systems

School of Computer Science and Engineering

Vellore Campus

George Priya Doss C

Department of Integrative Biology

School of Bio Sciences and Technology

Zaki O.K

El Abd H.S

Harche S.A

Mattar R.A

Al disi R.S

Nofal M.Y

El Bekay R

Ahmed K.A

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Metabolic Brain Disease

Type I galactosemia is a very rare autosomal recessive genetic metabolic disorder that occurs because of the mutations present in the galactose-1-phosphate uridyl transferase (GALT) gene, resulting in a deficiency of the GALT enzyme. The action of the GALT enzyme is to convert galactose-1-phosphate and uridine diphosphate glucose into glucose-1-phosphate (G1P) and uridine diphosphate-galactose, a crucial second step of the Leloir pathway. A missense mutation in the GALT enzyme leads to variable galactosemia's clinical presentations, ranging from mild to severe. Our study aimed to employ a comprehensive computational pipeline to analyze the most prevalent missense mutations (p.S135L, p.K285 N, p.Q188R, and p.N314D) responsible for galactosemia; these genes could serve as potential targets for chaperone therapy. We analyzed the four mutations through different computational analyses, including amino acid conservation, in silico pathogenicity and stability predictions, and macromolecular simulations (MMS) at 50 ns The stability and pathogenicity predictors showed that the p.Q188R and p.S135L mutants are the most pathogenic and destabilizing. In agreement with these results, MMS analysis demonstrated that the p.Q188R and p.S135L mutants possess higher deviation patterns, reduced compactness, and intramolecular H-bonds of the protein. This could be due to the physicochemical modifications that occurred in the mutants p.S135L and p.Q188R compared to the native. Evolutionary conservation analysis revealed that the most prevalent mutations positions were conserved among different species except N314. The proposed research study is intended to provide a basis for the therapeutic development of drugs and future treatment of classical galactosemia and possibly other genetic diseases using chaperone therapy. © 2019 Elsevier Ltd

Fulltext

Computers in Biology and Medicine

An extensive computational approach to analyze and characterize the functional mutations in the galactose-1-phosphate uridyl transferase (GALT) protein responsible for classical galactosemia

Breast cancer (BC) is the most commonly diagnosed cancer among females worldwide, and among the BC-associated mutations in various proteins, mutations in the RAC-alpha serine/threonine-protein kinase (AKT1) remain the most dominant. We thus attempted to understand the potential molecular pathogenicity profile of the mutations in AKT1 using a comprehensive computational protocol involving analyses of biochemistry-disruption and destabilizing properties and conservation. Our predictions revealed that E17K, R67W, V164G, E319G, R391G, D32Y, L52H, L52R, and W80R were the most pathogenic mutations. In addition, the change of glutamate to lysine at position 17 of AKT1 (E17K) was found to be highly predominant. An extensive two-step molecular dynamics (simple and complex) simulation (MDS) using GROMACS (GROningen MAchine for Chemical Simulations) was then initiated to analyze and understand the structural impact of the E17K mutation on the function of AKT1. The simple MDS analysis revealed that the E17K mutation decreases the compactness and intramolecular hydrogen bonds of the protein. We also performed a virtual screening analysis with 19 AKT inhibitors obtained from the Selleck Chemicals website those satisfied the Lipinski rule of 5. Among these 19 compounds, Akti-1/2 exhibited the best binding affinity with both native AKT1 and the E17K mutant. The molecular interaction study also revealed that the co-crystallized AKT1 inhibitor N-(4-(5-(3-acetamidophenyl)-2-(2-aminopyridin-3-yl)-3H-imidazo [4,5-b]pyridin-3-yl)benzyl)-3-fluorobenzamide (12j) exhibited a better interaction with native AKT1 compared with the E17K mutant AKT1 protein, whereas, Akti-1/2 exhibited the opposite effects, i.e., a better interaction with the E17K mutant AKT1 than the native AKT1. These findings from the interaction analysis were further supported by the complex MDS, which measured the compactness and intermolecular hydrogen bonds of the proteins. The results obtained in this study suggest that Akti-1/2 might be a better inhibitor for the treatment of BC caused by the E17K mutation in AKT1. © 2019 Elsevier Ltd

A computational approach for investigating the mutational landscape of RAC-alpha serine/threonine-protein kinase (AKT1) and screening inhibitors against the oncogenic E17K mutation causing breast cancer

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. © 2018 Wiley Periodicals, Inc.

Journal of Cellular Biochemistry

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

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. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.

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

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

Structural modeling of p.V31F variant in the aspartoacylase gene

Novel mutation in an Egyptian patient with infantile Canavan disease

Pediatrics International

Canavan disease: Clinical features and recent advances in research

Clinical Biochemistry

New T530C mutation in the aspartoacylase gene caused Canavan disease with no correlation between severity and N-acetylaspartate excretion

PLoS ONE

Molecular Modeling of Disease Causing Mutations in Domain C1 of cMyBP-C

Two patients with Canavan disease and structural modeling of a novel mutation

Journal	Data powered by TypesetMetabolic Brain Disease
Publisher	Data powered by TypesetSpringer Science and Business Media LLC
ISSN	0885-7490
Open Access	No