In Silico Analysis of SNPs in<i> PARK2</i> and<i> PINK1</i> Genes That Potentially Cause Autosomal Recessive Parkinson Disease

Bakhit, Yousuf; Ibrahim, Mohamed O.; Amin, Mutaz; Mirghani, Yousra Abdelazim; Hassan, Mohamed A.

doi:10.1155/2016/9313746

Cited by 8 publications

(2 citation statements)

References 26 publications

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“…In cattle, it has been associated with temperament (flight speed) (9) and in humans in the functions of dopaminergic neurons due to the mutations in this gene associated with Parkinson's disease (29) .…”

Section: Park2mentioning

confidence: 99%

Identificación de genes candidatos y SNP relacionados con el temperamento del ganado utilizando un análisis GWAS junto con un análisis de redes interactuantes

Paredes-Sánchez

Sifuentes‐Rincón

Lara-Ramírez

et al. 2022

Rev. Mex. Cienc. Pecu.

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The objective of this study was to identify in Angus and Brangus breed animals with extreme temperament, measured as exit velocity, genomic regions and candidate genes associated with bovine temperament. The population was genotyped with the Genomic Profiler HD 150K chip and after the genome-wide association analysis, the SNPs rs133956611 (P=2.65 E-06) and rs81144933 (P=9.58 E-06) were associated with temperament. The mapping analysis of the regions close to the SNP rs81144933 identified the SNCA (alpha-synuclein) and MMRN1 (multimerin-1) genes at 222.8 and 435.9 Kb downstream respectively, while for the rs133956611 loci the gene GPRIN3 (GPRIN family-member-3) was identified at 245.7 Kb upstream, all three genes are located on the BTA6 chromosome. The analysis of SNCA protein-protein interactions allowed the identification of the genes APP (β-amyloid precursor protein), PARK7 (parkinsonism-associated-deglycase), UCHL1 (ubiquitin-C-terminal-hydrolase-L1), PARK2 (parkin-RBR- E3-ubiquitin-protein-ligase), and genes of the SLC family as candidates to be associated with bovine temperament. All these candidate genes and their interacting were resequenced, which allowed the discovery of new SNPs in the SNCA and APP genes. Of these, the SNPs located in introns 5, 8 and 11 of the APP gene affect splicing site motifs. These results indicate that SNCA and its interacting genes are candidates to be related to bovine temperament.

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Section: Park2mentioning

confidence: 99%

Identificación de genes candidatos y SNP relacionados con el temperamento del ganado utilizando un análisis GWAS junto con un análisis de redes interactuantes

Paredes-Sánchez

Sifuentes‐Rincón

Lara-Ramírez

et al. 2022

Rev. Mex. Cienc. Pecu.

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“…[5] In vitro functional and characterization studies, is a highly demanding task in terms of workload, time and financial cost. For these reasons, computational analysis is an appropriate alternative that is more rapid and low-cost approach, which is why it has been used to study many types of inheritance diseases in the past years [42][43][44] to enrich our knowledge of the ways mutations could affect protein structure and function. The main objective of this work was to classify the most damaging SNPs that could be used as diagnostic markers.…”

Section: Introductionmentioning

confidence: 99%

Novel Mutations within PRSS1 Gene that Could Potentially Cause Hereditary Pancreatitis: Using Bioinformatics Approach

Mustafa

Abdelmoneim²,

Elfadol

et al. 2019

Int. Ann. Sci.

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Hereditary pancreatitis (HP) is a rare heterogeneous disease with partial penetrance identified by frequent episodes of severe abdominal pain, often showing in young aged children. It is complicating by chronic pancreatitis, and high rate of pancreatic cancer (up to 40-50%). The aim of this work was to classify the most deleterious mutation in PRSS1 gene and to predict their influence on the functional and structural level by a variety of bioinformatics analysis tools. The raw data of PRSS1 gene were recovered from SNP database, and further used to examine a deleterious effect using SIFT, PolyPhen-2, PROVEAN, SNAP2, SNPs&GO, PHD-SNP, PANTHER and P-Mut. The functional analysis predicted that two SNPs “rs1366278558 and rs767036052” have a deleterious effect at functional level. Additionally, we submitted them to I-mutant 3.0, and MUPro respectively to investigate their effect on structural level; the two tools revealed that; two mutations have a dramatic decrease of the protein stability, thus suggesting that the M1R and L4P mutations of PRSS1 gene could destabilize the amino acid interactions causing functional abnormalities of PRSS1 protein. The 3D structure of PRSS1 was predicted by RaptorX and modeled using UCSF Chimera to compare the differences between the native and the mutant amino acids. From the comparative analysis at the functional and structural level, these two SNPs “M1R and L4P” have a deleterious effect and thus could be used as diagnostic markers to predict HP. These findings can be used as a platform to develop large-scale studies in the future.

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

Agrahari

Sneha

et al. 2017

Metab Brain Dis

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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.

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In Silico Analysis of SNPs in PARK2 and PINK1 Genes That Potentially Cause Autosomal Recessive Parkinson Disease

Cited by 8 publications

References 26 publications

Identificación de genes candidatos y SNP relacionados con el temperamento del ganado utilizando un análisis GWAS junto con un análisis de redes interactuantes

Identificación de genes candidatos y SNP relacionados con el temperamento del ganado utilizando un análisis GWAS junto con un análisis de redes interactuantes

Novel Mutations within PRSS1 Gene that Could Potentially Cause Hereditary Pancreatitis: Using Bioinformatics Approach

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

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