The Swiss-Prot variant page and the ModSNP database: A resource for sequence and structure information on human protein variants

Yip, Yum Lina; Scheib, Holger; Diemand, Alexander; Gattiker, Alexandre; Famiglietti, Livia; Gasteiger, Elisabeth; Bairoch, Amos Marc

doi:10.1002/humu.20021

Cited by 123 publications

(114 citation statements)

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“…Where available, we also stored start and end positions of exons and directions of mRNA on contig sequences. From the corresponding receptor entries, data on small variants at the gene and/or protein level were extracted from dbSNP [Sherry et al, 1999], OMIM [Pearson et al, 1994], HGMD [Cooper et al, 1998], UniProt/SwissProt [Yip et al, 2004], and tGRAP [Edvardsen et al, 2002]. Available disease associations were retrieved.…”

Section: Data Sourcesmentioning

confidence: 99%

“…Apart from the highly detailed locus-specific databases on GPCR variants that are reported in Table 1 [Fuhrer et al, 2003;Oetting, 2002;Pidasheva et al, 2004], the variety of online sources is evident from general databases that contain subsets of variants. Individual general databases contain rare disease-causing mutations [Cooper et al, 1998;Pearson et al, 1994], small genetic variants [HapMap Consortium, 2003;Sherry et al, 1999], CNVs [Iafrate et al, 2004], and other selections of variants [Yip et al, 2004]. An additional wealth of data on natural variants is reported in the scientific literature and patents, but these data are not easily captured in a database.…”

Section: Introductionmentioning

confidence: 99%

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GPCR NaVa database: natural variants in human G protein-coupled receptors

et al. 2007

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Communicated by Mauno VihinenThe superfamily of human G protein-coupled receptors (GPCRs) is large and regulates a plethora of important physiological processes by transducing extracellular signals over cell membranes. A diversity of natural variants occurs in these receptors, including rare mutations and common polymorphisms. These variants differ in their impact on DNA, ranging from single nucleotide polymorphisms (SNPs) to copy number variants, and in their impact on protein function. Natural variants furthermore vary in their effects on human phenotypes from neutral to disease-associated. As mutation data are highly dispersed over numerous sources, a single resource for variants would aid investigators of GPCRs. The GPCR NaVa database therefore integrates data on natural variants in human GPCRs from online databases, the scientific literature, and patents. Where available, variants contain information on their location in the DNA (and protein sequence), the involved nucleotides (and amino acids), the average frequency of each allele, reported disease associations, and references to public databases and the scientific literature. The GPCR NaVa database aims to facilitate studies into pharmacogenetics, genotype-phenotype, and structure-function relationships of GPCRs. The GPCR NaVa database is interlinked with the family-specific GPCRDB resource and is accessible as a stand-alone database through a user-friendly website at http://nava.

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Section: Data Sourcesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

GPCR NaVa database: natural variants in human G protein-coupled receptors

et al. 2007

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“…The segments of every Swissprot entry imparted details on polymorphic variants, some of which were disease(s) -associated by causing defects in a given protein (Yip et al, 2004(Yip et al, , 2008Boeckmann et al, 2003). The 3D structure of angiogenin and their complexes were extracted from Protein Data Bank with PDB ID 2ANG (Berman et al, 2000) for mutant modeling and docking studies according to harmful point mutants.…”

Section: Datasetsmentioning

confidence: 99%

A computational approach to analyze the missense mutations in human angiogenin variants leading to amyotrophic lateral sclerosis

Sreevishnupriya

Rajasekaran

2013

Bangladesh J Pharmacol

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A computational approach to analyze the missense mutations in human angiogenin variants leading to amyotrophic lateral sclerosis BJP IntroductionAmyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by selective destruction of motor neurons, resulting paralysis in stages and death within a few years from onset (Bruijin et al., 2004). In the past decade, a small number of genes involved in the etiology of the disease have been identified. Angiogenin (ANG), which encodes an angiogenic protein, has been recently identified as a candidate susceptibility gene for ALS in the Irish and Scottish population by Greenway et al (Greenway et al., 2004).The ANG gene provides instructions for making a protein called angiogenin. This protein promotes the formation of new blood vessels from pre-existing blood vessels through a process called angiogenesis. The ANG gene is located on the long (q) arm of chromosome 14 between positions 11.1 and 11.2. More precisely, the ANG gene is located from base pair 21,152,335 to base pair 21,162,344 on chromosome 14.The protein aggregation, defective axonal transport, oxidative stress, dysfunctional growth factor signaling, mitochondrial dysfunction and excitotoxicity are some of the factors found to be combined to the inception of ALS.Around 10% of ALS cases are inherited genetically, but the other 90% have no clear genetic cause (Dion et al., 2009 AbstractThe most deleterious missense mutations of angiogenin forming amyotrophic lateral sclerosis were identified computationally and the substrate binding efficiencies of these mutations were also analyzed. Out of 12 variants, IMutant2.0, SIFT and PolyPhen programs identified 3 variants that were less stable, deleterious and damaging respectively. These 3 variants were modeled to find their conformational changes in concern with native angiogenin through RMSD calculation and Total energy. Docking of native and 3 mutants with ribonuclease inhibitor was performed to describe the binding efficiencies of those detrimental missense mutations. By computing the binding amino acids' flexibility of angiogenin and computing the binding free energy (ΔG)between native and mutant complexes, the loss in binding affinity with their interacting protein namely ribonuclease inhibitor was investigated. This work is licensed under a Creative Commons Attribution 3.0 License. You are free to copy, distribute and perform the work. You must attribute the work in the manner specified by the author or licensor. Article Info

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“…The ASPA protein and 30 variants, namely, I16T, H21P, E24G, G27R, A57T, D68A, D114E, D114Y, G123E, I143T, C152R, C152W, C152Y, R168C, R168H, P181T, P183H, V186F, M195R, Y231C, H244R, D249V, G274R, P280L, P280S, E285A, A287T, F295S, A305E and C310G investigated in this work were retrieved from the Swissprot database [20][21][22].…”

Section: The Sap Data Set From Swissprotmentioning

confidence: 99%

Computational analysis of deleterious missense mutations in aspartoacylase that cause Canavan’s disease

Sreevishnupriya

Chandrasekaran

Senthilkumar

et al. 2012

Sci. China Life Sci.

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In this work, the most detrimental missense mutations of aspartoacylase that cause Canavan's disease were identified computationally and the substrate binding efficiencies of those missense mutations were analyzed. Out of 30 missense mutations, I-Mutant 2.0, SIFT and PolyPhen programs identified 22 variants that were less stable, deleterious and damaging respectively. Subsequently, modeling of these 22 variants was performed to understand the change in their conformations with respect to the native aspartoacylase by computing their root mean squared deviation (RMSD). Furthermore, the native protein and the 22 mutants were docked with the substrate NAA (N-Acetyl-Aspartic acid) to explain the substrate binding efficiencies of those detrimental missense mutations. Among the 22 mutants, the docking studies identified that 15 mutants caused lower binding affinity for NAA than the native protein. Finally, normal mode analysis determined that the loss of binding affinity of these 15 mutants was caused by altered flexibility in the amino acids that bind to NAA compared with the native protein. Thus, the present study showed that the majority of the substrate-binding amino acids in those 15 mutants displayed loss of flexibility, which could be the theoretical explanation of decreased binding affinity between the mutant aspartoacylases and NAA. missense mutation, Canavan's disease, aspartoacylase, NAA, flexibility Citation:Sreevishnupriya K, Chandrasekaran P, Senthilkumar A, et al. Computational analysis of deleterious missense mutations in aspartoacylase that cause Canavan's disease.

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The Swiss-Prot variant page and the ModSNP database: A resource for sequence and structure information on human protein variants

Cited by 123 publications

References 31 publications

GPCR NaVa database: natural variants in human G protein-coupled receptors

GPCR NaVa database: natural variants in human G protein-coupled receptors

A computational approach to analyze the missense mutations in human angiogenin variants leading to amyotrophic lateral sclerosis

Computational analysis of deleterious missense mutations in aspartoacylase that cause Canavan’s disease

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