Copyright
©The Author(s) 2015.
World J Med Genet. Aug 27, 2015; 5(3): 46-51
Published online Aug 27, 2015. doi: 10.5496/wjmg.v5.i3.46
Published online Aug 27, 2015. doi: 10.5496/wjmg.v5.i3.46
Table 1 Examples of freely available, online tools for predicting the properties of variant proteins
| Category | Name | Weblink | Ref. |
| Structural analysis | YASARA energy minimisation | http://www.yasara.org/minimizationserver.htm | [29] |
| LS-SNP | ls-snp.icm.jhu.edu/ls-snp-pdb/main | [30] | |
| GETAREA | curie.utmb.edu/getarea.html | [31] | |
| Stability prediction | I-Mutant 3.0 | gpcr2.biocomp.unibo.it/cgi/predictors/I-Mutant3.0/I-Mutant3.0.cgi | [32,33] |
| mCSM | bleoberis.bioc.cam.ac.uk/mcsm/ | [34] | |
| SDM score | mordred.bioc.cam.ac.uk/~sdm/sdm.php | [35,36] | |
| Mupro | mupro.proteomics.ics.uci.edu | [37] | |
| iStable | predictor.nchu.edu.tw/iStable/ | [38] | |
| PredictSNP 1.0 | loschmidt.chemi.muni.cz/predictsnp/ | [39] | |
| Meta-SNP | snps.biofold.org/meta-snp/ | [40] | |
| KD4V | decrypthon.igbmc.fr/kd4v | [41] | |
| Fold-X | foldx.crg.es | [42] | |
| PoPMuSiC | dezyme.com/ | [43] | |
| CUPSAT | cupsat.tu-bs.de | [44,45] | |
| GETAREA | curie.utmb.edu/getarea.html | [31] | |
| Binding affinity changes | BeAtMuSiC | babylone.ulb.ac.be/beatmusic | [46] |
| Aggregation tendency, amyloid formation and chaperone binding | TANGO | tango.crg.es/ | [47] |
| WALTZ | http://www.switchlab.org/bioinformatics/waltz | [48] | |
| LIMBO | http://www.switchlab.org/bioinformatics/limbo | [49] | |
| Sequence conservation | Clustal Omega | http://www.ebi.ac.uk/tools/msa/clustalo/ | [50] |
| Scorecons | http://www.ebi.ac.uk/thornton-srv/databases/cgi-bin/valdar/scorecons_server.pl | [51] | |
| SIFT | sift.jcvi.org/ | [52] | |
| PROVEAN | provean.jcvi.org/index.php | [53] | |
| LS-SNP | ls-snp.icm.jhu.edu/ls-snp-pdb/ | [30] | |
| SNPs and GO | snps.biofold.org/snps-and-go/pages/help.html | [54] | |
| PANTHER | http://www.pantherdb.org/tools/csnpscoreform.jsp | [55] | |
| GenMAPP | http://www.genmapp.org | [56] | |
| PolyPhen 2 | genetics.bwh.harvard.edu/pph2/ | [57,58] | |
| nsSNP Analyzer | snpanalyzer.uthsc.edu | [59] | |
| FI mutation assessor | mutationassessor.org/v1 | [60] | |
| YALE MU2A | krauthammerlab.med.yale.edu/mu2a | [61] |
Table 2 Examples of bioinformatics based predictions of the severity of variants associated with inherited metabolic diseases
| Disease | Protein | Comments | Ref. |
| Alkaptonuria | Homogentisate 1,2-dioxygenase | Combining a variety of computational approaches gave rise to the most accurate predictions | [62] |
| Apparent mineralocorticoid excess | 11βHSD2 | The predicted degree of structural change in the enzyme correlates with disease severity | [63] |
| Fabry disease | GLA | A purpose built program designed to detect protein instability outperformed existing, generic tools | [64] |
| Fabry disease | GLA | A purpose built web interface allows prediction of a patient’s responsiveness to pharmacological chaperone therapy | [65] |
| Gaucher disease | GBA | Slightly different results were obtained with different programs; however, 22 out of 47 variants were predicted to be harmful by all seven programs used | [28] |
| Glucose 6-phosphate dehydrogenase deficiency | G6PDH | A combination of prediction tools suggested that protein stability is an important factor in this disease; novel potentially disease-associated variants were identified | [66] |
| Hyperargininemia | ARG1 | Mutations affect residues in the active site, or protein stability, or quaternary structure | [67] |
| MODY 2 | GCK | Variations which decrease protein stability and/or occur in highly conserved regions of the protein are associated with disease | [68] |
| Niemann-pick disease type C | NPC1 and NPC2 | The majority of disease-associated variants were predicted to be less stable than wild-type | [69] |
| Phenylketonuria | PAH | Protein stability predicted to be most important factor in disease causation | [10] |
| Pyruvate kinase deficiency | PK1 and PK2 | A combination of prediction tools suggested that protein stability is an important factor in this disease; novel potentially disease-associated variants were identified | [66] |
| Type I galactosemia | GALT | Main predicted effect is the loss of stability of GALT | [70] |
| Type III galactosemia | GALE | Effects on protein stability and degree of sequence conservation combined were required for good predictions | [71] |
- Citation: Timson DJ. Value of predictive bioinformatics in inherited metabolic diseases. World J Med Genet 2015; 5(3): 46-51
- URL: https://www.wjgnet.com/2220-3184/full/v5/i3/46.htm
- DOI: https://dx.doi.org/10.5496/wjmg.v5.i3.46
