ABCMdb

ABCA1 p.Arg306His

Predicted by SNAP2:	A: D (59%), C: D (66%), D: D (63%), E: N (53%), F: D (66%), G: D (75%), H: D (66%), I: D (71%), K: N (61%), L: D (63%), M: D (71%), N: D (53%), P: D (71%), Q: N (53%), S: N (61%), T: D (53%), V: D (63%), W: D (91%), Y: D (85%),
Predicted by PROVEAN:	A: N, C: N, D: N, E: N, F: D, G: N, H: N, I: D, K: N, L: D, M: N, N: N, P: N, Q: N, S: N, T: N, V: D, W: D, Y: N,

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[hide] Accurate prediction of the functional significance... PLoS Genet. 2005 Dec;1(6):e83. Epub 2005 Dec 30. Brunham LR, Singaraja RR, Pape TD, Kejariwal A, Thomas PD, Hayden MR
Accurate prediction of the functional significance of single nucleotide polymorphisms and mutations in the ABCA1 gene.
PLoS Genet. 2005 Dec;1(6):e83. Epub 2005 Dec 30., [PMID:16429166]

Abstract [show]
The human genome contains an estimated 100,000 to 300,000 DNA variants that alter an amino acid in an encoded protein. However, our ability to predict which of these variants are functionally significant is limited. We used a bioinformatics approach to define the functional significance of genetic variation in the ABCA1 gene, a cholesterol transporter crucial for the metabolism of high density lipoprotein cholesterol. To predict the functional consequence of each coding single nucleotide polymorphism and mutation in this gene, we calculated a substitution position-specific evolutionary conservation score for each variant, which considers site-specific variation among evolutionarily related proteins. To test the bioinformatics predictions experimentally, we evaluated the biochemical consequence of these sequence variants by examining the ability of cell lines stably transfected with the ABCA1 alleles to elicit cholesterol efflux. Our bioinformatics approach correctly predicted the functional impact of greater than 94% of the naturally occurring variants we assessed. The bioinformatics predictions were significantly correlated with the degree of functional impairment of ABCA1 mutations (r2 = 0.62, p = 0.0008). These results have allowed us to define the impact of genetic variation on ABCA1 function and to suggest that the in silico evolutionary approach we used may be a useful tool in general for predicting the effects of DNA variation on gene function. In addition, our data suggest that considering patterns of positive selection, along with patterns of negative selection such as evolutionary conservation, may improve our ability to predict the functional effects of amino acid variation.

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110 DOI: 10.1371/journal.pgen.0010083.g003 Table 3. subPSEC Scores for ABCA1 Variants Described in a Cohort of Individuals with Low HDL Cholesterol from the General Population Variant subPSEC Score Macrophage Efflux PolyPhen D1706N À6.57 0.38a Possibly damaging C1477F À5.55 0.34a Probably damaging W590S À5.19 - Probably damaging H551D À4.99 0.32a Probably damaging P85L À4.62 0.8 Probably damaging W590L À4.48 0.31a Probably damaging N1800H À4.23 0.27a Possibly damaging R965C À4.22 0.59 Probably damaging S1731C À4.21 0.28a Possibly damaging A1670T À4.2 - Possibly damaging K401Q À4.2 - Benign T459P À4.11 0.28a Possibly damaging R638Q À4.08 - Possibly damaging L1026P À3.86 0.25a Benign T2073A À3.84 0.28a Possibly damaging E815G À3.53 - Probably damaging R1615Q À3.45 - Possibly damaging S1181F À3.44 - Possibly damaging R306H À3.31 - Benign E1386Q À2.44 0.51 Benign S1376G À2.19 - Benign R1341T À2.09 - Possibly damaging D2243E À1.6 - Benign P248A À0.18 - Benign a Efflux value is 2 SDs or more below control levels of 0.52 6 0.07. Login to comment