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A gene-specific method for predicting hemophilia-causing point mutations.


ABSTRACT: A fundamental goal of medical genetics is the accurate prediction of genotype-phenotype correlations. As an approach to develop more accurate in silico tools for prediction of disease-causing mutations of structural proteins, we present a gene- and disease-specific prediction tool based on a large systematic analysis of missense mutations from hemophilia A (HA) patients. Our HA-specific prediction tool, HApredictor, showed disease prediction accuracy comparable to other publicly available prediction software. In contrast to those methods, its performance is not limited to non-synonymous mutations. Given the role of synonymous mutations in disease and drug codon optimization, we propose that utilizing a gene- and disease-specific method can be highly useful to make functional predictions possible even for synonymous mutations. Incorporating computational metrics at both nucleotide and amino acid levels along with multiple protein sequence/structure alignment significantly improved the predictive performance of our tool. HApredictor is freely available for download at http://www.ncbi.nlm.nih.gov/CBBresearch/Przytycka/HA_Predict/index.htm.

SUBMITTER: Hamasaki-Katagiri N 

PROVIDER: S-EPMC4029106 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature

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A gene-specific method for predicting hemophilia-causing point mutations.

Hamasaki-Katagiri Nobuko N   Salari Raheleh R   Wu Andrew A   Qi Yini Y   Schiller Tal T   Filiberto Amanda C AC   Schisterman Enrique F EF   Komar Anton A AA   Przytycka Teresa M TM   Kimchi-Sarfaty Chava C  

Journal of molecular biology 20130803 21


A fundamental goal of medical genetics is the accurate prediction of genotype-phenotype correlations. As an approach to develop more accurate in silico tools for prediction of disease-causing mutations of structural proteins, we present a gene- and disease-specific prediction tool based on a large systematic analysis of missense mutations from hemophilia A (HA) patients. Our HA-specific prediction tool, HApredictor, showed disease prediction accuracy comparable to other publicly available predic  ...[more]

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