ArticleBMC bioinformatics2016
Convert your favorite protein modeling program into a mutation predictor: "MODICT".
Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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7 authors at 3 institutions in 3 countries.
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Abstract
backgroundPredict whether a mutation is deleterious based on the custom 3D model of a protein.
resultsWe have developed MODICT, a mutation prediction tool which is based on per residue RMSD (root mean square deviation) values of superimposed 3D protein models. Our mathematical algorithm was tested for 42 described mutations in multiple genes including renin (REN), beta-tubulin (TUBB2B), biotinidase (BTD), sphingomyelin phosphodiesterase-1 (SMPD1), phenylalanine hydroxylase (PAH) and medium chain Acyl-Coa dehydrogenase (ACADM). Moreover, MODICT scores corresponded to experimentally verified residual enzyme activities in mutated biotinidase, phenylalanine hydroxylase and medium chain Acyl-CoA dehydrogenase. Several commercially available prediction algorithms were tested and results were compared. The MODICT PERL package and the manual can be downloaded from https://github.com/IbrahimTanyalcin/MODICT .
conclusionsWe show here that MODICT is capable tool for mutation effect prediction at the protein level, using superimposed 3D protein models instead of sequence based algorithms used by POLYPHEN and SIFT.
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