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Keywords:

  • missense mutation;
  • machine learning;
  • support vector machine;
  • protein structure;
  • protein stability;
  • phenylketonuria

Abstract

A previous computational analysis of missense mutations linked to monogenic disease found a high proportion of missense mutations affect protein stability, rather than other aspects of protein structure and function. The purpose of this study is to relate the presence of such stability damaging missense mutations to the levels of a particular protein present under “in vivo” like conditions, and to test the reliability of the computational methods. Experimental data on a set of missense mutations of the enzyme phenylalanine hydroxylase (PAH) associated with the monogenic disease phenylketonuria (PKU) have been compared with the expected in vivo impact on protein function, obtained using SNPs3D, an in silico analysis package. A high proportion of the PAH mutations are predicted to be destabilizing. The overall agreement between predicted stability impact and experimental evidence for lower protein levels is in accordance with the estimated error rates of the methods. For these mutations, destabilization of protein three-dimensional structure is the major molecular mechanism leading to PKU, and results in a substantial reduction of in vivo PAH protein concentration. Although of limited scale, the results support the view that destabilization is the most common mechanism by which missense mutations cause monogenic disease. In turn, this conclusion suggests the general therapeutic strategy of developing drugs targeted at restoring wild type stability. Proteins 2012;. © 2011 Wiley Periodicals, Inc.