Presumably due to the capability of the hepatitis C virus (HCV) to evade the antiviral effects of alpha interferon, treatment is ineffective in more than half of chronically genotype HCV type 1 (HCV-1)-infected patients. Previous approaches to correlate the number of amino acid mutations within regions of HCV nonstructural (NS)-5A protein with virologic treatment response provided conflicting results. In the present study, we developed a new mathematical model to investigate NS5A sequences of HCV-1-infected patients. The mean number of all mutations within the complete NS5A protein was significantly higher in virologic responders compared to nonresponders (P = 0.008 and P = 0.0001 for amino acid residues predicted on the surface of the NS5A protein). Differences did not achieve statistical significance for NS5A regions that are currently assumed to be functionally relevant (e.g., the interferon sensitivity-determining region, the RNA-activated protein kinase-binding domain, etc.). Analyses of smoothed mutational frequencies showed that the number of mutations in other NS5A regions correlated with virologic response. Such a correlation was observed for both genuine and randomly generated NS5A sequences. The existence of local accumulations of mutations within genuine NS5A isolates that truly correlated with treatment response was defined by a refined test procedure. Upon considering the predicted residue accessibility, we identified the main focus of mutations correlating with treatment response to be the sequence from amino acids 2350 to 2370. Thus, evaluation of NS5A mutations in correlation with treatment response is improved by consideration of functional and predicted conformational amino acid properties. As shown by simulations with randomly generated sequences, multiple analyses of simple counts of local NS5A amino acid mutations and correlation with treatment response are insufficient. For improvement of mutational analysis, a refined specific functional data test procedure is proposed.