Hepatitis C virus (HCV) infection is a major and rising global health problem, affecting about 170 million people worldwide. The current standard of care treatment with interferon alpha and ribavirin in patients with the genotype 1 infection, the most frequent genotype in the USA and Western Europe, leads to a successful outcome in only about 50% of individuals. Accurate prediction of hepatitis C treatment response is of great benefit to patients and clinicians. The informational spectrum method, a virtual spectroscopy method for structure/function analysis of nucleotide and protein sequences, is applied here for the identification of the conserved information of the HCV proteins that correlate with the combination therapy outcome. Among the HCV proteins that we have analyzed the informational property of the p7 of HCV genotype 1b was best related to the therapy outcome. On the basis of these results, a simple bioinformatics criterion that could be useful in assessment of the response of HCV-infected patients to the combination therapy has been proposed.