Abstract

Because of their high resistance rate to the existing drugs, influenza A viruses have become a threat to human beings. It is known that the replication of influenza A viruses needs a pH-gated proton channel, the so-called M2 channel. Therefore, to develop effective drugs against influenza A, the most logic strategy is to inhibit the M2 channel. Recently, the atomic structure of the M2 channel was determined by NMR spectroscopy (Schnell, J.R. and Chou, J.J., Nature, 2008, 451, 591-595). The high-resolution NMR structure has provided a solid basis for structure-based drug design approaches. In this study, a benchmark dataset has been constructed that contains 34 newly-developed adamantane-based M2 inhibitors and covers considerable structural diversities and wide range of bioactivities. Based on these compounds, an in-depth analysis was performed with the newly developed fragment-based quantitative structure-activity relationship (FB-QSAR) algorithm. The results thus obtained provide useful insights for dealing with the drug-resistant problem and designing effective adamantane-based antiflu drugs.