Targeting Influenza Neuraminidase

Flu, in its seasonal or pandemic form, is a major threat as infectious disease. The pathogenicity of influenza A and B viruses - the causative agents of influenza - depends on the function of the neuraminidase (NA) enzyme. This protein catalyzes the detachment of sialic acid from the host cell, promotes the distribution of mature viruses and, thus, the spread of the infection. Influenza NA is established as the primary drug target for anti-viral treatment, with inhibitors such as oseltamivir and zanamivir on the market. These drugs are able to decrease the duration of infections and to considerably alleviate symptoms and transmission. The development of new potent inhibitors is critical, as emerging drug resistances due to mutations of the viral enzyme are continuously reported for approved inhibitors. During the past few years, enormous amounts of data and information on influenza NA have been gathered, indicating a number of weak points and features of influenza NA that have not been addressed in anti-viral drug design so far. Recently this fact has become even more obvious, when experimental and theoretical studies revealed the high structural flexibility of the protein that decisively affects chemical and geometric properties of the binding site. Computational approaches were already driving the development of the first generation of neuraminidase inhibitors and with the recent advancements in fundamental research on influenza NA today we are in the position to apply a plethora of theoretical and experimental approaches to identify next-generation inhibitor leads that are based on innovative rational design concepts. Stimulated by these striking developments we hereby propose a research project for the identification of smart next-generation NA inhibitors employing state-of-the art computational and experimental approaches. We will investigate reported mutations and how these impair drug action at an atomic level of detail and identify locations where such resistance-inducing mutations are likely to occur. These analyses will allow us to systematically exploit novel revealed weak points of NA for the development of smart inhibitors that target conserved residues on the protein side and, hence, face a substantially lower risk of developing drug resistance. We will pay special attention to protein flexibility that has so far largely kept drug design approaches from addressing masked NA subpockets and ligand binding features. Established virological testing systems and surface plasmon resonance technology will be employed to validate computational models and to characterize the binding properties of novel leads. The biological data will be implemented to our theoretical models in iterative feedback cycles in order to identify optimum lead structures of influenza NA inhibitors. In total, we will examine in vitro activity for 120 compounds and we anticipate characterizing 3 to 5 leads of next generation NA inhibitors.

Flu, in its seasonal or pandemic form, is a major threat as infectious disease. The pathogenicity of influenza A and B viruses - the causative agents of influenza - depends on the function of the neuraminidase (NA) enzyme. This protein catalyzes the detachment of sialic acid from the host cell, promotes the distribution of mature viruses and, thus, the spread of the infection. Influenza NA is established as the primary drug target for anti-viral treatment, with inhibitors such as oseltamivir and zanamivir on the market. These drugs are able to decrease the duration of infections and to alleviate symptoms and transmission. Together with our collaboration partner we could identify new inhibitors that not only inhibit viral neuraminidase but also bacterial neuraminidase. Such dual inhibitors can be the starting points for the development of drugs that simultaneously combat influenza and coinfections. To compare different neuraminidases we employed different computer-aided techniques. We especially used methods that explicitly consider protein flexibility, as it is essential for the inhibitors interaction with the enzyme. These methods not only helped to identify inhibitors and to explain their mode of action, but also to rationalize their different behavior towards different neuraminidase enzymes.Neuraminidase is a target with especially pronounced flexibility and thus the application of simulation techniques is especially intriguing and but also challenging. Also for other targets the biological and pharmacological response is influenced by protein flexibility. Hence during the project also other targets were investigated to optimize the computational techniques. In this way during the project we could not only advance the knowledge on new influenza neuraminidase inhibitors, but we could also underline the importance of protein flexibility for the interactions during molecular recognition and for the identification of new lead structure by virtual techniques.