Istituto di Cristallografia - CNR

A novel approach for studying receptor-ligand interactions on living cells surface by using NUS/T1?-NMR methodologies combined with computational techniques: The RGDechi15D-?v?5 integrin complex

Structural investigations of receptor-ligand interactions on living cells surface by high-resolution Nuclear Magnetic Resonance (NMR) are problematic due to their short lifetime, which often prevents the acquisition of experiments longer than few hours. To overcome these limitations, we developed an on-cell NMR-based approach for exploring the molecular determinants driving the receptor-ligand recognition mechanism under native conditions. Our method relies on the combination of high-resolution structural and dynamics NMR data with Molecular Dynamics simulations and Molecular Docking studies. The key point of our strategy is the use of Non Uniform Sampling (NUS) and T1?-NMR techniques to collect atomic-resolution structural and dynamics information on the receptor-ligand interactions with living cells, that can be used as conformational constraints in computational studies. In fact, the application of these two NMR methodologies allows to record spectra with high S/N ratio and resolution within the lifetime of cells. In particular, 2D NUS [H-H] trNOESY spectra are used to explore the ligand conformational changes induced by receptor binding; whereas T1?-based experiments are applied to characterize the ligand binding epitope by defining two parameters: T1? Attenuation factor and T1? Binding Effect. This approach has been tested to characterize the molecular determinants regulating the recognition mechanism of ??-integrin by a selective cyclic binder peptide named RGDechi15D. Our data demonstrate that the developed strategy represents an alternative in-cell NMR tool for studying, at atomic resolution, receptor-ligand recognition mechanism on living cells surface. Additionally, our application may be extremely useful for screening of the interaction profiling of drugs with their therapeutic targets in their native cellular environment.

Computational and Structural Biotechnology Journal
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Farina B.; Andrea C.; Del Gatto A.; Comegna D.; Di Gaetano S.; Capasso D.; Paladino A.; Acconcia C.; Teresa Gentile M.; Saviano M.; Fattorusso R.; Zaccaro L.; Russo L.
Autori IC CNR