Pentameric ligand-gated ion channels (pLGICs) are a family of membrane proteins that mediate the fast synaptic communication between neurons. The delicate role played by these neuroreceptors makes them major therapeutic targets for a variety of neuronal disorders, including Alzheimer's disease, which can be attributed to flaws in neuronal signalling. pLGICs are formed by five subunits arranged around an ion permeable pore and are activated by the binding of small molecules, the neurotransmitters, which triggers a wave of conformational changes culminating with the opening (gating) of the ion channel. In spite of their importance, we still have a very limited understanding of their behaviour and only in recent years the availability of structural information from experiments and progress in computational methods are opening new possibilities to tackle their complexity at the atomic level. In this project, we investigated the activation mechanisms of prototypical pLGICs with the aid of a number of state-of-the-art and novel computational techniques. In particular, molecular dynamics and metadynamics, a powerful enhanced sampling method to accelerate rare events, were employed to study the binding process of the neurotransmitter GABA to the insect RDL receptor, complementing mutagenesis electrophysiology experiments; binding free energy landscapes and anities were evaluated both for the wild-type and selected mutants and plausible binding paths were identified. The role of the trans-cis isomerisation of a highly conserved proline on the gating of the serotonin-activated 5-HT3 receptor was also explored with metadynamics. Experiments found this single process to be crucial for the correct functioning of the gate and our simulations showed a correlation between the isomerisation of this proline and conformational changes in the helices lining the pore. Understanding the conformational preference of protein building blocks may thus hold the key to fully comprehend the behaviour of whole receptors. Hence, a novel protocol, based on metadynamics and the dimensionality reduction algorithm sketchmap, was developed to map the conformational free energy of amino acids. As an example, it was applied here to aspartic acid, for which a number of stable conformers, including those experimentally observed with rotational spectroscopy, were identified. The results obtained in this thesis contribute to the fundamental understanding of pLGICs by helping unravel the complexity of the neurotransmitter binding and channel gating processes. Given the number of experimental structures recently made avalable, they are particlarly timely in paving the way for future studies on this important family of proteins.
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