Abstract
There is a hope that inhibitors of the purinoreceptor P2X7, a ligand-gated ion channel, would have a beneficial role in the therapy of inflammatory processes. Therefore, the P2X7 channel is a putative drug target but neither X-ray nor NMR analyses have been made. It was attempted to predict the conformations of P2X receptor subunits using homology-based comparative modelling and threading. The modelling could not be carried out because of missing template proteins. The paper reviews a new method to predict the conformation of proteins. The method is exemplified on the human P2X7 (h-P2X7) receptor. The coordinates of the spatial structure of the h-P2X7 protein were determined by a profile-based neural network prediction. The conformation was geometry optimised using the quantum chemistry RHF/3-21G minimal basic set and allatom molecular mechanics AMBER force field. A dielectric constant of ε = 3.5 was used to simulate the lipophilic environment of the membrane-bound glycoprotein. The h-P2X7 protein has a number of interacting peptide modules. The discovery of peptide module raises the possibility of exploiting structure-based strategies to design h-P2X7 inhibitors.
Keywords: Sponge metabolites, Proteomics, Drug target, Human P2X7 receptor, Ligand-gated ion channel
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