The geometry optimized P2X3 receptor subunit is freely available for academic researchers on e-mail request (PDB format).
The methods of bioinformatics, molecular modelling, and quantitative structure-activity relationships (QSARs) using regression and artificial neural network (ANN) analyses were applied to develop safer aldoxime antidotes against poisoning by organophosphorus (OP) agents with high, mean, and low aging rates. We start here from a molecular modelling of the mouse AChE at an atomistic level. Aim is to predict qualitatively the structural requirements of an aldoxime that shows an unique reactivating activity against the three classes of OPs. An antidotal action should occur by a three-site mechanism: the aldoxime groups of the first pyridinium ring should point towards the catalytic site, and the second pyridinium ring and its substituents should be anchored at the peripherical and anionic subsites. Based on this model, it is predicted that a suitable substituent is based on an arginine-like moiety. Then, an ANN-based QSAR analysis using a training set of aldoximes with known structure and activities was applied. Its input layer consisted of seven nodes: the group-membership descriptors that parameterize the type of the OP, the logarithms of the distribution coefficients at pH 7.4 and their squared term, the lowest unoccupied molecular orbital (LUMO) energies, the scaled molar refractions of the substituents, and their squared term. It was shown that the qualitative prediction made by molecular modelling can be quantified by an ANN prediction.
The methods of bioinformatics, molecular modelling, and quantitative structure-activity relationships (QSARs) using regression and artificial neural network (ANN) analyses were applied to develop safer aldoxime antidotes against poisoning by organophosphorus (OP) agents with high, mean, and low aging rates. We start here from a molecular modelling of the mouse AChE at an atomistic level. Aim is to predict qualitatively the structural requirements of an aldoxime that shows an unique reactivating activity against the three classes of OPs. An antidotal action should occur by a three-site mechanism: the aldoxime groups of the first pyridinium ring should point towards the catalytic site, and the second pyridinium ring and its substituents should be anchored at the peripherical and anionic subsites. Based on this model, it is predicted that a suitable substituent is based on an arginine-like moiety. Then, an ANN-based QSAR analysis using a training set of aldoximes with known structure and activities was applied. Its input layer consisted of seven nodes: the group-membership descriptors that parameterize the type of the OP, the logarithms of the distribution coefficients at pH 7.4 and their squared term, the lowest unoccupied molecular orbital (LUMO) energies, the scaled molar refractions of the substituents, and their squared term. It was shown that the qualitative prediction made by molecular modelling can be quantified by an ANN prediction.
There is evidence that the P2X1 receptor subunit is involved in apoptosis, platelet aggregation, and smooth muscle contraction. The conformation of the membrane-embedded, ligand-gated mouse P2X1 glycoprotein, a monovalent-bivalent cation channel-forming receptor, is predicted. The first step is based on secondary structure prediction. The secondary structure is converted into a three-dimensional geometry. Then, the secondary and tertiary structures are optimized by using the quantum chemistry RHF/3-21G minimal basic set and the all-atom molecular mechanics AMBER96 force field. The fold of the membrane-embedded protein is simulated by a suitable dielectric. The structure is refined using a conjugate gradient minimizer (Fletcher-Reeves modification of the Polak-Ribiere method). Although the mouse P2X1 receptor subunit is more complex (388 amino acids) than the KcsA protein (160 amino acids), the overall folds are similar. The geometry optimized P2X1 receptor subunit is freely available for academic researchers on e-mail request (PDB format).
The membrane-embedded, ligand-gated P2X glycoprotein receptor is a monovalent-bivalent cation channel that is activated by physiological concentrations of extracellular ATP. A quantitative structure-activity relationship (QSAR) analysis was developed to model the cation permeability of the P2X2 channel and its mutants. As chemical properties, the helix-coil equilibrium constants and the distribution coefficients of the system octanol/water at pH 7.4 were applied and modified (sliding windows) according to Eroshkin et al. (Comput. Appl. Biosci., 1995, 11, 49-44). The results were visualized by a dimeric P2X2 channel construct. The results support the hypothesis that residues which put into the cavity and contribute to hydrogen bonding forces are involved to a control of the transport of hydrated cations through the P2X2 channel. The model may be useful to develop P2X2 receptor antagonists.
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