Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5809826 | European Journal of Pharmaceutical Sciences | 2015 | 14 Pages |
â¢The program of Surflex-Dock was utilized to decipher the recognition patterns of target α7 nAChR-antagonists.â¢The interaction energies of the α7 nAChR-antagonists were acquired based upon the data of molecular dynamics simulation.â¢Residues B/Tyr-93, B/Trp-147 and B/Tyr-188 were proved to be pivotal to the α7 nAChR-antagonists recognitions.â¢Both the structure-based alignment and the docking-based alignment methods were used to structure 3D-QSAR models.â¢These attempts can be employed to create novel nAChR antagonists and further excavate antagonistic mechanism.
As the key constituent of ligand-gated ion channels in the central nervous system, nicotinic acetylcholine receptors (nAChRs) and neurodegenerative diseases are strongly coupled in the human species. In recently years the developments of selective agonists by using nAChRs as the drug target have made a large progress, but the studies of selective antagonists are severely lacked. Currently these antagonists rest mainly on the extraction of partly natural products from some animals and plants; however, the production of these crude substances is quite restricted, and artificial synthesis of nAChR antagonists is still one of the completely new research fields. In the context of this manuscript, our primary objective was to comprehensively analyze the recognition patterns and the critical interaction descriptors between target α7 nAChR and a series of the novel compounds with potentially antagonistic activity by means of virtual screening, molecular docking and molecular dynamics simulation, and meanwhile these recognition reactions were also compared with the biointeraction of α7 nAChR with a commercially natural antagonist - methyllycaconitine. The results suggested clearly that there are relatively obvious differences of molecular structures between synthetic antagonists and methyllycaconitine, while the two systems have similar recognition modes on the whole. The interaction energy and the crucially noncovalent forces of the α7 nAChR-antagonists are ascertained according to the method of Molecular Mechanics/Generalized Born Surface Area. Several amino acid residues, such as B/Tyr-93, B/Lys-143, B/Trp-147, B/Tyr-188, B/Tyr-195, A/Trp-55 and A/Leu-118 played a major role in the α7 nAChR-antagonist recognition processes, in particular, residues B/Tyr-93, B/Trp-147 and B/Tyr-188 are the most important. These outcomes tally satisfactorily with the discussions of amino acid mutations. Based on the explorations of three-dimensional quantitative structure-activity relationships, the structure-antagonistic activity relationships of antagonists and the characteristics of α7 nAChR-ligand recognitions were received a reasonable summary as well. These attempts emerged herein would not only provide helpful guidance for the design of α7 nAChR antagonists, but shed new light on the subsequent researches in antagonistic mechanism.
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