Abstract
Background: In the recent years, histamine H3 receptor (H3R) has been receiving increasing attention in pharmacotherapy of neurological disorders. The aim of the current study was to investigate structural requirements for the prediction of H3 antagonistic activity using quantitative structure-activity relationship (QSAR) and molecular docking techniques. Methods: To this end, genetic algorithm coupled partial least square and stepwise multiple linear regression methods were employed for developing a QSAR model. The obtained QSAR model was stringently assessed using different validation criteria. Results: The generated model indicated that connectivity information and mean absolute charge are two important descriptors for the prediction of H3 antagonistic activity of the studied compounds. To gain insight into the mechanism of interaction between studied molecules and H3R, molecular docking was performed. The most important residues involved in the ligand-receptor interactions were identified. Conclusion: The result of current study can be used for designing of new H3 antagonist and proposing structural modifications to improve H3 inhibitory potency.
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