Molecular modeling of histamine H3 receptor and QSAR studies on arylbenzofuran derived H3 antagonists

Dastmalchi, Siavoush, Hamzeh-Mivehroud, Maryam, Ghafourian, Taravat and Hamzeiy, Hossain (2007) Molecular modeling of histamine H3 receptor and QSAR studies on arylbenzofuran derived H3 antagonists. Journal of Molecular Graphics and Modelling, 26 (5). pp. 834-844. ISSN 1093-3263

Full text not available from this repository.

Abstract

Histamine H3 receptors are presynaptic autoreceptors found in both central and peripheral nervous systems of many species. The central effects of these receptors suggest a potential therapeutic role for their antagonists in treatment of several neurological disorders such as epilepsy, schizophrenia, Alzheimer's and Parkinson's diseases. The purpose of this study was to identify the structural requirements for H3 antagonistic activity via quantitative structure-activity relationship (QSAR) studies and receptor modeling/docking techniques. A combination of partial least squares (PLS) and genetic algorithm (GA) was used in the QSAR approach to select the structural descriptors relevant to the receptor binding affinity of a series of 58 H3 antagonists. The descriptors were selected out of a pool of >1000 descriptors calculated by DRAGON, Hyperchem and ACD labs suite of programs. The resulting QSAR models for rat and human H3 binding affinities were validated using different strategies. QSAR models generated in the current work suggested the role of charge transfer interactions in the ligand-receptor interaction verified using the molecular modeling of the receptor and docking two antagonists to the binding site. The 3D model of human H3 receptor was built based on bovine rhodopsin structure and evaluated by molecular dynamics (MD) simulation in a mixed water-vacuum-water environment. The results were indicative of the stability of the model relating the observed structural changes during the MD simulation to the suggested ligand-receptor interactions. The results of this investigation are expected to be useful in the process of design and development of new potent H3 receptor antagonists. © 2007 Elsevier Inc. All rights reserved.

Item Type: Article
Keywords: Charge transfer; Docking; Genetic algorithms; Molecular modeling; Neurology; Patient treatment; Three dimensional, Histamine H3 receptors; Partial least squares (PLS); Presynaptic autoreceptors, Amines, benzofuran derivative; histamine H3 receptor; histamine H3 receptor antagonist; rhodopsin, article; binding affinity; genetic algorithm; molecular docking; molecular dynamics; molecular model; partial least squares regression; priority journal; quantitative structure activity relation, Amino Acid Sequence; Animals; Benzofurans; Cattle; Cell Line; Cloning, Molecular; Histamine Antagonists; Humans; Ligands; Models, Molecular; Molecular Sequence Data; Protein Structure, Secondary; Pyrrolidines; Quantitative Structure-Activity Relationship; Rats; Receptors, Histamine H3; Rhodopsin; Sequence Alignment, Bovinae; Rattus
Schools and Departments: School of Life Sciences > Biochemistry
Depositing User: Taravat Ghafourian
Date Deposited: 30 Nov 2017 11:43
Last Modified: 30 Nov 2017 11:43
URI: http://sro.sussex.ac.uk/id/eprint/64150
📧 Request an update