E3 Journal of Biotechnology and Pharmaceutical Research

E3 Journal of Biotechnology and Pharmaceutical Research Vol. 3 (2) pp. 22 - 27, April 2012; © E3 Journals; ISSN 2141-7474

Generating a 3D structure model of Histamine-4 receptor for Antiinflammatory Drug Design

Abstract

Histamine-4 receptor (H4R) belongs to the GPCRs (G protein-coupled receptors) family. The H4R involved in allergic pathogenesis, autoimmune diseases such as arthritis, type-I allergic diseases such as asthma, conjunctivitis, and rhinitis. This macromolecule has never been crystallized yet. In drug design, the need to obtain 3D structure of macromolecules is to bridge the gap of ligand- and receptor-based methods. Three-dimensional structure of the target is essential for defining the active site and also for designing, improving, and docking of small ligands to the complex target protein. This study was aimed to generate H4R 3D structure that fulfilled the quality parameters of DOPE and QMEAN by using homology modeling principles. The method used in this work was performed in several steps as follows: (1) searching for the H4R sequence data and identifying protein structures similar to the data to be used as templates for H4R; (2) automatic sequence alignment to calculate the similarity between the templates and H4R sequence; (3) building the H4R 3D structure models using SWISS-MODEL and MODELLER 9v7; and (4) validating the 3D structure models by using DOPE, QMEAN, and Ramachandran plot. This study produced four H4R models that were validated by Ramachandran plot. The best model was applied to dock histamine by using AutoDock 4.0.It could be concluded from this work that 3D structure of H4R was able to be generated and applied to dock histamine in its predicted active site. The active site consists of six amino acid residues which are Asp94, Tyr95, Glu182, Trp316, Tyr319, and Phe344. Its agonist, histamine, is bound in the binding site of this protein via the formation of two hydrogen bonds with Asp94 and Tyr319.

Keywords: H4R 3D structure, homology modeling, histamine