Computational investigation of interactions between human H2 receptor and its agonists

Sun, Xianqiang; Li, Yaozong; Li, Weihua; Xu, Zhejun; Tang, Yun

doi:10.1016/j.jmgm.2010.12.001

Cited by 18 publications

(13 citation statements)

References 48 publications

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“…In a more recent study, a homology model of H2R was constructed based on the β1-adrenergic receptor [27]. The authors combined a pharmacophore model with structure-based modeling using induced fit docking and MD simulations on selected H2 agonists.…”

Section: H2 Receptormentioning

confidence: 99%

Structure-based discovery and binding site analysis of histamine receptor ligands

Kingsford-Adaboh

Keserü

2016

Expert Opinion on Drug Discovery

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Introduction: Application of structure-based drug discovery in histamine receptor projects was previously hampered by the lack of experimental structures. The publication of the first X-ray structure of the histamine H1 receptor has been followed by several successful virtual screens and binding site analysis studies of H1-antihistamines. This structure together with several other recently solved aminergic G-protein coupled receptors (GPCRs) enabled the development of more realistic homology models for H2, H3 and H4 receptors. Areas covered: In this paper, we review the development of histamine receptors models and their application on drug discovery. Expert opinion: In our opinion, the application of atomistic histamine receptor models played a significant role in understanding key ligand-receptor interactions as well as in the discovery of novel chemical starting points. The recently solved H1 receptor structure is a major milestone in structure-based drug discovery, however our analysis also demonstrate that for building H3 and H4 receptor homology models other GPCRs may be more suitable as a template. For these receptors we envisage that the development of higher quality homology models will significantly contribute to the discovery and optimization of novel H3 and H4 ligands.

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Section: H2 Receptormentioning

confidence: 99%

Structure-based discovery and binding site analysis of histamine receptor ligands

Kingsford-Adaboh

Keserü

2016

Expert Opinion on Drug Discovery

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“…However, the Glide program was not covered in their study. As Glide is a popular docking method that has performed well in numerous evaluations [36][37][38][39] , in this study self-docking was carried out on the 52 TK structures using the Glide SP mode. Figure 2 demonstrated the self-docking results for all complexes.…”

Section: Self Dockingmentioning

confidence: 99%

Structure-based ensemble-QSAR model: a novel approach to the study of the EGFR tyrosine kinase and its inhibitors

Sun

Chen

et al. 2013

Acta Pharmacol Sin

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Aim: To develop a novel 3D-QSAR approach for study of the epidermal growth factor receptor tyrosine kinase (EGFR TK) and its inhibitors. Methods: One hundred thirty nine EGFR TK inhibitors were classified into 3 clusters. Ensemble docking of these inhibitors with 19 EGFR TK crystal structures was performed. Three protein structures that showed the best recognition of each cluster were selected based on the docking results. Then, a novel QSAR (ensemble-QSAR) building method was developed based on the ligand conformations determined by the corresponding protein structures. Results: Compared with the 3D-QSAR model, in which the ligand conformations were determined by a single protein structure, ensemble-QSAR exhibited higher R2 (0.87) and Q2 (0.78) values and thus appeared to be a more reliable and better predictive model. Ensemble-QSAR was also able to more accurately describe the interactions between the target and the ligands. Conclusion: The novel ensemble-QSAR model built in this study outperforms the traditional 3D-QSAR model in rationality, and provides a good example of selecting suitable protein structures for docking prediction and for building structure-based QSAR using available protein structures.

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“…Regarding the H2 receptors and agonists, a very interesting work was realized by Sun et al [10] following different methods, among them standing pharmacophore modeling (with which they realized a search of the best pharmacophore using QSAR techniques), homolog modeling, molecular docking and molecular dynamics simulation. The results were cross validated with each other, being the pharmacophore and the homology models in good agreement with each other.…”

Section: Molecular Modeling and Qsar Applicationsmentioning

confidence: 99%

Advances in the molecular modeling and quantitative structure–activity relationship-based design for antihistamines

Gálvez

Gálvez-Llompart

Zanni

et al. 2013

Expert Opinion on Drug Discovery

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Given the importance of the use of AHs, the search for new drugs in this field has become imperative today. In this regard, the use of QSAR methods based on MT, namely QSAR-MT, has proven to be a powerful tool when the goal is discovering new hit or lead structures. It has been shown that antihistaminic activity is complex and different for the four known types of receptors (H1 to H4) and that electronic, steric and physicochemical issues determine drug activity. These factors, along with the purely structural ones, can be deduced from topological and topochemical information.

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Computational investigation of interactions between human H2 receptor and its agonists

Cited by 18 publications

References 48 publications

Structure-based discovery and binding site analysis of histamine receptor ligands

Structure-based discovery and binding site analysis of histamine receptor ligands

Structure-based ensemble-QSAR model: a novel approach to the study of the EGFR tyrosine kinase and its inhibitors

Advances in the molecular modeling and quantitative structure–activity relationship-based design for antihistamines

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