Literature DB >> 28738772

Molecular Docking and Drug Discovery in β-Adrenergic Receptors.

Santiago Vilar1, Eduardo Sobarzo-Sanchez1, Lourdes Santana1, Eugenio Uriarte1.   

Abstract

BACKGROUND: Evolution in computer engineering, availability of increasing amounts of data and the development of new and fast docking algorithms and software have led to improved molecular simulations with crucial applications in virtual high-throughput screening and drug discovery. Moreover, analysis of protein-ligand recognition through molecular docking has become a valuable tool in drug design.
OBJECTIVE: In this review, we focus on the applicability of molecular docking on a particular class of G protein-coupled receptors: the β-adrenergic receptors, which are relevant targets in clinic for the treatment of asthma and cardiovascular diseases.
RESULTS: We describe the binding site in β-adrenergic receptors to understand key factors in ligand recognition along with the proteins activation process. Moreover, we focus on the discovery of new lead compounds that bind the receptors, on the evaluation of virtual screening using the active/ inactive binding site states, and on the structural optimization of known families of binders to improve β-adrenergic affinity. We also discussed strengths and challenges related to the applicability of molecular docking in β-adrenergic receptors.
CONCLUSION: Molecular docking is a valuable technique in computational chemistry to deeply analyze ligand recognition and has led to important breakthroughs in drug discovery and design in the field of β-adrenergic receptors. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Entities:  

Keywords:  G proteincoupledzzm321990receptors; Molecular docking; drug design; drug discovery; virtual screening; β-adrenergic receptors

Mesh:

Substances:

Year:  2017        PMID: 28738772     DOI: 10.2174/0929867324666170724101448

Source DB:  PubMed          Journal:  Curr Med Chem        ISSN: 0929-8673            Impact factor:   4.530


  9 in total

1.  Continuous Evaluation of Ligand Protein Predictions: A Weekly Community Challenge for Drug Docking.

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5.  Selected by gene co-expression network and molecular docking analyses, ENMD-2076 is highly effective in glioblastoma-bearing rats.

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Authors:  Hayder M Al-Kuraishy; Ali Ismail Al-Gareeb; Gomaa Mostafa-Hedeab; Keneth Iceland Kasozi; Gerald Zirintunda; Akhmed Aslam; Mamdouh Allahyani; Susan Christina Welburn; Gaber El-Saber Batiha
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8.  Design, in silico studies, and synthesis of new 1,8-naphthyridine-3-carboxylic acid analogues and evaluation of their H1R antagonism effects.

Authors:  Vinod Kumar Gurjar; Dilipkumar Pal
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9.  Selected using bioinformatics and molecular docking analyses, PHA-793887 is effective against osteosarcoma.

Authors:  Bo Wu; Wenzhuo Yang; Zhaoyu Fu; Haoqun Xie; Zhen Guo; Daqun Liu; Junliang Ge; Sheng Zhong; Luwei Liu; Jingyi Liu; Dong Zhu
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  9 in total

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