Literature DB >> 26055215

3D-QSAR and docking studies on adenosine A2A receptor antagonists by the CoMFA method.

E Pourbasheer1, S Shokouhi Tabar, V H Masand, R Aalizadeh, M R Ganjali.   

Abstract

Parkinson's disease affects millions of people around the world. Recently, adenosine A2A receptor antagonists have been identified as a drug target for the treatment of Parkinson's disease. Consequently, there is an immediate need to develop new classes of A2A receptor antagonists. In the present analysis, three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed on a series of pyrimidines, using comparative molecular field analysis (CoMFA). The best prediction was obtained with a CoMFA standard model (q(2) = 0.475, r(2) = 0.977) and a CoMFA region focusing model (q(2) = 0.637, r(2) = 0.976) combined with steric and electrostatic fields. The structural insights derived from the contour maps helped to better interpret the structure-activity relationships. Also, to understand the structure-activity correlation of A2A receptor antagonists, we have carried out molecular docking analysis. Based on the results obtained from the present 3D-QSAR and docking studies, we have identified some key features for increasing the activity of compounds, which have been used to design new A2A receptor antagonists. The newly designed molecules showed high activity with the obtained models.

Entities:  

Keywords:  3D-QSAR; A2A receptor antagonists; CoMFA; docking; drug design

Mesh:

Substances:

Year:  2015        PMID: 26055215     DOI: 10.1080/1062936X.2015.1049666

Source DB:  PubMed          Journal:  SAR QSAR Environ Res        ISSN: 1026-776X            Impact factor:   3.000


  5 in total

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Review 2.  In Silico Studies in Drug Research Against Neurodegenerative Diseases.

Authors:  Farahnaz Rezaei Makhouri; Jahan B Ghasemi
Journal:  Curr Neuropharmacol       Date:  2018       Impact factor: 7.363

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Authors:  Ravindra L Bakal; Rahul D Jawarkar; J V Manwar; Minal S Jaiswal; Arabinda Ghosh; Ajaykumar Gandhi; Magdi E A Zaki; Sami Al-Hussain; Abdul Samad; Vijay H Masand; Nobendu Mukerjee; Syed Nasir Abbas Bukhari; Praveen Sharma; Israa Lewaa
Journal:  Saudi Pharm J       Date:  2022-04-07       Impact factor: 4.562

4.  QSAR Study of 17β-HSD3 Inhibitors by Genetic Algorithm-Support Vector Machine as a Target Receptor for the Treatment of Prostate Cancer.

Authors:  Eslam Pourbasheer; Saadat Vahdani; Davood Malekzadeh; Reza Aalizadeh; Amin Ebadi
Journal:  Iran J Pharm Res       Date:  2017       Impact factor: 1.696

5.  Structure-based identification of dual ligands at the A2AR and PDE10A with anti-proliferative effects in lung cancer cell-lines.

Authors:  Leen Kalash; Ian Winfield; Dewi Safitri; Marcel Bermudez; Sabrina Carvalho; Robert Glen; Graham Ladds; Andreas Bender
Journal:  J Cheminform       Date:  2021-03-03       Impact factor: 5.514

  5 in total

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