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Molecular docking studies of 1-(substituted phenyl)-3-(naphtha [1, 2-d] thiazol-2-yl) urea/thiourea derivatives with human adenosine A(2A) receptor.


ABSTRACT: Computational assessment of the binding interactions of drugs is an important component of computer-aided drug design paradigms. In this perspective, a set of 30 1-(substituted phenyl)-3-(naphtha[1, 2-d] thiazol-2-yl) urea/thiourea derivatives showing antiparkinsonian activity were docked into inhibitor binding cavity of human adenosine A(2A) receptor (AA2AR) to understand their mode of binding interactions in silico. Lamarckian genetic algorithm methodology was employed for docking simulations using AutoDock 4.2 program. The results signify that the molecular docking approach is reliable and produces a good correlation coefficient (r(2) = 0.483) between docking score and antiparkinsonian activity (in terms of % reduction in catalepsy score). Potent antiparkinsonian agents carried methoxy group in the phenyl ring, exhibited both hydrophilic and lipophilic interactions with lower energy of binding at the AA(2A)R. These molecular docking analyses should, in our view, contribute for further development of selective AA(2A)R antagonists for the treatment of Parkinson's disease.

SUBMITTER: Azam F 

PROVIDER: S-EPMC3143394 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Molecular docking studies of 1-(substituted phenyl)-3-(naphtha [1, 2-d] thiazol-2-yl) urea/thiourea derivatives with human adenosine A(2A) receptor.

Azam Faizul F   Prasad Medapati Vijaya Vara MV   Thangavel Neelaveni N   Ali Hamed Ismail HI  

Bioinformation 20110719 9


Computational assessment of the binding interactions of drugs is an important component of computer-aided drug design paradigms. In this perspective, a set of 30 1-(substituted phenyl)-3-(naphtha[1, 2-d] thiazol-2-yl) urea/thiourea derivatives showing antiparkinsonian activity were docked into inhibitor binding cavity of human adenosine A(2A) receptor (AA2AR) to understand their mode of binding interactions in silico. Lamarckian genetic algorithm methodology was employed for docking simulations  ...[more]

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