Docking Applied to the Prediction of the Affinity of Compounds to P-Glycoprotein | Zendy

Pablo H. Palestro | Zendy; Luciana Gavernet | Zendy; Guillermina Estiú | Zendy; Luis Enrique Bruno Blanch | Zendy

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Docking Applied to the Prediction of the Affinity of Compounds to P-Glycoprotein

Author(s) -

Pablo H. Palestro,

Luciana Gavernet,

Guillermina Estiú,

Luis Enrique Bruno Blanch

Publication year - 2014

Publication title -

biomed research international

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.772

H-Index - 126

eISSN - 2314-6141

pISSN - 2314-6133

DOI - 10.1155/2014/358425

Subject(s) - docking (animal) , virtual screening , autodock , p glycoprotein , computational biology , drug , computer science , chemistry , machine learning , drug discovery , pharmacology , biochemistry , in silico , biology , medicine , nursing , multiple drug resistance , gene , antibiotics

P-glycoprotein (P-gp) is involved in the transport of xenobiotic compounds and responsible for the decrease of the drug accumulation in multi-drug-resistant cells. In this investigation we compare several docking algorithms in order to find the conditions that are able to discriminate between P-gp binders and nonbinders. We built a comprehensive dataset of binders and nonbinders based on a careful analysis of the experimental data available in the literature, trying to overcome the discrepancy noticeable in the experimental results. We found that Autodock Vina flexible docking is the best choice for the tested options. The results will be useful to filter virtual screening results in the rational design of new drugs that are not expected to be expelled by P-gp.

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