Knowledge based identification of MAO-B selective inhibitors using pharmacophore and structure based virtual screening models.

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Boppana K, Dubey PK, Jagarlapudi SA, Vadivelan S, Rambabu G

Knowledge based identification of MAO-B selective inhibitors using pharmacophore and structure based virtual screening models.

Eur J Med Chem. 2009 Sep;44(9):3584-90. doi: 10.1016/j.ejmech.2009.02.031. Epub 2009 Mar 11.

PubMed ID

19321235 [ View in PubMed

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Abstract

Monoamine Oxidase B interaction with known ligands was investigated using combined pharmacophore and structure based modeling approach. The docking results suggested that the pharmacophore and docking models are in good agreement and are used to identify the selective MAO-B inhibitors. The best model, Hypo2 consists of three pharmacophore features, i.e., one hydrogen bond acceptor, one hydrogen bond donor and one ring aromatic. The Hypo2 model was used to screen an in-house database of 80,000 molecules and have resulted in 5500 compounds. Docking studies were performed, subsequently, on the cluster representatives of 530 hits from 5500 compounds. Based on the structural novelty and selectivity index, we have suggested 15 selective MAO-B inhibitors for further synthesis and pharmacological screening.

DrugBank Data that Cites this Article

Binding Properties

Drug	Target	Property	Measurement	pH	Temperature (°C)
Linezolid	Amine oxidase [flavin-containing] B	IC 50 (nM)	17000	N/A	N/A	Details
Pargyline	Amine oxidase [flavin-containing] B	IC 50 (nM)	2600	N/A	N/A	Details