Footprinting of Inhibitor Interactions ofIn SilicoIdentified Inhibitors of Trypanothione Reductase ofLeishmaniaParasite
Author(s) -
Santhosh Venkatesan,
Vikash Kumar Dubey
Publication year - 2012
Publication title -
the scientific world journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.453
H-Index - 93
eISSN - 2356-6140
pISSN - 1537-744X
DOI - 10.1100/2012/963658
Subject(s) - virtual screening , in silico , leishmania infantum , computational biology , docking (animal) , chemistry , biology , biochemistry , drug discovery , genetics , leishmaniasis , medicine , nursing , visceral leishmaniasis , gene
Structure-based virtual screening of NCI Diversity set II compounds was performed to indentify novel inhibitor scaffolds of trypanothione reductase (TR) from Leishmania infantum . The top 50 ranked hits were clustered using the AuPoSOM tool. Majority of the top-ranked compounds were Tricyclic. Clustering of hits yielded four major clusters each comprising varying number of subclusters differing in their mode of binding and orientation in the active site. Moreover, for the first time, we report selected alkaloids and dibenzothiazepines as inhibitors of Leishmania infantum TR. The mode of binding observed among the clusters also potentiates the probable in vitro inhibition kinetics and aids in defining key interaction which might contribute to the inhibition of enzymatic reduction of T[S] 2. The method provides scope for automation and integration into the virtual screening process employing docking softwares, for clustering the small molecule inhibitors based upon protein-ligand interactions.
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