Docking-based inverse virtual screening strategy for identification of novel protein targets for triclosan.

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ID: 55603
2019
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Abstract
Triclosan (TCS) is chemically designated as 5-chloro-2-(2,4-dichlorophenoxy) phenol and is considered as endocrine-disrupting chemical (EDC). The various diseases found due to exposure of TCS, have been linked with modulation of the human enoyl-acyl carrier protein-reductase (hER). However, the new protein targets for TCS other than hER, which are responsible for various diseases, are still unknown. In the present study, a bioinformatics approach was used to identify new possible targets for TCS. A text mining study was initially performed to understand the association of TCS in various biochemical processes. Discovery studio software 4.1 was used to carry out inverse virtual screening for 226 numbers of pathway proteins by docking study using CHARMm based docking tool, and twenty proteins were screened. CDOCKER energy values lower than -12.65 kcal/mol was considered for the screening of selected proteins. Three new proteins; Receptor-interacting protein 1 (RIP1), Apoptosis signal-regulating kinase 1 (ASK1) and B-cell lymphoma 2 (Bcl-2) from Apoptosis Signaling Pathway revealed best CDOCKER energy with triclosan which was -26.88, -23.34 and -22.96 kcal/mol respectively. The interaction of TCS with RIP1 and ASK1 were mostly hydrophobic; however, hydrogen bond type interaction was found in TCS/Bcl2 complex. Therefore, docking-based inverse virtual screening study suggests that TCS has other targets rather than hER, which can modulate various biochemical processes. The docking protocol was validated through evaluation of root-mean-square deviation (RMSD), key interaction score system (KISS) and the relationship between the docking energy and toxicity data available in ToxCast database. Low RMSD value (0.55 ˚A) and high KISS score (0.66) along with higher correlation (R = 0.9798) between docking affinity and toxicity indicated that docking protocol can be used to optimize the binding energetics.
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bhardwaj2019dockingbasedchemosphere Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Bhardwaj, Prashant;Biswas, G P;Bhunia, Biswanath;
Journal Chemosphere
Year 2019
DOI
S0045-6535(19)31507-3
URL
Keywords
validation triclosan text mining cdocker energy endocrine-disrupting chemical inverse virtual screening

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