|
High Throughput Screening of Potential Inhibitors of Alzheimer’s Disease Associated Tau Aggregation Protein
|
|
| Author:
|
SANTOSH JHA, ARCHANA RAI, AND HARE RAM SINGH , ARCHANA RAI
|
| Abstract:
|
The bioinformatics approach towards finding a solution for the problem of tau aggregation in brain requires the computational modelling of the tau aggregation protein and screening of its potential inhibitor. This was achieved in this study through a number of steps, the first being the modelling of Tau aggregation protein which has no significant template available. Thus the need of a web server such as I-TASSER which performs sequence analysis to structure of a given query protein using threading as principle, arose. The predicted model further underwent docking with total 73 confirmations of 5 already identified inhibitors. The docking results were quite promising based on the docking score and glide score although the model produced did not pass the stereotype tests of being the correct predicted structure. These inhibitors can be used as lead molecules for the designing of inhibitor based drugs. The ADMET analysis provided an insight into how good an anthraquinone can be as a drug molecule to inhibit the aggregation of PHFs. This included Lipinski’s rule, Jorgensen’s rule, blood brain barrier penetration, skin permeability, human intestinal absorption, and oral absorption. PHF 005 (1-phenyl-1-(2,3,4-trihydroxy-phenyl)-methanone) was found to be the best inhibitor of Tau protein (isoform 2) among all the inhibitors with comparable ADMET properties. So it may have to potential to be able to inhibit tau aggregation and thus add in the aid of Alzheimer’s disease. Present study focuses on the importance of structure based in silico drug design which takes less time and is cost effective.
|
| Keyword:
|
Tau aggregation, ADMET, Lipinski’s rule, Jorgensen’s rule.
|
| EOI:
|
-
|
| DOI:
|
-
|
| Download:
|
Request For Article
|
|
|