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Title

From EST to structure models for functional inference of APP, BACE1, PSEN1, PSEN2 genes

Authors

Muthusankar Aathi* & Shanmughavel Piramanayagam

 

Affiliation

Computational Biology Lab, Department of Bioinformatics, Bharathiar University, Coimbatore-641046, Tamil Nadu, India

 

Email

Muthusankar Aathi - Email: muthubioinf@gmail.com; *Corresponding author

 

Article Type

Research Article

 

Date

Received September 22, 2019; Revised October 28, 2019; Accepted October 29, 2019; Published October 31, 2019

 

Abstract

Successive oxidative stress and biochemical changes results in neuronal death and neuritic plaques growth in Alzheimer's disease (AD). Therefore, it is interest to analyze amyloid-βeta precursor protein (APP), beta-secretase 1 (BACE1), presenilin (PSEN1 and PSEN2) genes
from brain tissues to gain insights. Development of potential inhibitors for these targets is of significance. EST sequences of 2898 (APP), 539 (BACE1), 786 (PSEN1) and 314 (PSEN2) genes were analyzed in this study. A contig sequences with APP (contigs 1-4), BACE1 (contigs 5-7),
PSEN1 (contigs 8, 9, 10, 11), PSEN2 (contigs 13, 14) except PSEN1 (contigs 10) and PSEN2 (contigs 13) genes were identified. APP (contig 3 without translational error) was further analyzed using molecular modeling and docking to show its binding with curcumin (principal curcuminoid of turmeric) having -7.3 kcal/mol interaction energy for further consideration as a potential inhibitor.

 

Keywords

Alzheimerís disease, Curcumin, Hypothetical protein

 

Citation

Aathi & Piramanayagam, Bioinformation 15(10): 760-771 (2019) 

 

Edited by

P Kangueane

 

ISSN

0973-2063

 

Publisher

Biomedical Informatics

 

License This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.