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
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
Alzheimer’s disease, Curcumin, Hypothetical protein
Citation
Aathi & Piramanayagam, Bioinformation 15(10): 760-771 (2019)
Edited by
P Kangueane
ISSN
0973-2063
Publisher
