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


Muthusankar Aathi* & Shanmughavel Piramanayagam



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



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



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.



Alzheimerís disease, Curcumin, Hypothetical protein



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


Edited by

P Kangueane






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.