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Bioinformation. 2019 Oct 31;15(10):760-771. doi: 10.6026/97320630015760. eCollection 2019.

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

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


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.


Alzheimer's disease; Curcumin; Hypothetical protein

Conflict of interest statement

The authors confirm that this article content has no conflict of interest.

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