This paper is published in Volume-5, Issue-2, 2019
Area
Neurobiology
Author
Kusumitha Shrinivasan, Swarnali Sarkar, Anand Prem Rajan
Org/Univ
Vellore Institute of Technology, Vellore, Tamil Nadu, India
Pub. Date
30 March, 2019
Paper ID
V5I2-1654
Publisher
Keywords
Alzheimer’s Disease, Amyloid precursor protein

Citationsacebook

IEEE
Kusumitha Shrinivasan, Swarnali Sarkar, Anand Prem Rajan. Identification of novel compounds to treat Alzheimer’s disease, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Kusumitha Shrinivasan, Swarnali Sarkar, Anand Prem Rajan (2019). Identification of novel compounds to treat Alzheimer’s disease. International Journal of Advance Research, Ideas and Innovations in Technology, 5(2) www.IJARIIT.com.

MLA
Kusumitha Shrinivasan, Swarnali Sarkar, Anand Prem Rajan. "Identification of novel compounds to treat Alzheimer’s disease." International Journal of Advance Research, Ideas and Innovations in Technology 5.2 (2019). www.IJARIIT.com.

Abstract

Alzheimer’s disease or Alzheimer’s is a brain disorder characterized by progressive loss of neural functions and dementia in elderly people. It has perilous effects on memory and other cognitive activities. Apolipoprotein (APOE) is responsible for delivering cholesterol-rich lipoproteins to the bloodstream. The maintenance of optimum levels of cholesterol is absolutely necessary as an imbalance might lead to cardiovascular and neurological diseases. Out of the four alleles for the APOE gene, the main causative agent for the onset of Alzheimer’s is the e4 allele. APOE e4 allele leads to the production of amyloid plaques which further cause the accumulation of amyloid β peptide. The excess build-up of such toxic products leads to neuronal death giving rise to early symptoms of the disease. Our research mainly focuses on the identification of potential inhibitors against Sortilin (SORT1), an APOE receptor associated with Alzheimer’s. We have employed scientific software to identify the specific conformations of ligands that show the maximum interaction with the target compound and further analyzed these results by generating descriptors computationally for QSAR studies. The optimum model was generated with r2 = 0.794, s= 0.108. We have been able to select two ligands which can be used as potential drugs to treat Alzheimer’s.