In silico Docking Studies and Potential Lead Identification against JNK3 for Alzheimer’s Disease

  • Nishtha Singh Department of Applied Science, Indian Institute of Information Technology, Allahabad, Deoghat, Jhalwa, Uttar Pradesh, INDIA.
  • Sonal Upadhyay Department of Applied Science, Indian Institute of Information Technology, Allahabad, Deoghat, Jhalwa, Uttar Pradesh, INDIA.
  • Ankur Jaiswar Department of Applied Science, Indian Institute of Information Technology, Allahabad, Deoghat, Jhalwa, Uttar Pradesh, INDIA.
  • Nidhi Mishra Department of Applied Science, Indian Institute of Information Technology, Allahabad, Deoghat, Jhalwa, Uttar Pradesh, INDIA.
Keywords: JNK3, Alzheimer’s disease, Amyloid β peptides

Abstract

Background: Alzheimer’s Disease (AD) is a neuron related brain disorder leading to reasoning and memory loss. There is no specific cure identified for AD. JNK3 (c-Jun N-terminal kinase /stress-activated protein kinase) are highly revealed within the central nervous system, particularly neurons, playing vital role in functioning of brain. JNK3 hyper phosphorylation is a very common conclusion in neurodegenerative diseases. JNK3 in turn hyper phosphorylates Amyloid Precursor Protein (APP) which leads to the formation of Amyloid β peptides (an inductive agent of Alzheimer’s disease). Methods: Protein JNK-3 (PDB ID: 3KVX) was retrieved from protein data bank and later we docked a library of compounds against it. These were further validated by ADMET studies. Results: Thus, docking inhibitors of JNK3 may provide a promising sanitive approach. Based on best docking score and glide score a potential lead is identified against JNK3. Conclusion: Inhibiting JNK-3 may lead to less production of amyloidβ peptides, thus reducing the risk of Alzheimer’s disease.

Downloads

Download data is not yet available.

Author Biography

Sonal Upadhyay, Department of Applied Science, Indian Institute of Information Technology, Allahabad, Deoghat, Jhalwa, Uttar Pradesh, INDIA.

MTech student

Table 1: Binding efficiency comparison based on Docking Score, Glide g Score and Glide emodel
Published
2019-12-12
How to Cite
1.
Singh N, Upadhyay S, Jaiswar A, Mishra N. In silico Docking Studies and Potential Lead Identification against JNK3 for Alzheimer’s Disease. ijpi [Internet]. 12Dec.2019 [cited 20Feb.2020];9(4):220-2. Available from: http://jpionline.org/index.php/ijpi/article/view/337