Identification of inhibitors for neurodegenerative diseases targeting dual leucine zipper kinase through virtual screening and molecular dynamics simulations

ABSTRACT

Neurodegenerative diseases lead to a gradual decline in cognitive and motor functions due to the progressive loss of neurons in the central nervous system. The role of dual leucine zipper kinase (DLK) in regulating stress responses and neuronal death pathways highlights its significance as a target against neurodegenerative diseases. The non-availability of FDA-approved drugs emphasizes a need to identify novel DLK-inhibitors. We screened NPAtlas (Natural products) and MedChemExpress (FDA-approved) libraries to identify potent ATP-competitive DLK inhibitors. ADMET analyses identified four compounds (two natural products and two FDA-approved) with favourable features. Subsequently, we performed molecular dynamics simulations to examine the binding-stability and ligand-induced conformational dynamics. Molecular mechanics Poisson Boltzmann surface area (MM-PBSA) calculations demonstrated CID139591660, dithranol, and danthron having greater affinity, while CID156581477 showed lower affinity than control sunitinib. PCA and network analysis results indicated structural and network alteration post-ligand binding. Furthermore, we identified an analogue of CID156581477 using the deep learning-based web server DeLA Drug which demonstrated a higher affinity than its parent compound and the control and identified several crucial interacting residues. Overall, our study provides significant theoretical guidance for designing potent novel DLK inhibitors and compounds that could emerge as promising drug candidates against DLK following laboratory validation.

KEYWORDS:

• Dual leucine zipper kinase
• neurodegenerative disease
• virtual screening
• molecular dynamics
• free energy

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data supporting this study’s findings are available from the corresponding author (PK) upon reasonable request.

Ethics Statement

There is no human or animal experiment in this study.

Supplementary material

Supplemental data for this article can be accessed at: https://doi.org/10.1080/1062936X.2024.2363195.

Additional information

Funding

This work was supported by the Department of Science and Technology (DST), Govt. of India (grant number DST/NSM/R&D_HPC_Applications/2021/03.18 and SR/FST/LS-I/2020/621). SK would like to thank the University Grants Commission for providing a doctoral fellowship under the JRF scheme. SS thanks the Ministry of Education, Govt. of India, for providing a doctoral fellowship under the Prime Minister’s Research Fellows (PMRF) scheme.