Structure-based virtual screening and molecular dynamics simulation for the identification of sphingosine kinase-2 inhibitors as potential analgesics

Abstract

Neuropathic pain is due to an injury or disease of the somatosensory nervous system, which accounts for a significant economical and health burden to society. Due to poor understanding of their underlying mechanisms, the available treatments merely provide symptomatic relief and precipitates a variety of adverse effects. This suggests that there is an unmet medical need that must be addressed with effective strategies for the development of novel therapeutics. Sphingosine kinase 2 (SphK2) is an oncogenic lipid kinase that has emerged as a promising target for chronic pain and other diseases. In the present study, we have explored the structure-based virtual high-throughput screening of the Nuclei of Bioassays, Ecophysiology, and Biosynthesis of Natural Products Database (NuBBE) to identify potent natural products as inhibitors of SphK2. A molecular docking study was performed to calculate binding affinities and specificity to identify potential leads against SphK2. Initially, hits were selected by the implementation of absorption, distribution, metabolism, excretion and toxicity properties, Lipinski rule, and PAINS filters. The top-scoring hits also exhibiting an optimal ADMET profile were subjected to MM/GBSA free binding free energy calculation and molecular dynamics simulation. The results from molecular dynamics simulation revealed a stable ligand -SphK2 complex with protein and ligand RMSD within reasonable limits. Overall, we identified compounds, NuBBE_972 and NuBBE_1107 as potential inhibitors of SphK2 with optimal pharmacokinetic properties which have the potential to be developed as novel therapeutics for the management of chronic pain.

Communicated by Ramaswamy H. Sarma

Keywords:

• Virtual screening
• molecular dynamics simulation
• sphingosine kinase 2
• chronic pain
• natural inhibitors

Acknowledgements

We acknowledge the Department of Pharmaceutical Engineering & Technology (BHU), Varanasi U.P. for providing the infrastructure and support. The support and the resources provided by ‘PARAM Shivay Facility’ under the National Supercomputing Mission, Government of India at the Indian Institute of Technology, Varanasi are gratefully acknowledged. A part of computational studies was performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre, Linköping University, Linköping, Sweden.

Disclosure statement

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

Additional information

Funding

This work is supported by Senior Research Fellowship awarded to Mr. Akhilesh under the supervision of Dr. Vinod Tiwari by the Indian Council of Medical Research (File no. 5/3/8/17/ITR-F/2020). This work is also supported by the core research grant (CRG/2020/002621) and SPARC grant (SPARC/2018-2019/P435/SL) awarded to Dr. Vinod Tiwari by the Science and Engineering Research Board and Ministry of Human Resource & Development, Government of India respectively. Anurag TK Baidya and Bhanuranjan Das acknowledges the Teaching Assistantship awarded by IIT(BHU).