Identification of Potential Positive Allosteric Modulators of Sigma-1 Receptor using Computational Molecular Docking and Virtual Screening

Purpose: Coronaviruses (such as SARS-COV-2) can achieve replication in host cells by activating pathways in the endoplasmic reticulum (ER), which causes ER stress. As it is known that the mortality rate of elderly populations in COVID-19 infection is dramatically high, indicating a vital role in the timely response of cell stress response signaling pathways in the management of the treatment of COVID-19. The sigma-1 receptor (Sig1R) is an important upstream modulator of ER stress, which regulates folding/degradation of proteins, Ca+2 homeostasis, ER stress responses, and cellular survival. Therefore, ligands enhancing Sig1R activities may improve the treatment of COVID-19 of the elderly patients. Positive Allosteric Modulators (PAM) can enhance protein activities by binding at an allosteric site. Several PAMs of Sig1R have been reported. However, the molecular basis of interactions of PAMs in Sig1R is poorly understood. Further, we do not have much information about the allosteric binding sites in Sig1R yet. Our purpose in this research is to identify possible chemical scaffolds/compounds that can bind at the allosteric sites of Sig1R and selectively elicit the activity of Sig1R. Method: In this study, we have assessed several known PAMs of Sig1R to investigate their binding affinity, the molecular basis of their interactions at three possible allosteric binding sites in Sig1R using the efficient docking suite, Glide. In addition to this, we explored ZINC and DRUG bank databases to search for compounds/chemical scaffolds that are similar to PAMs, which can be docked and engineered further to get a highly efficient drug target/PAM of Sig1R. Results: We have found that methylphenylpiracetam, SKF38393, and SCH23390 show high affinity for allosteric pockets. Further, by virtual screening of small drug-like compounds of the ZINC database in Auto Dock Vina, we obtained a list of 1000 compounds for each allosteric pocket of Sig1R. In the next step, we plan to continually refine our search by performing docking of these compounds and the compounds we obtained through ligand-based search in Glide to identify the promising set of compounds that bind efficiently at an allosteric site in Sig1R. Conclusion: Using molecular docking, we have found three compounds methylphenylpiracetam, SKF38393, and SCH23390 that bind to Sig1R at the allosteric pockets with high binding affinities and identified a list of 1000 compounds for each potential allosteric sites, shedding light on the further development of selective PAMs of Sig1R.