Ligand Identification for the Orthosteric site of Sigma 1 Receptor using Computational Molecular Docking and Virtual Screening Methods

Purpose:

The 𝝈1 Receptor (Sig-1R) is a ligand operated membrane protein resides in the mitochondria-associated-membranes of the endoplasmic reticulum (ER). At the molecular level, Sig-1R has several important roles in cellular homeostasis, including Ca2+ regulation, and helping chaperone the unfolded protein response. This ER stress has been found to be one of the factors leading to cytokine storm and clinical deterioration in patients with a coronavirus infection, leading to an interest in drugs which modulate the response of the Sig-1R for treatment of COVID-19.

These receptors are found throughout the CNS as well as the periphery, explaining its wide range of effects throughout the body. At the organ level, studies conducted on the Sig-1R have implicated its involvement in neurodegenerative diseases such as Parkinson’s and Alzheimer’s Disease, cardiac diseases such as heart failure and cardiovascular disease (CVD), and major depressive disorder. This implication in a wide variety of disease states means it has a large potential as a drug target. Our study's purpose is to identify novel potential drug candidates at the orthosteric binding site of Sig-1R with high binding affinity, specificity, and favorable PK parameters using a structure-based drug design approach.

Method:

Prior work in this lab found a list of the top 1000 orthosteric ligands by docking Sig-1R against libraries containing 9,270 small drug-like molecules using the TACC drug discovery tool. These libraries were extracted from the ZINC database. From this list of 1000 compounds, we selected the top 130 compounds (binding affinity cut-off ≥ -11.0 kcal/mol) and re-docked against the Sig-1R using the efficient docking suite Glide in Maestro. Also, we analyzed the pharmacokinetic/ADME parameters of these compounds using SwissADME, identifying possible candidates to use as our scaffold to try and design a ligand with even stronger binding affinity to the orthosteric site of Sig1R. Furthermore, we docked 130 compounds with the Dopamine Receptor D2 (D2R) to analyze their specificity for the Sig-1R.

Results:

Using an extra precision molecular docking in Glide, we found that our molecule 106 (-12.88 kcal/mol), molecule 105 (-12.83 kcal/mol), and molecule 100 (-12.29 kcal/mol) all had very high binding affinity for the Sig-1R. Both Molecules 105 and 100 had favorable PK parameters, as both were estimated to be BBB permeable, as well as not breaking any aspects of Lipinski’s Rule of Five. Molecule 100 was also found to have relatively low binding affinity (-7.6 kcal/mol) for the D2R.

Conclusion:

Using our computational molecular docking methods, we have identified molecule 100 as a ligand with strong affinity and specificity for the Sig1R, as well as favorable PK parameters. This could be a strong candidate to use as a chemical scaffold to develop a ligand with even stronger binding affinity for Sig-1R, which can eventually go on to in-vitro assays to confirm activity.