Identification of putative substrates and inhibitors for Glutathione S-transferases using computational methods

<p>Glutathione S-transferases (GSTs) comprise a family of enzymes that utilizes glutathione (GSH) in many enzymatic reactions that involved in transformation of several compounds including therapeutic drug molecules and carcinogens. In addition, GSTs influence cellular survival and proliferation, by repressing apoptosis signal-regulating kinase 1 (ASK1) thus affecting the activation of p38 mitogen-activated protein kinase (MAPK) and c-Jun N-terminal kinase (JNK) in response to various intra and extracellular stresses. Molecules inhibiting the function of GSTs received attention as an adjuvant therapy to the highly toxic electrophilic agents to avoid usage of high doses and toxicity for better outcomes. There is no detailed <em>in silico</em> analysis exists in literature to describe the binding patterns of known inhibitors to all GST isoforms. This study is aimed at providing details of binding patterns of known and putative substrates (Busulfan, Treosulfan, SS-EBDM, SS-DEB), inhibitors (Ethacrynic acid, Sulfolane and Curcumin) with predominately-expressed seven isoforms of GST (Alpha1, Alpha2, Pi1, Mu1, Mu2, Mu5 and Theta1). In silico methodology include six steps namely (a) Retrieval of three-dimensional structure of GSTs and Ligand molecules from RCSB-PDB and NCBI-PubChem databases, (b) Protein and Ligand preparation using Auto Dock Tools (ADT), (c) Receptor grid preparation based on known binding site (Direct docking protocol) of GSTs using AutoDock/Vina plugin in PyMOL, (d) Preparation of Auto Dock Vina configuration file, (e) Running of docking calculation using Auto Dock Vina and (f) Analysis of docking results using ADT, PyMOL and LigPlus programs. Molecular docking studies of substrates/inhibitors are performed with both Apo and GSH bounded forms of GSTs. Structural parameters such as estimated free energy of binding (ΔH), estimated inhibition constant (Ki), binding orientation, intermolecular interactions were noted for all the docking interaction models. Then the parameters were compared against each substrate or inhibitor for the affinity towards a selective GST isoform. Out of the three putative or known inhibitors screened, Curcumin showed a significant high binding affinity towards all the classes of GSTs, particularly GST Alpha1 (ΔH: -9.7 kcal/mol and Ki: 0.08 µM). Ethacrynic acid also showed better binding affinity towards GST Alpha1 (ΔH: -7.6 kcal/mol and Ki: 2.7 uM). Sulfolane did not exhibited a stronger affinity towards all the seven GST isoforms. Busulfan and Treosulfan exhibited a reasonable binding affinity towards GST Alpha1 (ΔH: -5.2 and -5.3 kcal/mol) and weakened affinity for the remaining six GST isoforms. Thus, treosulfan could be a possible substrate for GST Alpha1. Manual inspection of three-dimensional structures of the docking complexes revealed that binding-sites for inhibitor and substrate are different. In an on-going study, we are evaluating the inhibitory potential of Curcumin and Ethacrynic acid against GSTs in <em>in vitro</em> studies. The detailed description of the binding interactions may be useful to screen new putative GST substrates and inhibitors. Presence or absence of variants in these binding pockets also can define the amount of inhibitor required and the affinity and potency of an inhibitor and or substrate. </p> <p>This poster is presented at " ESPT 2017 in Catania, Italy from Oct 4th-7th 2017"