S-transferases and their interacting protein partners: a computational perspective J. Muthukumaran1, Teresa Santos-Silva1, Marc Ansari2,3 and C. R. S. Uppugunduri2,3 1UCIBIO, REQUIMTE, Departamento de Química, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal 2Department of Pediatrics, Onco-Hematology Unit, Geneva University Hospital, Geneva, Switzerland 3CANSEARCH Research Laboratory, Department of Pediatrics, Faculty of Medicine, University of Geneva, Geneva, Switzerland

INTRODUCTION RESULTS

 Glutathione S-transferase participates in detoxification of endogenous and exogenous electrophiles. Table 2: MD Simulation results of GSTs with ASK1 They also participates in other cellular processes, such as electrophilic agents induced stress and growth factor- induced signaling, proliferation, differentiation, and apoptosis. GST Average Average Rg Potential Energy Essential Isoforms RMSD (nm) (kj/mol) Dynamics  This investigation is aimed at scrutinizing the interaction of predominantly expressed cytosolic GST isoforms (A1, (nm) (nm) A2, P1, M1, M2, M5 and T1) with two key partners of electrophile induced stress apoptotic pathway i.e. apoptosis GST A1 0.22 2.65 -1908568.87 (13700ps) 244.06 signal-regulating kinase 1 (ASK1) and mitogen-activated protein kinase (MAPK8) using computational methods. GST A2 0.27 2.63 -1587740 (8100ps) 278.932 GST M1 0.27 2.74 -1954723.375 (5560ps) 301.066 METHODOLOGY GST M2 0.3 2.93 -2066349.25 (15520ps) 442.799 GST M5 0.22 2.70 -1895464.75 (1940ps) 292.549  The following computational workflow was implemented to predict the binding affinity of GST isoforms towards ASK1 and MAPK8. GST P1 0.25 2.67 -1783174.5 (16620ps) 246.417 GST T1 0.22 2.79 -1922931.37 (19070ps) 235.815 1. Preparation of input sequence and structure dataset using UniProt and PDB databases.

2. Phylogenetic analysis of seven GST isoforms using Clustal Omega and MEGA to assess the evolutionary 3 relationship. 2.5 3. String protein sequence search to construct the functional interactome for seven GSTs isoforms. 2.0 4. Preparation of the protein structures using MGL-ADT Tools. 5. Docking of GSTs with ASK1, MAPK8 using HADDOCK. 1.5 1 6. Prediction of hot spot regions of GSTs by in silico alanine scanning mutagenesis using DrugScorePPI. G calc [Kcal/mol] G calc 0.5

7. Analysis of protein-protein docking results using PRODIGY, PDBSum and PyMOL. ∆∆ 8. Molecular dynamics simulation (MD) of GSTs with ASK1, MAPK8 using Gromacs. 0 R76 K79 T75 E66 T65 I70 T63 T65 L72 D59 N49 L51 K52 F62 S42 D43 L64 V54 K53 L41 L236 R240 9. Analysis and interpretation of MD results using PyMOL and GRACE. Amino acid residues R107 Figure 2 : Predicted hotspot residues of GSTT1 with ASK1 RESULTS (a) (b)

GSTT1 GSTM1

MAPK8 ASK1

Figure 3 : Predicted protein-protein complexes of (a) GSTM1 with MAPK8 and (b) GSTT1 with ASK1 (a) (b)

Figure 1: Phylogenetic analysis for various isoforms of GSTs  Group 1 has two subgroups, SG1: GST-A1, GST-A2 and GST-P1, SG2: GST-M1, GST-M2 and GST- M5  Group2 has one taxa namely GST-T1 (Separate group). GST-A1, A2 and P1 are closely related. Similarly M1, M2 and M5 are closely related. GST-T1 was diverged from all Table 1: A) Protein-Protein docking results B) Intermolecular interactions of GSTs with MAPK8 A) B) Compl Intermolecular interactions Complexes HADDOCK Score Binding affinity exes Salt Disul Hydrogen Non- dH(kcal/mol) Kd (M) bridges phide bonds bonded bond contacts GSTA1-MAPK8 -83.7 +/ 6.2 -10.1 7.3e-08 s Figure 4 : RMSD plots of (a) GSTM1 with MAPK8 and (b) GSTT1 with ASK1 GSTA2-MAPK8 -76.6 +/ 10.4 -13.3 4.4e-10 GSTA-1- - - 10 181 GSTM1-MAPK8 -105.7 +/ 20.1 -14.1 1.2e-10 MAPK8 CONCLUSION GSTA2- 4 - 18 243 GSTM2-MAPK8 -159.0 +/ 20.2 -15.7 7.9e-12 MAPK8 GSTM5-MAPK8 -151.7 +/ 6.8 -16.8 1.4e-12 GSTM1- 7 - 18 220  The binding affinity of GST isoforms towards MAPK8 is in the order of GSTP-MAPK8 -86.6 +/ 8.3 -13.3 4.5e-10 MAPK8 GSTM1>GSTM5>GSTP >GSTA2>GSTA1>GSTM2 >GSTT1. GSTT1-MAPK8 -91.8 +/ 7.7 -13.5 3.3e-10 GSTM2- 6 - 20 274 MAPK8  Whereas the binding affinity for ASK1 is in the order of  MD simulations with MAPK8 showed that GSTM1 had the lowest GSTM5- 4 - 12 247 GSTT1>GSTA1>GSTP1>GSTA2>GSTM5>GSTM1>GSTM2 trace value of 169.3 nm2(essential dynamic analysis), followed by MAPK8 GSTM5 (174.9 nm). The Average RMSD values and potential GSTP- 3 - 15 181  energy values of M1 and M5 towards MAPK8 were 0.167, - MAPK8 GSTM1 has higher affinity towards MAPK8 and GSTT1 towards ASK1 indicating 1262919.75 (19310ps) and 0.225, -1367582.375 (19510ps), GSTT1- 8 - 19 223 their potential role in cellular processes other than metabolism. MAPK8 respectively. J MuthuKumaran acknowledges Foundation for Science and Technology, Portugal for financial Abbreviations: UniProt - Universal Protein ; PDB - Protein Data Bank ; MEGA - Molecular Evolutionary Genetics Analysis; MGL- Acknowledgements support (SFRH/BPD/97719/2013) ADT - Molecular Graphics Laboratory - Autodock Tools; HADDOCK - High Ambiguity Driven protein-protein DOCKing; PRODIGY - PROtein binDIng enerGY prediction; PDBSum - Summaries and analyses of PDB structures; GROMACS - GROningen MAchine for Chemical Simulations; GRACE - GRaphing, Advanced Computation and Exploration of data.