In-silico investigation of the effects of genetic mutations on the structural dynamics of thiopurine s-methyltransferase and their implications on the metabolism of 6-mercaptopurine - Mwaniki, Rehema Mukami (Rhodes University, Faculty of Science, Department of Biochemistry and Microbiology)
Thiopurine S-methyltransferase (TPMT) is a cytosolic enzyme that catalyzes the S-methylation of aromatic and heterocyclic sulfhydryl compounds such as 6-mercaptopurine (6MP), 6-thioguanine (6TG) and azathioprine (AZA) which is first converted to 6MP through reduction by glutathione S- transferases (GST). The compounds, generally referred to as thiopurines, are immunosuppressants used to treat childhood acute lymphoblastic leukemia (ALL), autoimmune disorders and transplant rejection. Thiopurines are prodrugs which require metabolic activation to give thioguanine nucleotides that exert their cytotoxic effects by incorporation into DNA or inhibiting purine synthesis. The methylation reaction by TPMT utilizing S-adenosylmethionine (SAM) as the methyl donor prevents their conversion to these toxic compounds. The catalytic activity of TPMT in metabolising these compounds has been associated with occurrence of genetic variations. The variations that result to missense mutations cause amino-acid changes and in turn alter the polypeptide sequence of the protein. This could alter functionality and structural dynamics of the enzyme. This study sought to understand the underlying mechanism by which 7 specially selected mutations impede metabolic activity of the enzyme on 6-MP using in silico techniques. VAPOR and PredictSNP were used to predict the effects of single nucleotide polymorphisms (SNPs) on the stability and function of the enzyme. Of the 7 mutations, only H227Q was predicted to be functionally benign while the rest (L49S, L69V, A80P, R163H, R163C and R163P) were predicted to be deleterious or associated with disease. All the SNPs were predicted to destabilize the enzyme. Molecular dynamics (MD) simulations were preformed to mimic the behaviour of the apo, holo and drug-bound WT and mutant enzymes in vivo. This was followed by post-MD analysis to identify changes in the local and global motions of the protein in the presence of mutations and changes in intra-protein communication networks through contact map and centrality metrics calculations. RMSD and Rg analyses were performed to assess changes in global motions and compactness of the enzyme in the apo, holo and drug-bound states and in the presence of mutations. These revealed that binding of the ligand had a stabilizing effect on the WT enzyme evident from more steady trends from the analyses across trajectories in the holo and drug-bound enzymes compared to the apoenzyme. The occurrence of mutations had an effect on the global motions and compactness of the enzyme across the trajectories. Most mutations resulted in destabilized systems and less compact structures shown by unsteady RMSD and Rg across trajectories respectively. The drugbound systems appeared to be more stable in most of the systems meaning that the binding of 6MP stabilized the enzyme regardless of the presence of a mutation. RMSF analysis recorded local changes in residue flexibility due to the presence of mutations in all the systems. All the drug-bound mutant systems lost flexibility on the Î±Ahelix which caps the active site. This could have an effect on drug binding and result to defective drug metabolism. The A80P mutation resulted to a more rigid structure from both global and local motions compared to the WT enzyme which could be associated with its nearly loss of function in vivo and in vitro. Dynamic cross correlation calculations were performed to assess how the atoms moved together. Correlated, anti-correlated and areas of no correlations were recorded in all the systems and in similar places when compared to each other. This meant that occurrence of mutations had no effect on how the atoms moved together. Contact map analysis showed that occurrence of mutations caused changes in interactions around the positions where the mutations occurred, which could have an effect on protein structural dynamics. The A80P substitution which occurred on the surface away from the binding site was identified as an allosteric mutation that resulted to changes in the catalytic site. Contact maps for the drug-cofactor complex in the mutant systems in comparison with the WT protein revealed changes that could suggest reorientation of the drug at the catalytic site. This could be an implication to altered drug metabolism. Eigenvector centrality (EC) and betweenness centrality (BC) for the most equilibrated portions of the trajectories were calculated for all the studied systems to identify residues connected to the most important residues and those that were spanned the most in shortest paths connecting other residues. Areas that scored highest in these metrics where mostly found in regions surrounding the catalytic site. Top 5% centrality hubs calculations showed loss of major hubs due to mutations with gaining of new ones. This means that mutations affected communication networks within the protein. The gained hubs were in areas close-by the lost ones which could have been an attempt of the protein to accommodate the mutations. Persistent top 5% BC hubs were identified at positions 90 and 151 while one persistent top 5% EC hub was identified at position 70. This positions play important roles in shaping the catalytic site and are in direct contact with the ligands. It was concluded that in silico techniques and analysis applied in this study revealed possible mechanisms in which genetic variations affected the structural dynamics of TMPT enzyme an affecte 6MP metabolism.
Keywords: Mutation; Thiopurine S-methyltransferase; Mercaptopurine; Molecular dynamics; Protein structure; Structural dynamics