2.1. Sequence conservation of COMT
Sequence alignments of COMT were performed for 13 different species: Homo sapiens, Mus musculus, Bos taurus, Equus caballus, Sus scrofa, Rattus norvegicus, Mycobacterium vanbaalenii, Pichia stipitis, Mycobacterium gilvum, Nicotiana tabacum, Salmo salar, Populus trichocarpa, Papaver somniferum, Thalictrum tuberosum. The software ClustalX 2.0.10 was used to perform the alignment using the Neighbor Joining algorithm with default parameters.
2.2. MD simulation of ligand complexes
The crystal structure of human soluble-COMT (PDB: 3BWM) was used as a starting point for our MD simulations. A caveat of the crystal structure, as published by several groups, is that the inhibitor used to crystallize the protein has a different binding geometry compared to natural ligands. Specifically, since most inhibitors decrease the nucleophilicity of the attacking oxygen with nitrate groups, these ligands bind bidentate to the Mg2+
in the active site. Several groups have proposed that natural substrates of COMT contain a monodentate coordination number in the active site [4
]. Additionally, the interaction between Trp143 and the ligand side chain is possible only after MD simulations [4
Thus, we initially dock either dopamine or levodopa into the active site using the 3,5-dinitrocatechol substrate position as a reference. We adopt a similar simulation methodology as outlined by Kuhn et al in order to obtain our minimized complexes [4
]. Briefly, we simulate our system using the AMBER force field (amber03) and derived constraints for our ligands and S-adenosylmethionine using Antechamber. Parameters for Mg2+
were adjusted according to Kuhn’s values; i.e., an atomic charge of +2, R*Mg
= 0.7868 Å, εMg
= 0.8751 kcal/mol. The crystallographic water remains coordinated to Mg2+
. Additionally, the optimal nonbonded parameters between the attacking oxygen and donor sulfur were derived from Kollman (R*S
= 2.0000 Å, εS
= 0.2500 kcal/mol).
Charges were assigned using RESP, with two Na+ counterions to neutralize charges, and the ligand was solvated with a 20 Å sphere of TIP3P water. The counterions were over 16 Å away from the active site and were fixed to remove potential artificial long-range electrostatic effects. Simulations were performed with a nonbonding cutoff of 16 Å, a time step of 1.5 fs with SHAKE, and at a constant temperature of 300 K using the Berendsen coupling scheme.
For the first minimization, the water molecules were relaxed for 1500 steps while all other atoms remained rigid. The water was then equilibrated using MD simulation for 20 ps. Next, we progressively removed the positional restraints on the protein-ligand complex (from 25 to 0 kcal/(mol Å2)) over a period of 4000 minimization steps. The system then underwent MD equilibration for 20 ps. To avoid loss of water near the vicinity of the protein-ligand complex due to diffusion, the water shell was stripped and a new 20 Å shell of TIP3P was added, minimized, and equilibrated as described above. The protein-ligand complex was then minimized for another 4000 steps followed by an additional 20 ps of MD equilibration. A final minimization of 2000 steps was performed to yield our final structure.
2.3. QM determination of reaction barriers
We used three different models to study the methylation reaction between levodopa/dopamine and trimethylsulfonium (a substitute for S-adenosylmethionine). Model 1 was constructed by modeling only the ligand and trimethylsulfonium. Model 2 was constructed by taking Model 1 and adding four solvation layers of water, followed by minimization. Model 3 was generated from the minimized ligand pose generated using AMBER simulations of COMT with bound ligand [4
]. We included residues coordinated to Mg2+
(as well as its crystallographic water), the catalytic Lys144, and the regioselective Trp144 in our final construct for Model 3. In all models, the reaction coordinate is examined along the sulfur-oxygen axis.
Using a B3LYP functional, we performed a QST2 search for Models 1 and 3 to find the transition state of each methylation reaction using Gaussian03. A mixed basis set of 6-31G for C, H and 6-311+G* for S, Mg, O, and N were used. Reactants of each methylation reaction were computed by geometry optimization. NBO analysis was used to examine the interaction energies between the two ligands. In addition, a level-of-theory study was performed on Model 1 to monitor the effects of changing density functionals on our barrier height calculations.
We calculate the energies of the transition state and reactant for Model 2 by taking the transition state for the simple model in the gas phase and solvating it with four water shells. The water was minimized using molecular mechanics, and then a single point calculation was done at the quantum level (using the same basis set) with the water treated using molecular mechanics. It is important to note that the single point calculations done in explicit solvent likely underestimate the stabilization due to the polarization of water since the dielectric response of water is primarily determined by its orientational dynamics. Nonetheless Model 2 serves as an estimate of the methylation reaction occurring in an aqueous environment.