Supplementary Methods
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1 Supplementary Methods MMPBSA Free energy calculation Molecular Mechanics/Poisson Boltzmann Surface Area (MM/PBSA) has been widely used to calculate binding free energy for protein-ligand systems (1-7). In MM/PBSA, binding free energy ( ) for protein and ligand to form a complex was calculated using equation (1), where, and are absolute free energy for complex, protein and ligand, respectively. (1) The free energy for any molecule could be divided into a contribution from the solute and a contribution from the solvent: (2) (3) (4) The contribution from the solute is composed of the gas phase MM energy ( ) and the conformation entropy ( ). could be obtained by average the molecular mechanics energy from the collected snapshots during MD simulation, including (bond, angle and dihedral energies), (electrostatic interaction energy) and (van der Waals interaction energy). The contribution from the solvent is the sum of electrostatic salvation energy (polar contribution),, and non-electrostatic salvation component (non-polar contribution),. The polar contribution is calculated using PB model, while the non-polar contribution is estimated by solvent accessible surface area (SASA) (equation 6). (5) (6) (7) Each energy item is calculated separately by using the conformations extracted from MD trajectory and the binding free energy of forming complex are finally obtained by subtracting the energy terms for complex by those for protein and ligand (equation 7). The snapshots of ligand, protein and complex were taken from single trajectory of MD simulation and used to calculate each free energy items above listed. In the single trajectory strategy, the is canceled between ligand, protein and complex. The non-polar contribution,, is calculated by SASA using the LCPO method. The surface tension proportionally constant and were set to / Å 2 and 0.00 /, respectively. For MMPBSA free energy calculation, the polar contribution of solvent free energy,, was calculated by solving the finite-difference Possion-Boltzmann equation (8). The exterior dielectric constant was set to 80.0 and the solute dielectric constant was set to 2 for the strong polar interactions on the binding interface (3). The entropy calculation is only a rough estimation based on normal mode analysis and time consuming. It is reported the inclusion of this item makes the free energy prediction even worse (7). In this paper, the entropy item is not included in the
2 free energy calculation. The last 2 ns trajectory from production simulation was used to obtain the snapshots for MMGBSA/PBSA free energy calculation and energy decomposition with time interval of 10 fs and totally 200 frames were taken into the calculation. In vitro Enzyme and Cell-based assays The E. coli GUS enzyme assay was performed as a kinetic read assay using the substrate para-nitrophenyl β-d-glucuronide (PNPG). The assay buffer was 50 mm HEPES, ph 7.4 and 0.01% Triton X-100 with final dimethyl sulfoxide (DMSO) concentration adjusted to 1% in all wells. Compound stocks were made with 100% DMSO. The assay was performed by addition of 20 µl compound (various concentrations) diluted with assay buffer/dmso into a clear polystyrene 96-well plate (Costar #9017) followed by 40 µl E. coli GUS enzyme, then a 10 min incubation period followed by the addition of 40 µl PNPG to start the enzyme reaction. Final concentrations in the assay were 1 nm GUS and 300 µm PNPG. The PNG concentration was equivalent to the K m for PNPG determined under these assay conditions. Absorbance at 405 nm was measured every minute for 5 minutes using a BMG PheraStar (BMG Labtech, Cary, NC) plate reader. Rates (absorbance units/min) were determined by linear regression using the plate reader software. Controls were wells with no enzyme (background, 0% activity) and no compound (100% activity). Data from compound treated wells were normalized to these controls to get % Specific Activity and IC 50 data calculated as previously described (9). The GUS cell-based assay and bacterial toxicity assay were performed as previously described (9). Plotted data points represent the average of two or three determinations per concentration and error bars represent standard deviation. Graphs are representative of three independent experiments and IC 50 values were derived by averaging values from all three independent determinations. Histologic score For cell infiltration of inflammatory cells, rare inflammatory cells in the lamina propria were counted as 0; increased numbers of inflammatory cells, including neutrophils in the lamina propria as 1; confluence of inflammatory cells, extending into the submucosa as 2; and a score of 3 was given for transmural extension of the inflammatory cell infiltrate. For epithelial damage, absence of mucosal damage was counted as 0, discrete focal lymphoepithelial lesions were counted as 1, mucosal erosion/ulceration was counted as 2, and a score of 3 was given for extensive mucosal damage and extension through deeper structures of the bowel wall. The two subscores were added and the combined histologic score ranged from 0 (no changes) to 6 (extensive cell infiltration and tissue damage).
3 Supp. Fig. S1 2D structures of Amoxapine, Amoxapine s metabolites, Loxapine, and the previous reported potent GUS inhibitors: Inhibitor 1 and 2.
4 Suppl. Fig. S2 The initial structures (left panel, Before MD ) and the last snapshots (right panel, After MD ) taken from 4 ns MD simulation. F365 and E413 are shown in sticks. The residues nearby the ligand are shown in cartoon. From top to bottom, Amoxapine (AMOX), 7 hydroxyamoxapine (7-OHAMOX), 8 hydroxyamoxapine (8- OHAMOX), and Loxapine. Amoxapine and its 7/8 hyoxyl metabolites are stable in the active site while Loxapine undergoes significant reorientation and relocation. The movement of Loxapine in the active site implies the unstable binding.
5 Supp. Table S1. Hydrogen bonds formed by ligand and protein during the last 2 ns simulation. Ligand Atom from ligand Atom from receptor Average distance a %Occupied Amoxapine NH E413:OE hydroxyamoxapine NH E413:OE hydroxylamoxapine NH E413:OE Loxapine a : Distance between acceptor and donor atoms. Supp. Table. S2 Histologic score and Ki-67-positive cells of the examined tissue vehicle CPT-11 AMOX-1 AMOX-5 Histologic score 0.2± ±0.74 * 2±0.63 # 1.2±0.48 # # of Ki-67-positive cells/20 field 34± ±0.48 * 10.4±3 # 22.2±5 # * p<0.05, vs vehicle; # p<0.01, vs CPT-11
6 1. Wang J, Hou T, Xu X. Recent Advances in Free Energy Calculations with a Combination of Molecular Mechanics and Continuum Models. Current Computer - Aided Drug Design. 2006;2: Hou T, Wang J, Li Y, Wang W. Assessing the performance of the molecular mechanics/poisson Boltzmann surface area and molecular mechanics/generalized Born surface area methods. II. The accuracy of ranking poses generated from docking. Journal of Computational Chemistry. 2011;32: Hou T, Wang J, Li Y, Wang W. Assessing the performance of the MM/PBSA and MM/GBSA methods. 1. The accuracy of binding free energy calculations based on molecular dynamics simulations. J Chem Inf Model. 2011;51: Xu L, Sun H, Li Y, Wang J, Hou T. Assessing the performance of MM/PBSA and MM/GBSA methods. 3. The impact of force fields and ligand charge models. J Phys Chem B. 2013;117: Honig B, Nicholls A. Classical electrostatics in biology and chemistry. Science. 1995;268: Kollman PA, Massova I, Reyes C, Kuhn B, Huo S, Chong L, et al. Calculating Structures and Free Energies of Complex Molecules: Combining Molecular Mechanics and Continuum Models. Accounts of Chemical Research. 2000;33: Yang T, Wu JC, Yan C, Wang Y, Luo R, Gonzales MB, et al. Virtual screening using molecular simulations. Proteins: Structure, Function, and Bioinformatics. 2011;79: Rocchia W, Alexov E, Honig B. Extending the Applicability of the Nonlinear Poisson Boltzmann Equation: Multiple Dielectric Constants and Multivalent Ions. The Journal of Physical Chemistry B. 2001;105: Ahmad S, Hughes MA, Yeh L-A, Scott JE. Potential Repurposing of Known Drugs as Potent Bacterial β-glucuronidase Inhibitors. Journal of Biomolecular Screening. 2012;17:
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