Supplementary Information for The importance of functional monomer dimerization in molecular imprinting process Authors: Yagang Zhang, Di Song, Laura M. Lanni, Ken D. Shimizu* Department of Chemistry and Biochemistry, University of South Carolina, Columbia, South Carolina 2928 Fax:(83)-777-9521 Tel:(83)-777-6523 shimizu@mail.chem.sc.edu S-1
Table of Contents 1. General Information..... S3 Jobʼs plots of EA9A and MAA...S3 Binding constant of TEA and MAA..S4 2. Computer simulation with COPASI program...s5 3. Surface area measurements by BET. S23 S-2
1. General Information 1 H NMR spectra were recorded on a Varian 3 MHz NMR at ambient temperature. Chemical shifts (ppm) were referenced to tetramethylsilane or residual protonated solvent. UV measurements were made using a Jasco V-53 spectrometer. Solvents were purchased from Sigma-Aldrich, Fisher, VWR, and were purified and dried by passing through a PURE SOLV solvent purification system (Innovative Technology). Deuterated solvents were purchased from Cambridge Isotope Laboratories. All other reagents were purchased from Sigma-Aldrich and were used as received. Surface area and nitrogen adsorption isotherms were calculated using the Brunauer-Emmett-Teller (BET) model. Gas adsorption studies were carried out using Quantachrome Autosorb Automated Gas Sorption System. 1.1 Jobʼs plot of EA9A and MAA Continuous variation analysis (Jobʼs plot) at 8.5 mm in CD 3 CN showed MAA to EA9A stoichiometry between 2:1 and 1:1. To determine the stoichiometry, data points on each side of the maximum chemical shift was fitted to a straight line. The x-value at cross point was analytically determined from the equations from the fitted lines. Measurement of Jobʼs plot was not possible at concentration higher than 8.5 mm due to the solubility limit of EA9A in acetonitrile. Although carboxylic acids such as MAA can form higher order (2:1 and 3:1) complex with adenine guests such as ethyl adenine-9-acetate (EA9A), the first order complex will dominate in CD 3 CN because chances are slim to form higher order complexes based on the probability of placing two or three functional monomer around the template molecule. S-3
.4 change in chemical shift of EA9A-NH.3.2.1.2.4.6.8 1 EA9A in MAA (mole %) Figure S1. Jobʼs plot for MAA and EA9A at 8.5 mm CD 3 CN showing a MAA to EA9A stoichiometry of 1.4:1 by monitoring chemical shifts of the EA9A amino protons. 1.2 Binding constant of TEA and MAA Experimental binding constant between triethylamine (TEA) and MAA in acetonitriled3 were obtained by NMR titration. NMR titrations were performed using TEA and freshly distilled MAA in dry acetonitrile-d3. To a 7 μl solution of 25.8 mm TEA were added aliquots of a MAA solution (411 mm) until final MAA concentration is 3 mm. The measured chemical shift of the TEA-CH 2 protons were fitted to a 1:1 binding model to yield a Ka = 28 M -1. S-4
.7 Chemical shift of TEA -CH2 proton.6.5.4.3.2.1 5 1 15 2 25 3 [MAA] (mm) Figure S2. 1 H NMR titration curve of the addition of MAA (411 mm) to TEA (25.8 mm) in CD 3 CN. The measured chemical shift of the TEA-CH 2 protons were fitted to a 1:1 binding model to yield a Ka = 28 M -1. 2. Computer simulation with COPASI program To study the influence of monomer dimerization on the imprinting effect, the equilibrium processes in the prepolymerization mixture were modeled using the computer program COPASI (Bioinformatics. 26, 22, 367-374). COPASI is a free program which can be downloaded at: http://www.copasi.org COPASI Version 4.5 was used to simulate the imprinting and dimerization processes in the prepolymerization mixture. The assumption was made that the distributions of various monomer-template complexes in the prepolymerization mixture are representative of those found in the resulting polymerized monolith. S-5
First step in the simulation is to set up the multiple reversible equilibriums as shown in eq 1, 2, 3, and 4 where M and T are the concentrations of monomer and template respectively. M + M M 2 M + T MT + M M 2 T + M K dim K a1 K a2 K a3 MT M 2 T M 3 T (1) (2) (3) (4) K a1 /3 = K a2 = 3 K a3 (5) K dim is the association constant to form dimer. K a1 is the association constant to form first order complex. K a2 is the association constant to form second order complex and K a3 is the association constant to form third order complex. The relationships between K a1, K a2, and K a3 are based on the decreasing statistical probability of complex formation on the three binding sites on the template (eq 5). To set up equilibriums, go to Model\Biochemical\Reactions. Put equilibriums in the boxes where it says Equation. Second step in the simulation is to input initial variables such as experimental concentration of monomer [M], experimental concentration of template [T], experimental association constant for forming dimer or monomer-template complex. Various association constant was used to simulate the effect of adding polar solvent to the prepolymerization mixture upon forming different type of binding sites. initial variables can be set by going to Parameter Overview. Third step is to do the calculation. Go to Tasks\Steady-State and run the calculation. Final step is to record the output data: equilibrium concentration of each species in the process of forming different types of complexes. From the output results, the S-6
equilibrium concentration of specifically defined species such as selective sites, background sites or ratio of selective/background can be calculated and analyzed. 2.1 Simulation of MIP and NIP with and without dimerization by using experimental data. MIP and NIP without dimerization For MIP equilibrium equations were established as follows: M + T = MT (K a1 ) MT + M = M2T (K a2 ) M2T + M = M3T (K a3 ) Initial variables were set as follows: [M] =.2 M [T] =.2 M K exp = K a1 = 7.5 M -1 K a1 /3 = K a2 = 3 K a3 For NIP equilibrium equations were established as follows: M + T = MT MT + M = M2T M2T + M = M3T Initial variables were set as follows: [M] =.2 M [T] =.2 M K a1 = 1. M -1 S-7
K a1 /3 = K a2 = 3 K a3 MIP and NIP with dimerization For MIP equilibrium equations were established as follows: M + M = M2 M + T = MT MT + M = M2T M2T + M = M3T Initial variables were set as follows: [M] =.2 M [T] =.2 M K a1 = 7.5 M -1 K a1 /3 = K a2 = 3 K a3 For NIP equilibrium equations were established as follows: M + M = M2 M + T = MT MT + M = M2T M2T + M = M3T Initial variables were set as follows: [M] =.2 M [T] =.2 M K a1 = 1. M -1 K a1 /3 = K a2 = 3 K a3 S-8
Define selective sites as sum of the final concentration of [MT]+[M2T]+[M3T] Define non-selective sites as the final concentration of [M] Define demerized sites as the final concentration of [M2] Define total number of sites as sum of the final concentration of [M]+[MT]+[M2T]+[M3T] Table S1. Simulation results of concentrations of different types of binding sites. [M] [MT] [M2T] [M3T] [M2] MIP without dimerization.181.886.42.64 MIP with dimerization.124.828.257.265.38 NIP without dimerization.196.325.21 4.54E-6 NIP with dimerization.13.229 9.82E-5 1.4E-6.338 Table S2. Simulation results of percentages of different types of binding sites. sel sites total sites [M]% [MT]% [M2T]% [M3T]% [M2]% sel sites% MIP without dimerization.135.195.931.455.26.31.692 MIP with dimerization.11.166.747.499.155.159.186.669 NIP without dimerization.346.2.983.163.15 2.27E-5.173 NIP with dimerization.239.166.782.138.591 8.44E-6.23.144 2.2 Simulation of the effect of having a higher binding constant relative to K d (increading K d /K a2 ) upon final concentration of different types of binding sites For MIP with dimerization, equilibrium equations were established as follows: M + M = M2 M + T = MT S-9
MT + M = M2T M2T + M = M3T Define selective sites as sum of the final concentration of [MT]+[M2T]+[M3T] Define non-selective sites as the final concentration of [M] Define total number of sites as sum of the final concentration of [M]+[MT]+[M2T]+[M3T] Initial variables were set as follows: [M] =.2 M [T] =.2 M K a1 =7.5 M -1, K a1 /3 = K a2 = 3 K a3, K d /K a2 varying from.1 to 1. K a1 =1 M -1, K a1 /3 = K a2 = 3 K a3, K d / K a2 varying from.1 to 1. K a1 =2 M -1, K a1 /3 = K a2 = 3 K a3, K d / K a2 varying from.1 to 1. K a1 =3 M -1, K a1 /3 = K a2 = 3 K a3, K d / K a2 varying from.1 to 1. total number of background sites.2.18.16.14.12.1.8.6.4.2 Ka2=1 Ka2=3.3 Ka2=6.66 Ka2=2.5.2.4.6.8 1 Kd/K a2 S-1
Figure S3. Simulation of the influence of increasing K d /K a2 upon total number of background sites. total number of selective sites.2.18.16.14.12.1.8.6.4.2 Ka2=1 Ka2=6.66 Ka2=3.3 Ka2=2.5.2.4.6.8 1 Kd/K a2 Figure S4. Simulation of the influence of increasing K d /K a2 upon total number of background sites. S-11
.25 ratio of selective/background sites.2.15.1.5 Ka2=1 Ka2=3.3 Ka2=6.66 Ka2=2.5.2.4.6.8 1 Kd/K a2 Figure S5. Simulation of the influence of increasing K d /K a2 upon the ratio of selective/background sites..25.2 total number of sites.15.1.5 Ka2=1 Ka2=3.3 Ka2=6.66 Ka2=2.5.2.4.6.8 1 Kd/K a2 Figure S6. Simulation of the influence of increasing K d /K a2 upon total number of sites. S-12
.94 percent of background sites.92.9.88.86.84.82.8 Ka2=1 Ka2=6.66 Ka2=3.3 Ka2=2.5.2.4.6.8 1 Kd/K a2 Figure S7. Simulation of the influence of increasing K d /K a2 upon percentage of background sites..2.18 percent of selective sites.16.14.12.1.8.6.4.2 Ka2=1 Ka2=3.3 Ka2=6.66 Ka2=2.5.2.4.6.8 1 Kd/K a2 Figure S8. Simulation of the influence of increasing K d /K a2 upon percentage of selective sites. S-13
2.3 Simulation of the influence of adding polar solvent in prepolymerization solution upon different types of binding sites. For MIP and NIP with dimerization, reversible equilibrium equations were established as follows: M + M = M2 M + T = MT MT + M = M2T M2T + M = M3T Define selective sites as sum of the final concentration of [MT]+[M2T]+[M3T] Define non-selective sites as the final concentration of [M] Define demerized sites as the final concentration of [M2] Define total number of sites as sum of the final concentration of [M]+[MT]+[M2T]+[M3T] Ratio of selective/non-selective sites is defined as ([MT]+[M2T]+[M3T])/ ([M]) Initial variables were set as follows: Initial concentration [M] =.2 M, [T] =.2M Adding polar solvent will disrupt both dimerization and templation, thus both K d and K a2 decrease upon adding more polar solvent additives. The effects of the polar solvents on the prepolymerization equilibriums were modeled using the parameter s. Numerically s equals 2/K d. The additions of increasing concentrations of polar solvents were simulated by increasing the factor s, which systematically weakened the monomer-template and dimer complexes. In this simulation process for MIP, K a2 varied from 9 to.9, K d varied from 3 to.3, and the ratio of K a2 /K d = 3 is kept constant. In the simulation process for NIP, K a2 was set as.1, K d varied from 3 to.3. S-14
.2 total number of background sites.18.16.14.12.1.8 MIP adding polar solvent 2 4 6 8 s Figure S9. Influence of increasing amount of polar solvent additives (increasing s) in prepolymerization solution upon total number of background sites in MIP. total number of selective sites.2.18.16.14.12.1.8.6.4.2 MIP adding polar solvent 2 4 6 8 s Figure S1. Influence of increasing amount of polar solvent additives (increasing s) in prepolymerization solution upon total number of selective sites in MIP. S-15
.2 total number of sites.18.16.14.12.1 MIP adding polar solvent.8 2 4 6 8 s Figure S11. Influence of increasing amount of polar solvent additives (increasing s) in prepolymerization solution upon total number of sites in MIP. 1 percent of background sites.95.9.85 MIP adding polar solvent.8 2 4 6 8 s Figure S12. Influence of increasing amount of polar solvent additives (increasing s) in prepolymerization solution upon percentage of background sites in MIP. S-16
percent of selective sites.16.14.12.1.8.6.4.2 MIP adding polar solvent 2 4 6 8 s Figure S13. Influence of increasing amount of polar solvent additives (increasing s) in prepolymerization solution upon percentage of selective sites in MIP..22 total number of background sites.2.18.16.14.12.1.8 NIP adding polar solvent 2 4 6 8 s Figure S14. Influence of increasing amount of polar solvent additives (increasing s) in prepolymerization solution upon total number of background sites in NIP. S-17
.12 total number of selective sites.11.1.9.8.7 NIP adding polar solvent.6 2 4 6 8 s Figure S15. Influence of increasing amount of polar solvent additives (increasing s) in prepolymerization solution upon total number of selective sites in NIP..22.2 total number of sites.18.16.14.12.1.8 NIP adding polar solvent 2 4 6 8 s Figure S16. Influence of increasing amount of polar solvent additives (increasing s) in prepolymerization solution upon total number of sites in NIP. S-18
2.4 Simulation of the influence of increasing K d (when K a kept constant) upon the final concentration of different types of sites For MIP and NIP with dimerization, reversible equilibrium equations were established as follows: M + M = M2 M + T = MT MT + M = M2T M2T + M = M3T Define selective sites as sum of the final concentration of [MT]+[M2T]+[M3T] Define non-selective sites as the final concentration of [M] Define demerized sites as the final concentration of [M2] Define total number of sites as sum of the final concentration of [M]+[MT]+[M2T]+[M3T] Ratio of selective/non-selective sites is defined as ([MT]+[M2T]+[M3T])/ ([M]) Initial variables were set as follows: Initial concentration [M] =.2 M, [T] =.2M In the simulation: K a2 was kept constant at.33, K d varied from.1 to 1, K a2 was kept constant at 2.5, K d varied from.1 to 1, K a2 was kept constant at 1, K d varied from.1 to 4, K a2 was kept constant at 3, K d varied from.1 to 12. S-19
total number of selective sites [M].34.3.26.22.18.14 K a2 =.33 2 4 6 8 1 K d Figure S17. Simulation of the influence of increasing K d upon total number of selective sites when K a2 is hold constant (K a2 =.33) for MIP.14 total number of selective sites [M].13.12.11.1.9.8 K a2 =2.5.7 2 4 6 8 1 K d Figure S18. Simulation of the influence of increasing K d upon total number of selective sites when K a2 is hold constant (K a2 =2.5) for MIP S-2
total number of selective sites [M].2.19.18.17.16.15.14.13.12 K a2 =1 5 1 15 2 25 3 35 4 K d Figure S19. Simulation of the influence of increasing K d upon total number of selective sites when K a2 are hold constant (K a2 =1) for MIP.2 total number of selective sites [M].195.19.185.18.175.17.165.16.155.15 K a2 =3 2 4 6 8 1 12 K d Figure S2. Simulation of the influence of increasing K d upon total number of selective sites when K a2 are hold constant (K a2 =3) for MIP S-21
.25 Ka2=.33 Ka2=2.5 total number of selective sites [M].2.15.1.5 Ka2=1 Ka2=3 1 2 3 4 5 6 7 8 9 1 K d Figure S21. Simulation of the Influence of increasing K d upon total number of selective sites for MIP when K a2 are hold constant (K a2 =.33, 2.5, 1, 3 respectively).22 total number of background sites [M].2.18.16.14.12.1.8.6 Ka2=.33 Ka2=1 Ka2=2.5 Ka2=3 1 2 3 4 5 6 7 8 9 1 K d Figure S22. Simulation of the Influence of increasing K d upon total number of background sites for MIP when K a2 are hold constant (K a2 =.33, 2.5, 1, 3 respectively) S-22
percent of selective sites (%) 25 2 15 1 5 Ka2=.33 Ka2=1 Ka2=2.5 Ka2=3 2 4 6 8 1 K d Figure S23. Simulation of the Influence of increasing K d upon percentage of selective sites for MIP when K a2 are hold constant (K a2 =.33, 2.5, 1, 3 respectively) 3. Gas adsorption porosimetry. The washed and dried polymers were degassed for 16 h at 5 C and analyzed by nitrogen adsorption porosimetry (Quantachrome Autosorb Automated Gas Sorption System. Surface areas and average pore diameter were obtained by the Brunauer- Emmett-Teller (BET) method at 77.35 K. Results showed that MIPs and NIPs have surface area about 45-5 m 2 /g and average pore diameter 67-8 Å. Table S3. Surface areas, pore diameters, and binding capacities of MIPs and NIPs d formed in different solvent mixtures. polymer EA9A polymerization surface average binding S-23
(mmol) solvent(s) a area (m 2 /g) b pore Diameter (Å) b capacity (µmol/g) c MIP.11 CH 3 CN 45 8 3.6 MIP(25% AcOH).11 25 v/v% AcOH/CH 3 CN 5 67 1.9 NIP ------- CH 3 CN 46 72.55 NIP(25% MeOH) ------- 25 v/v% MeOH/CH 3 CN 5 68 1.8 a Polymers were polymerized with.2 mmol AIBN in a sealed vial (65 C, 6 h) in 4 ml solvent. b Surface areas and pore diameters were calculated from a multipoint nitrogen adsorption isotherm using a Brunauer-Emmett-Teller model. c Binding capacities for EA9A were measured by the change in the absorption (257 nm) of EA9A acetonitrile solutions (.1 mm, 2.5 ml) after equilibration with 6 mg polymer. d 1.1 mmol of MAA and 9.54 mmol of EGDMA were used to prepare each polymer. Nitrogen adsorption isotherms of MIPs and NIPs from BET measurements. S-24
volume (cc/g) 18 16 14 12 1 8 6 4 2 MIP (in CH 3 CN)..2.4.6 relative pressure (P/Po) Figure S24. Nitrogen adsorption isotherms of MIP (CH 3 CN) analyzed using the multipoint Brunauer-Emmett-Teller (BET) method at 77.35 K. 2 18 volumbe (cc/g) 16 14 12 1 8 MIP (in 25% AcOH/CH 3 CN) 6 4 2..2.4.6 relative pressure (P/Po) Figure S25. Nitrogen adsorption isotherms of MIP (in 25% AcOH/CH 3 CN) analyzed using the multi-point Brunauer-Emmett-Teller (BET) method at 77.35 K. S-25
volume (cc/g) 18 16 14 12 1 8 6 4 2 NIP (in CH 3 CN)..1.2.3.4.5 relative pressure (P/Po) Figure S26. Nitrogen adsorption isotherms of MIP (CH 3 CN) analyzed using the multipoint Brunauer-Emmett-Teller (BET) method at 77.35 K. 2 18 16 volume (cc/g) 14 12 1 8 6 4 2 NIP (in 25% MeOH/CH 3 CN)..1.2.3.4.5 relative pressure (P/Po) Figure S27. Nitrogen adsorption isotherms of MIP (in 25% MeOH/CH 3 CN) analyzed using the multi-point Brunauer-Emmett-Teller (BET) method at 77.35 K. S-26