A Rational Design, Synthesis, Biological Evaluation and Structure

Dec 15, 2015 - In the present study, a series of novel maleimide derivatives were rationally designed and optimized, and their inhibitory activities a...
0 downloads 10 Views 3MB Size
Article pubs.acs.org/jcim

A Rational Design, Synthesis, Biological Evaluation and Structure− Activity Relationship Study of Novel Inhibitors against Cyanobacterial Fructose-1,6-bisphosphate Aldolase Xinya Han,†,§ Xiuyun Zhu,†,§ Shuaihua Zhu,†,§ Lin Wei,† Zongqin Hong,† Li Guo,‡ Haifeng Chen,† Bo Chi,† Yan Liu,† Lingling Feng,† Yanliang Ren,*,† and Jian Wan*,† †

Key Laboratory of Pesticide & Chemical Biology (CCNU), Ministry of Education, Department of Chemistry, Central China Normal University, Wuhan, Hubei 430079, China ‡ Hubei Environmental Monitoring Central Station, Wuhan, Hubei 430072, China S Supporting Information *

ABSTRACT: In the present study, a series of novel maleimide derivatives were rationally designed and optimized, and their inhibitory activities against cyanobacteria class-II fructose-1,6-bisphosphate aldolase (Cy-FBA-II) and Synechocystis sp. PCC 6803 were further evaluated. The experimental results showed that the introduction of a bigger group (Br, Cl, CH3, or C6H3-o-F) on the pyrrole-2′,5′-dione ring resulted in a decrease in the Cy-FBA-II inhibitory activity of the hit compounds. Generally, most of the hit compounds with high Cy-FBA-II inhibitory activities could also exhibit high in vivo activities against Synechocystis sp. PCC 6803. Especially, compound 10 not only shows a high Cy-FBA-II activity (IC50 = 1.7 μM) but also has the highest in vivo activity against Synechocystis sp. PCC 6803 (EC50 = 0.6 ppm). Thus, compound 10 was selected as a representative molecule, and its probable interactions with the surrounding important residues in the active site of Cy-FBA-II were elucidated by the joint use of molecular docking, molecular dynamics simulations, ONIOM calculations, and enzymatic assays to provide new insight into the binding mode of the inhibitors and Cy-FBA-II. The positive results indicate that the design strategy used in the present study is very likely to be a promising way to find novel lead compounds with high inhibitory activities against Cy-FBA-II in the future. The enzymatic and algal inhibition assays suggest that Cy-FBA-II is very likely to be a promising target for the design, synthesis, and development of novel specific algicides to solve cyanobacterial harmful algal blooms.



INTRODUCTION Cyanobacterial harmful algal blooms (CHABs) have been increasing in frequency all over the world.1 Toxin-producing CHABs have posed a serious water pollution problem that impacts human health, living resources, and water economies.2 Approaches to control these CHABs can be classified as mechanical, physical/chemical, and biological. In comparison, chemical control is the most effective method. Chemical control involves the use of copper compounds, chemical oxidants, and herbicides.1 Nevertheless, none of these compounds were designed or developed for exclusive targeting of enzymes of cyanobacteria. Thus, the utility of chemical control has significant limitations. Compound design based on the specific target (critical enzyme) of cyanobacteria may provide a useful strategy for the development of potential algicides. Photosynthesis supplies all of the organic compounds and most of the energy and thus is arguably the most important biological process on earth.3 In the Calvin cycle of photoautotrophic organisms, fructose-1,6-bisphosphate aldolase (FBA, EC 4.1.2.13) is an essential regulatory enzyme. FBA catalyzes the reversible cleavage of fructose-1,6-biphosphate © XXXX American Chemical Society

(FBP) to dihydroxyacetone phosphate (DHAP) and glyceraldehyde 3-phosphate (GAP).4−6 FBA can be separated into two classes on the basis of differences in the reaction mechanism (Figure 1) and distribution in the biosphere.7 Class-I FBA (FBA-I), which was originally found in animals, plants, and protozoans, forms a Schiff base intermediate between the keto substrate (FBP or DHAP) and a lysine residue of the active site. In comparison, class-II FBA (FBA-II) utilizes a divalent metal ion to polarize the keto carbonyl group of the substrate (FBP or DHAP) and has been found in bacteria and fungi.8 Because FBA-II occurs in many pathogenic microbes and is absent in animals, it has been viewed as a particularly attractive new target, and much attention has been focused on drug design for FBA-II.7,9,10 Putative genes encoding both FBA-I and FBA-II have been found in the whole genome sequence database of cyanobacteria.11 However, it seems that in cyanobacteria, FBA-II usually represents approximately 90% of the total extractable FBA activity.6 Moreover, Nakahara et al.6 reported that FBA-I is Received: October 10, 2015

A

DOI: 10.1021/acs.jcim.5b00618 J. Chem. Inf. Model. XXXX, XXX, XXX−XXX

Article

Journal of Chemical Information and Modeling

Figure 1. Mechanisms of class-I and class-II FBAs.

Materials. All of the solvents and reagents were of analytical grade unless stated otherwise. Triosephosphate isomerase (TIM) from rabbit muscle, glycerol 3-phosphate dehydrogenase (GPDH) from rabbit muscle, and FBA from rabbit muscle were purchased from Sigma Corporation. The Cy-FBA-II recombinant protein was expressed in Escherichia coli BL21 (DE3) cells as described previously.10 Synechocystis PCC 6803 was obtained from Dr. Haibo Jiang (Central China Normal University). 1H and 13C NMR spectra were recorded on a Varian Mercury-Plus 400 or 600 MHz spectrometer in CDCl3, DMSO-d6, or acetone-d6. Chemical shifts are given in parts per million with tetramethylsilane as the internal reference. Flash chromatography purifications were performed on Merck silica gel 60 (230−400 mesh) as the stationary phase, and MeOH and CH3COCH3 were used as eluents. High-resolution mass spectrometry (HRMS) analysis was performed using a hybrid IT-TOF mass spectrometer with an electrospray ionization (ESI) interface (Shimadzu, Kyoto, Japan) and an Agilent 6224 Accurate-Mass time-of-flight mass spectrometer with an ESI interface (Agilent Technologies, Waldbronn, Germany). General Procedure for the Preparation of Compounds 1−26. Maleic anhydride (2.5 mmol) was added slowly to a solution of the substituted benzohydrazide (2.5 mmol) in 20 mL of acetic acid. The mixture was stirred under reflux for 4 h, and the solvent was evaporated under reduced pressure to yield the product 1−26, which was separated by column chromatography.23 The 1H and 13C NMR spectra of compounds 1−26 are listed in the Supporting Information. Enzymatic Inhibition Activity. To evaluate the inhibitory activities of the hit compounds synthesized in the present study, the half-maximal inhibitory concentration (IC50) values of the hit compounds were also determined at the Cy-FBA-II recombinant protein level as described previously.6,10 Briefly, the reaction was performed in a mixture containing 50 mM Tris-HCl buffer (pH 7.5), 0.2 mM CoCl2, 0.2 mM NADH, 0.5 unit each of TIM and GPDH, the hit compound at the desired concentration, and 0.4 mM FBP in a final volume of 0.22 mL. The reaction progress was measured by monitoring the decrease in absorbance of NADH at 340 nm on the microplate reader (BioTek Synergy 2) over 5 min at 30 °C. The IC50 value was determined from the inhibition curve, in which the inhibition rate was plotted against the concentration of the test compound. The inhibition rate (%I) was calculated using the following formula: %I = [(V0 − V)/V0] × 100%, where V0 and V represent the maximum velocity ([I] = 0 μM) and the velocity when inhibitor was added, respectively. The curves

functionally superfluous in Synechocystis sp. PCC 6803, while attempts to disrupt the FBA-II gene were not successful. In view of these crucial roles and functions of cyanobacterial FBAII (Cy-FBA-II), it is a good candidate target for the development of specific algicides. We previously reported a series of dual-target compounds aimed at Cy-FBA-II and cyanobacterial fructose-1,6-bisphosphatase (Cy-FBPase).10 To find a specific inhibitor against Cy-FBA-II, a series of novel maleimide derivatives have been successfully designed and synthesized by means of a structure-based drug design strategy. Indeed, the biological activities of maleimide derivatives have been documented, such as glycogen synthase kinase-3 inhibitors,12 monoglyceride lipase inhibitors,13 cyclooxygenase inactivators,14 antibiotics,15 and topoisomerase IIα inhibitors.16 To further understand the influence of different substituents of maleimide derivatives on the Cy-FBA-II inhibitory activity, comparative molecular field analysis (CoMFA) was also performed. Following this, a further study combining structure−activity relationship (SAR) analysis and optimized synthesis was carried out, and the proposed binding model of novel inhibitors targeting Cy-FBA-II was systematically identified.



MATERIALS AND METHODS Molecular Dynamics Simulations. Homology modeling of the three-dimensional (3D) conformation of Cy-FBA-II and the docking procedure were described in our previous work.10 The title compounds were constructed and optimized with the Tripos force field and Gasteiger−Huckel charges using SybylX1.3. Hydrogen atoms were added to the protein to allow for appropriate ionization at physiological pH. The whole protein was optimized using the AMBER force field.17,18 The hit compounds were docked into Cy-FBA-II using Surflex-Dock.19 To confirm the binding mode of representative molecule 10, molecular dynamics (MD) simulations were performed using the PMEMD module in the AMBER12 package20 based on the docking Cy-FBA-II complex with compound 10. The partial atomic charges of ligands were calculated using the restricted electrostatic potential (RESP)21 fitting protocol as implemented in the Antechamber module. The AMBER ff10 force field was used for the protein parameters, whereas the general AMBER force field was used for the parameters of ligand. Na+ ions were added to neutralize the system, which was then solvated in an octahedral box of TIP3P water molecules22 that extended at least 10 Å from any given protein atom of Cy-FBAII. B

DOI: 10.1021/acs.jcim.5b00618 J. Chem. Inf. Model. XXXX, XXX, XXX−XXX

Article

Journal of Chemical Information and Modeling

Figure 2. Optimization strategy leading from compound FBA5 to compound 1. (A) Structure of the unoptimized hit compound FBA5. (B) Structure of the optimized hit compound 1. (C) Binding model of compound FBA5 with Cy-FBA-II. (D) Binding model of compound 1 with CyFBA-II.

were fitted by nonlinear regression using logistic equation in the Origin 7.7 software. Inhibitory Assay on Synechocystis sp. PCC 6803. Synechocystis sp. PCC 6803 was cultured photoautotrophically in BG11 medium24 at 28 °C for 12 h in the light and 12 h in the dark alternatively at 50−55% relative humidity for 7 days in 96-well microtiter plates as described previously.10 The inhibition rate of the test compound on the cyanobacteria growth was determined by the following equation: %I = {1 − [(ODt680 − ODi680)/OD0680]} × 100%, where OD0680 and ODt680 are the optical densities at 680 nm for the cyanobacteria in the dimethyl sulfoxide (DMSO) control and test-compoundtreated cultures, respectively, and ODi680 is the optical density at 680 nm for the test compound in each assay. The halfmaximal effective concentration (EC50) values were obtained from the inhibition curves showing the inhibition rate versus the concentration of hit compound. The curves were fitted by nonlinear regression using logistic equation in the Origin 7.7 software. Three-Dimensional Quantitative Structure−Activity Relationships. The CoMFA model was obtained from the enzymatic inhibitory activities of 26 compounds (22 compounds for training sets and four compounds for test sets) against Cy-FBA-II. The inhibitory activities were converted into D values using the equation D = −log(IC50). The representative compound 10 was chosen as a template for superimposition. The default parameters of the steric and electrostatic interaction fields of CoMFA in Sybyl-X1.3 were used: a 2.0 Å spaced grid, an sp3 carbon probe atom with a van der Waals radius of 1.52 Å, and a charge of +1.0. The CoMFA steric and electrostatic fields were scaled with a default cutoff energy of 30

kcal/mol by the CoMFA-STD method25 in Sybyl-X1.3. A partial least-squares (PLS) approach26 was used to derive 3D quantitative structure−activity relationship (3D-QSAR) models in which the experimental D value was used as the dependent variable and the CoMFA descriptors were used as independent variables. The cross-validation with the leave-one-out option and were performed using the SAMPLS program27 to obtain the optimal number of components (n) and cross-validation coefficient (q2). Then a non-cross-validated analysis without column filtering was applied to get the regression coefficient (r2) along with its standard error (S) and the F-test value (F) for the CoMFA model evaluation.



RESULTS AND DISCUSSION Structure-Based Virtual Screening of Novel Hit Compounds against Cy-FBA-II. The homology modeling of the 3D conformation of Cy-FBA-II and the docking procedure were described in our previous work.10 On the basis of the structural and interactional information for CyFBA-II and the corresponding substrates, a specific protocol of virtual screening (as illustrated in Figure S1) was generated and performed to obtain novel hit compounds that target Cy-FBAII. In the first step, 1D ligand-based searching in terms of Lipinski rules28 was performed to preselect the compounds out of the Specs database that were more likely to yield cellpermeable compounds. After the first step, about 100 000 compounds were extracted. Then all of the preselected 1D compounds were transformed into 3D conformations using the CONCORD module of Sybyl 7.3.29 As reported in previous studies,30−32 FBA-II requires a divalent metal ion (zinc or cobalt ion) to polarize the keto carbonyl group of the substrate C

DOI: 10.1021/acs.jcim.5b00618 J. Chem. Inf. Model. XXXX, XXX, XXX−XXX

Article

Journal of Chemical Information and Modeling

Table 1. Substitution Patterns of Compounds 1−26 and Their Inhibition Activities against Cy-FBA-II and Synechocystis sp. PCC 6803

a

compd

R1

R2

R3

R4

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26

OH H H H H H H H H H H H H H H H H H H H OH H H OH H H

H H CH3 Br F NO2 OH H H H H H H OH H H H H H H H OH H H OH H

H H H H H H H CF3 CH3 Br F NO2 OH OH H Br CF3 H Br CF3 H H H H H H

H H H H H H H H H H H H H H H H H H H H H OH H H OH H

R5 H H H H H H H H H H H H H H Br Br Br Cl Cl Cl Cl Cl CH3 CH3 CH3 C6H3-o-F

R6

IC50 (μM)

H H H H H H H H H H H H H H H H H Cl Cl Cl Cl Cl CH3 CH3 CH3

8.9 ± 0.8 3.2 ± 0.4 2.4 ± 0.5 1.5 ± 0.2 5.0 ± 1.0 2.3 ± 0.4 2.5 ± 0.5 3.8 ± 0.4 1.9 ± 0.2 1.7 ± 0.5 4.0 ± 0.5 4.8 ± 0.2 3.4 ± 0.3 2.8 ± 0.4 13.2 ± 2.8 3.0 ± 0.3 10.7 ± 2.7 24 ± 2 25 ± 1 30 ± 2 29 ± 2 20 ± 1 4%a 5%a 3%a 5%a

Hill coefficient

EC50 (ppm)

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

10.9 ± 1.2 1.5 ± 0.2 6.7 ± 0.2 5.9 ± 0.6 8.4 ± 1.2 12.3 ± 1.3 9.3 ± 2.5 3.2 ± 0.7 3.0 ± 0.2 0.6 ± 0.1 2.4 ± 0.6 5.5 ± 0.3 7.2 ± 0.9 10.2 ± 1.5 11.8 ± 0.9 18 ± 1 19 ± 2 29 ± 5 27 ± 2 > 71 10.8 ± 1.2 >63 − − − −

1.1 0.6 0.8 1.1 0.7 0.9 0.9 1.0 0.8 1.1 1.0 0.7 0.9 1.1 0.8 0.8 1.0 1.1 1.2 1.2 1.3 0.9 − − − −

0.1 0.1 0.1 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.1 0.1 0.2 0.1 0.1 0.1 0.1

The inhibition rates were determined at 300 μM tested compound.

formed, and the top 10 000 compounds were selected. Subsequently, we observed one-by-one the interactions between the compounds and Cy-FBA-II using Sybyl-X1.3 graphics windows. Those compounds with similar skeletons and different substituent groups were collected into one cluster. Thus, a total of about 100 structure clusters were generated by the step described above. Among each cluster, we selected out about five compounds by jointly considering their dock scoring rank and observing their docked conformation: compounds with high docking scores and interactions with the Zn(II) ion in Cy-FBA-II were selected. Thus, a total of ∼500 “best” hit compounds were selected. Finally, according to our drug design experiences, 32 representative potential hit compounds were selected and purchased from Specs Corporation, and the corresponding inhibitory activities against Cy-FBA-II were further examined (Table S1). Compound FBA5 exhibited a high inhibitory ratio (>70%) against Cy-FBA-II, and thus, its IC50 value was further determined. Fortunately, compound FBA5 exhibits moderate inhibitory activity against Cy-FBA-II (IC50 = 17.8 μM). Rational Design of Novel Cy-FBA-II Inhibitors. To discover more potent inhibitors, insight into the accurate binding mode of FBA5 was essential. Thus, compound FBA5 was docked into the active site of Cy-FBA-II using the SurflexDock module in the Sybyl-X1.3 software. The possible binding

(FBP or DHAP) and stabilize the enediolate intermediate formed during catalysis, which is remarkably different from the requirements for FBA-I. Thus, the coordination with a divalent metal ion is a predominant factor for the binding of its ligand, which actually has been confirmed by the complexed crystallographic structures of FBA-II and its ligands.30,33 Thus, the Zn(II) ion was the most important pharmacophore for the design of novel Cy-FBA-II inhibitors. FlexX-Pharm, which enables pharmacophore-type constraints to be used in FlexX to guide ligand docking,34 was used to define spatial and pharmacophore constraints in the docking screening process based on Cy-FBA-II out of the Specs database as mentioned before. The spatial constraint defined by a distance from the Zn(II) ion of 3.5 Å or less was used in the FlexX-Pharm docking. Under this constraint, only compounds docked into the cavity of Cy-FBA-II that met this restrictive condition were selected out immediately for a further judgment by scoring function. After the FlexX-Pharm procedures were applied to Cy-FBA-II, approximately 50 000 compounds were retained. Surflex-Dock19 uses an empirical scoring function and a patented search engine to dock ligands into a protein’s binding site. It is particularly successful at eliminating false positive results and can be used to narrow the screening pool while retaining a large number of active compounds.19,35 Thus, Surflex-Dock experiments on Cy-FBA-II were further perD

DOI: 10.1021/acs.jcim.5b00618 J. Chem. Inf. Model. XXXX, XXX, XXX−XXX

Article

Journal of Chemical Information and Modeling Scheme 1. General Synthetic Route for Compounds 1−26

NO2, or OH (compounds 2−7). In comparison, compound 4 exhibited a higher inhibitory activity against Cy-FBA-II (IC50 = 1.5 μM) than the other compounds. This result suggests that Br at the R2 position is favorable for Cy-FBA-II activity. At the R3 position, H, CF3, CH3, halogen (Br or F), NO2, and OH were introduced, and the IC50 values show that compound 10 with the Br substituent at the R3 position exhibits the highest Cy-FBA-II activity. Thus, it is suggested that Br at the R3 position is also favorable. Actually, we can notice that the effects of the R2 and R3 substituents on the CyFBA-II activities of the hit compounds are slight. As can be seen in Table 1, compounds 1−14 exhibit similar inhibitory activities against Cy-FBA-II (1.5−8.9 μM). Taken together, the effect of substituents R1, R2, and R3 on the phenyl ring on the inhibitory activities is not obvious. Nevertheless, when the R5 and R6 substituents were changed to non-hydrogen atoms (Br, Cl, CH3 etc.), the corresponding CyFBA-II activities decreased remarkably. As can be seen in Table 1, the inhibitory activities of compound 15 (IC50 = 13.2 μM), 16 (IC50 = 3.0 μM), and 17 (IC50 = 10.7 μM), in which the R5 position was changed to Br, are about 2−4 fold lower than those of compounds 2 (IC50 = 3.2 μM), 10 (IC50 = 1.7 μM), and 8 (IC50 = 3.8 μM), respectively. These results indicated that a Br substituent at the R5 position is unfavorable for the inhibitory activities of the compounds. A similar effect of the substituent also could be noticed for compounds 18−20. As can be seen from Table 1, the introduction of two Cl atoms at the R5 and R6 positions led to about 7.5−14.7-fold decreases in the IC50 values of compounds 18 (IC50 = 24 μM), 19 (IC50 = 25 μM), and 20 (IC50 = 30 μM) compared with compounds 2 (IC50 = 3.2 μM), 10 (IC50 = 1.7 μM), and 8 (IC50 = 3.8 μM), respectively. These results indicate that halogen (Cl or Br) at the R5 and R6 positions is unfavorable. To identify the proposed binding model of the synthesized compounds targeted into Cy-FBA-II, the representative compound 10 was docked into the active site of Cy-FBA-II using the Surflex-Dock module in the Sybyl-X1.3 software. After the docking procedure, 100 poses with different binding conformations were obtained. Then the poses with similar conformations (RMSD < 0.8 Å) were aggregated into clusters, and we selected one respective pose in each cluster for further binding-energy calculations using the three-layer ONIOM (ONIOM3) method in the Gaussian 09 software package.37 In the ONIOM3 calculations, compound 10 and the Zn(II) ion were set as the high layer with a sphere model, which was calculated at the ωb97xd/6-31G(d) theoretical level. The important residues within 10 Å depth from any given atom of compound 10 were selected as the medium layer (M), which was calculated using a semiempirical method (PM6). The low layer (L) consisted of the entire enzyme system and was calculated by the molecular mechanics (MM) method using the AMBER force field. Finally, the pose with lowest binding energy was selected as the starting-point conformation, and MD simulations were further performed using the AMBER 12

conformation of FBA5 and Cy-FBA-II is illustrated in Figure 2. As can be seen from Figure 2C, one of the carbonyl groups of FBA5 can also form a coordination bond with the Zn(II) ion. On the other hand, the hydroxyl group on the benzene ring of compound FBA5 can coordinate with the Zn(II) ion. These results suggest that the carbonyl groups and the hydroxyl group on the benzene ring are important for the binding of FBA5 into Cy-FBA-II. However, previous studies36 have demonstrated that FBA5 can exist in solution as a mixture of various tautomeric forms. To increase the stability and remain the bioactivity of the hit compound, we attempted to reoptimize the structure of FBA5. As illustrated in Figure 2, for the left region of FBA5 (highlighted in blue), the acetylacetone moiety (Figure 2A) was changed to a pyrrole-2′,5′-dione ring (Figure 2B). This change can retain the coordination of the carbonyl group to Zn(II). For the middle region of FBA5 (highlighted in green), we changed the nitrile group (Figure 2A) to an amide group (Figure 2B), giving compound 1. Compared with FBA5, compound 1 could retain the coordination with Zn(II) and exhibit more reliability. Fortunately, the Cy-FBA-II inhibitory activity of compound 1 (8.9 μM) is increased about 2-fold compared with that of compound FBA5 (17.8 μM), as listed in Table 1. Thus, on the basis of the skeleton structure of compound 1, a series of novel maleimide derivatives were synthesized and optimized to obtain more potent inhibitors against Cy-FBA-II. Chemistry. The synthetic route to the title compounds is illustrated in Scheme 1, and their substituents are listed in Table 1. The structures of the synthesized compounds were characterized by 1H and 13C NMR spectroscopy and HRMS. The reactions of substituted benzohydrazides and maleic anhydride were finished quickly under reflux conditions in less than 4 h without any catalyst. All of the final products were obtained in high yields (>60%) by column chromatography purification. When hydroxyl or fluoro groups were substituted on the phenyl ring (e.g., compounds 1, 5, 21, and 25), the yield decreased slightly. SAR Analysis and Optimization of Hit Compounds. To evaluate the inhibitory activities of the hit compounds, the IC50 values of these compounds against Cy-FBA-II were determined in the present study. As listed in Table 1, compounds in which R5 and R6 are hydrogen atoms (e.g., compounds 1−14) always exhibit high inhibitory activities against Cy-FBA-II (IC50 = 1.5− 8.9 μM). A comparison of compounds 1 and 2 shows that the Cy-FBA-II activity of 2 (IC50 = 3.8 μM) is increased about 3fold compared with compound 1 (IC50 = 8.9 μM). Indeed, it is possible that the hydroxyl group as the R1 substituent could form an intramolecular hydrogen bond with the surrounding carbonyl group, which could result in a decrease in the solubility of the corresponding compound. Thus, the hydrogen atom at the R1 position is comparatively favorable. To examine the effect of the R2 substituent on the inhibitory activity, we also fixed R1, R3, R4, R5, and R6 as hydrogen atoms and varied the R2 substituent as H, CH3, halogen (Br or F), E

DOI: 10.1021/acs.jcim.5b00618 J. Chem. Inf. Model. XXXX, XXX, XXX−XXX

Article

Journal of Chemical Information and Modeling

Figure 3. Root-mean-square deviation (RMSD) (in Å) for all of the atoms of Cy-FBA-II in complex with compound 10 as a function of the MD simulation time.

explain our experimental finding that the compounds with hydrogen atoms at the R5 and R6 positions exhibit higher inhibitory potencies against Cy-FBA-II while compounds with halogen (Cl or Br) at these positions have lower inhibitory activities. Similarly, the introduction of CH3 or C6H3-o-F on the pyrrole-2′,5′-dione ring resulted in a significant decrease of the inhibitory activity (IC50 > 300 μM for compounds 23−26). The good agreement between the theoretical and experimental results suggests that our present binding model of the hit compounds with Cy-FBA-II is reasonable. To test the selectivity of the hit compounds, the inhibitory activity of compound 10 against mammalian FBA-I (isozyme A from rabbit muscle) was also tested in the present study; the IC50 curve of compound 10 against FBA-I is shown in Figure S2. The results show that the IC50 value of compound 10 against rabbit muscle FBA-I (Ra-FBA-I) is 54 μM. As expected, compound 10 with an IC50 value of 1.7 μM against Cy-FBA-II showed a selectivity of up to 30. CoMFA Analysis. The PLS analysis results for the CoMFA model are summarized in Table 2. A predictive CoMFA model

program.20 The plot of the evolution of the root-mean-square deviation (RMSD) with simulation time is shown in Figure 3. The conformation of compound 10 targeted into Cy-FBA-II with lowest kinetic energy was extracted from the simulation trajectory. The binding mode of the complex obtained by MD simulations is illustrated in Figure 4. As can be seen in Figure 4,

Table 2. Statistical Parameters of the CoMFA Model contribution (%)

Figure 4. Proposed binding mode of compound 10 into the active site of Cy-FBA-II after MD simulation. Inset: distances between the R5 and R6 substituents of the pyrrole-2′,5′-dione ring and the backbone of His232.

2

q

r

2

S

F

steric

electrostatic

0.81

0.991

0.104

291.161

53.7

46.3

with a leave-one-out cross-validated coefficient of (q2) of 0.81 and a correlation coefficient (r2) of 0.991 was built (a satisfactory QSAR model has q2 > 0.5 and r2 > 0.8). As shown in Figure 5, the predicted activity values are in good agreement with the experimental data. The standard error (S = 0.104) and F-test value (F = 291.161) further corroborate the predicted model. In the QSAR model, the contributions of the steric and electrostatic fields are 53.7% and 46.3%, respectively. In Figure 6, the CoMFA contour maps are used to represent the steric and electrostatic fields. In the steric field map, the green contour surrounding the benzene ring suggests that more bulky substituents in these positions would be favorable for higher activity, while the yellow contour surrounding the pyrrole ring indicates the region of unfavorable steric effects. These results are consistent with our binding mode as proposed above. In the CoMFA electrostatic field, the blue region indicates that negative charge may play a favorable role in the inhibitory activity, whereas positive charge around the carbonyl group on the pyrrole ring (red region) is favorable. Furthermore, a CoMSIA analysis was also performed to further confirm our binding mode. As illustrated in Table S2 and Figures S3 and S4, the CoMSIA results are similar to those of CoMFA. Synechocystis Activity. The inhibition activities (EC50) of most of the hit compounds against Synechocystis sp. PCC 6803

no remarkable hydrogen bond from the phenyl ring to surrounding residues can be noticed, which explains to some extent why the substituents R1, R2, and R3 of the phenyl ring can exhibit only a subtle effect on the inhibitory activity against Cy-FBA-II. In the middle region of 10, the carbonyl moiety can form a hydrogen bond with the backbone of residue Gly199. The NH moiety of 10 is involved in a hydrogen bond with residue Asn24. However, one of carbonyl groups on the pyrrole-2′,5′-dione ring of compound 10 can coordinate to the Zn(II) ion a distance of 1.9 Å. The other carbonyl group on the pyrrole-2′,5′-dione ring can form two hydrogen bonds with residues Asp277 and Thr278. As documented previously,33,38 the Zn(II) ion in the active site is essential for the catalysis of FBA-II. Thus, His232 is important to fix the position of Zn(II). On the other hand, this suggests that the coordination between the hit compound and Zn(II) is necessary. However, it should be noticed from Figure 4 that the R5 and R6 substituents of the pyrrole-2′,5′-dione ring actually are close to the backbone of residue His232 (∼2.1 Å). This means that bulky groups at the R5 and R6 positions could result in clashes between the R5 and/ or R6 group on the pyrrole-2′,5′-dione ring and His232 of CyFBA-II. Thus, bulky groups at the R5 and R6 positions are unfavorable for the inhibitory activities of hit compounds against Cy-FBA-II. This theoretical result can qualitatively F

DOI: 10.1021/acs.jcim.5b00618 J. Chem. Inf. Model. XXXX, XXX, XXX−XXX

Article

Journal of Chemical Information and Modeling

Figure 7. Inhibition curve (inhibition rate vs concentration) of compound 10, which was fitted by nonlinear regression using logistic equation in the Origin 7.7 software.

Figure 5. Plot of predicted vs experimental values for the training and test sets based on the CoMFA model.

significantly decreased, with an EC50 value of 11.5 ppm. This result demonstrated to some extent that Cy-FBA-II is the target of compound 10. Although compound 10 was only targeted into Cy-FBA-II, it exhibits similar algicide activity against Synechocystis sp. PCC 6803 compared with our previous dualtarget compound L20c (IC50 = 2.0 μM).10 On the other hand, the Cy-FBA-II inhibitory activities of compounds 18−22 are weak, and thus, the EC50 values for these compounds are corresponding larger than 10 ppm. The Cy-FBA-II inhibitory activities of compounds 23−26 are significantly weaker, and thus, their algicide activities were not determined in the present study. It should be noticed from Table 1 that compounds 6 (IC50 = 2.3 μM) and 16 (IC50 = 3.0 μM) exhibit higher CyFBA-II inhibitory activities but have moderate inhibitory activities against Synechocystis sp. PCC 6803 (EC50 = 12−18 ppm). Thus, it is hard to make a direct correlation between the Cy-FBA-II and algicide activities from the currently available experimental data because the absorption, distribution, and metabolism performance of individual compounds obtained in the present study may differ.

Figure 6. Steric and electrostatic maps of the CoMFA model. 10 is shown inside the field. In the steric field contour plot, sterically favored areas are represented by green polyhedra, while sterically disfavored areas are represented by yellow polyhedra. In the electrostatic field contour plot, positive-charge-favored areas are represented by red polyhedra, whereas negative-charge-favored areas are represented by blue polyhedra.



CONCLUSIONS A series of potentially novel hit compounds interacting with Cy-FBA-II were designed, synthesized, and optimized, and their inhibitory activities against Cy-FBA-II and Synechocystis sp. PCC 6803 were examined. The enzymatic results suggest that the substituents on the pyrrole-2′,5′-dione ring of the hit compounds can significantly influence the Cy-FBA-II inhibition activity. With hydrogen atoms at the R5 and R6 positions, the corresponding compounds exhibit higher Cy-FBA-II inhibitory activities, with IC50 values of 1.5−8.9 μM. In contrast, the introduction of a bigger group (Br, Cl, CH3, or C6H3-ortho-F) on the pyrrole-2′,5′-dione ring significantly decreased the CyFBA-II inhibitory activity. The possible reason for this and the binding mode of the hit compounds and Cy-FBA-II have been analyzed by the joint use of molecular docking, ONIOM calculations, MD simulations, and 3D-QSAR strategies. The results suggest that this is mainly due to steric clashes between the R5 and/or R6 group on the pyrrole-2′,5′-dione ring and His232 of Cy-FBA-II. It should be noticed that most of the hit

were also determined, as summarized in Table 1. The inhibition curve (plot of the inhibition rate vs the concentration) for representative compound 10 is illustrated in Figure 7. Generally, most of the compounds with higher Cy-FBA-II inhibition exhibit higher Synechocystis activities. For example, compounds 2, 3−5, and 7−13 have higher Cy-FBA-II inhibitory activities (IC50 = 1.5−5.0 μM) and also exhibit higher algal inhibition activities against Synechocystis sp. PCC 6803 (EC50 = 0.6−9.3 ppm). Especially, compound 10 exhibits greatest potential algicide activity (EC50 = 0.6 ppm). To further verify that the inhibition activities of the synthesized compounds against Synechocystis sp. PCC 6803 are achieved by inhibition of Cy-FBA-II, the representative compound 10 was also evaluated for inhibition activity against mutant Synechocystis sp. PCC 6803 whose Cy-FBA-II was overexpressed (for more details, see the Supporting Information). As a result of the increased amoutn of Cy-FBA-II in Synechocystis sp. PCC 6803, the inhibition activity of compound 10 was G

DOI: 10.1021/acs.jcim.5b00618 J. Chem. Inf. Model. XXXX, XXX, XXX−XXX

Journal of Chemical Information and Modeling



compounds with high Cy-FBA-II inhibitory activities could also exhibit high algicide activities. Among all of the hit compounds, compound 10 exhibited not only the highest in vitro activity against Cy-FBA-II (IC50 = 1.7 μM) but also the highest algicide activity against Synechocystis sp. PCC 6803 (EC50 = 0.6 ppm). To test the selectivity of the hit compounds, the inhibitory activity of compound 10 against mammalian FBA-I was also tested in the present study. The results indicate that compound 10 shows an IC50 value of 54 μM against Ra-FBA-I, corresponding to a high selectivity of up to 30. The positive results provide new insight into the binding mode of the inhibitors and Cy-FBA-II. The enzymatic and algal inhibition assays suggest that Cy-FBA-II is very likely to be a promising target for the design, synthesis, and development of novel specific algicides to solve CHABs.



REFERENCES

(1) Carmichael, W. W. Health Effects of Toxin-Producing Cyanobacteria:″The CyanoHABs″. Hum. Ecol. Risk Assess. 2001, 7, 1393−1407. (2) Cheung, M. Y.; Liang, S.; Lee, J. Toxin-Producing Cyanobacteria in Freshwater: A Review of The Problems, Impact on Drinking Water Safety, and Efforts for Protecting Public Health. J. Microbiol. 2013, 51, 1−10. (3) Bryant, D. A.; Frigaard, N. U. Prokaryotic Photosynthesis and Phototrophy Illuminated. Trends Microbiol. 2006, 14, 488−496. (4) Gefflaut, T.; Blonski, C.; Perie, J.; Willson, M. l. Class I Aldolases: Substrate Specificity, Mechanism, Inhibitors and Structural Aspects. Prog. Biophys. Mol. Biol. 1995, 63, 301−340. (5) Haake, V.; Zrenner, R.; Sonnewald, U.; Stitt, M. A Moderate Decrease of Plastid Aldolase Activity Inhibits Photosynthesis, Alters The Levels of Sugars and Starch, and Inhibits Growth of Potato Plants. Plant J. 1998, 14, 147−157. (6) Nakahara, K.; Yamamoto, H.; Miyake, C.; Yokota, A. Purification and Characterization of Class-I and Class-II Fructose-1,6-bisphosphate Aldolases from The Cyanobacterium Synechocystis sp. PCC 6803. Plant Cell Physiol. 2003, 44, 326−333. (7) Daher, R.; Coinçon, M.; Fonvielle, M.; Gest, P. M.; Guerin, M. E.; Jackson, M.; Sygusch, J.; Therisod, M. Rational Design, Synthesis, and Evaluation of New Selective Inhibitors of Microbial Class II (Zinc Dependent) Fructose Bis-phosphate Aldolases. J. Med. Chem. 2010, 53, 7836−7842. (8) Lebherz, H. G.; Rutter, W. J. Distribution of Fructose Diphosphate Aldolase Variants in Biological Systems. Biochemistry 1969, 8, 109−121. (9) Li, Z.; Liu, Z.; Cho, D. W.; Zou, J.; Gong, M.; Breece, R. M.; Galkin, A.; Li, L.; Zhao, H.; Maestas, G. D.; Tierney, D. L.; Herzberg, O.; Dunaway-Mariano, D.; Mariano, P. S. Rational Design, Synthesis and Evaluation of First Generation Inhibitors of The Giardia lamblia Fructose-1,6-biphosphate Aldolase. J. Inorg. Biochem. 2011, 105, 509− 517. (10) Li, D.; Han, X.; Tu, Q.; Feng, L.; Wu, D.; Sun, Y.; Chen, H.; Li, Y.; Ren, Y.; Wan, J. Structure-Based Design and Synthesis of Novel Dual-Target Inhibitors against Cyanobacterial Fructose-1,6-Bisphosphate Aldolase and Fructose-1,6-Bisphosphatase. J. Agric. Food Chem. 2013, 61, 7453−7461. (11) Kaneko, T.; Sato, S.; Kotani, H.; Tanaka, A.; Asamizu, E.; Nakamura, Y.; Miyajima, N.; Hirosawa, M.; Sugiura, M.; Sasamoto, S.; Kimura, T.; Hosouchi, T.; Matsuno, A.; Muraki, A.; Nakazaki, N.; Naruo, K.; Okumura, S.; Shimpo, S.; Takeuchi, C.; Wada, T.; Watanabe, A.; Yamada, M.; Yasuda, M.; Tabata, S. Sequence Analysis of the Genome of the Unicellular Cyanobacterium Synechocystis sp. Strain PCC6803. II. Sequence Determination of the Entire Genome and Assignment of Potential Protein-coding Regions. DNA Res. 1996, 3, 109−136. (12) Gunosewoyo, H.; Midzak, A.; Gaisina, I. N.; Sabath, E. V.; Fedolak, A.; Hanania, T.; Brunner, D.; Papadopoulos, V.; Kozikowski, A. P. Characterization of Maleimide-Based Glycogen Synthase Kinase3 (GSK-3) Inhibitors as Stimulators of Steroidogenesis. J. Med. Chem. 2013, 56, 5115−5129. (13) Matuszak, N.; Muccioli, G. G.; Labar, G.; Lambert, D. M. Synthesis and in Vitro Evaluation of N-Substituted Maleimide Derivatives as Selective Monoglyceride Lipase Inhibitors. J. Med. Chem. 2009, 52, 7410−7420. (14) Kalgutkar, A. S.; Crews, B. C.; Marnett, L. J. Design, Synthesis, and Biochemical Evaluation of N-Substituted Maleimides as Inhibitors of Prostaglandin Endoperoxide Synthases. J. Med. Chem. 1996, 39, 1692−1703. (15) Whalen, K. E.; Poulson-Ellestad, K. L.; Deering, R. W.; Rowley, D. C.; Mincer, T. J. Enhancement of Antibiotic Activity against Multidrug-Resistant Bacteria by The Efflux Pump Inhibitor 3,4Dibromopyrrole-2,5-dione Isolated from a Pseudoalteromonas sp. J. Nat. Prod. 2015, 78, 402−412. (16) Jensen, L. H.; Renodon-Corniere, A.; Wessel, I.; Langer, S. W.; Søkilde, B.; Carstensen, E. V.; Sehested, M.; Jensen, P. B. Maleimide Is

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jcim.5b00618. 1 H and 13C NMR spectra of the hit compounds and construction of the Cy-FBA-II overexpression strain of Synechocystis sp. PCC 6803 (PDF)



Article

AUTHOR INFORMATION

Corresponding Authors

*Tel/Fax: (+86)27-67862022. E-mail: [email protected] (Y.R.). *Tel/Fax: (+86)27-67862022. E-mail: [email protected]. cn (J.W.). Author Contributions §

X.H., X.Z., and S.Z. contributed equally to this study.

Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS This work was supported by the National Basic Research Program of China (973 Program, 2010CB126100), the National Natural Science Foundation of China (21572077, 21472061, 21373094, 21202056, 21272089 and 21172089), PCSIRT (IRT0953), the Program for Academic Leader in Wuhan Municipality (201150530150), and the Self-Determined Research Funds of CCNU from the College’s Basic Research and Operation of the Ministry of Education (CCNU14A05006).



ABBREVIATIONS USED CHABs, cyanobacterial harmful algal blooms; FBA, fructose1,6-bisphosphate aldolase; FBP, fructose-1,6-biphosphate; DHAP, dihydroxyacetone phosphate; GAP, glyceraldehyde 3phosphate; Cy-FBA-II, cyanobacterial class-II fructose-1,6bisphosphate aldolase; CoMFA, comparative molecular field analysis; SAR, structure−activity relationship; TIM, triosephosphate isomerase; GPDH, glycerol 3-phosphate dehydrogenase; IC50, half-maximal inhibitory concentration; EC50, half-maximal effective concentration; 3D-QSAR, three-dimensional quantitative structure−activity relationship; ONIOM, our own Nlayered integrated molecular orbital and molecular mechanics; MD, molecular dynamics; CoMSIA, comparative molecular similarity indices analysis H

DOI: 10.1021/acs.jcim.5b00618 J. Chem. Inf. Model. XXXX, XXX, XXX−XXX

Article

Journal of Chemical Information and Modeling a Potent Inhibitor of Topoisomerase II in vitro and in vivo: A New Mode of Catalytic Inhibition. Mol. Pharmacol. 2002, 61, 1235−1243. (17) Cornell, W. D.; Cieplak, P.; Bayly, C. I.; Gould, I. R.; Merz, K. M.; Ferguson, D. M.; Spellmeyer, D. C.; Fox, T.; Caldwell, J. W.; Kollman, P. A. A Second Generation Force Field for The Simulation of Proteins, Nucleic Acids, and Organic Molecules. J. Am. Chem. Soc. 1995, 117, 5179−5197. (18) Wang, D.; Zhu, X.; Cui, C.; Dong, M.; Jiang, H.; Li, Z.; Liu, Z.; Zhu, W.; Wang, J. G. Discovery of Novel Acetohydroxyacid Synthase Inhibitors as Active Agents against Mycobacterium tuberculosis by Virtual Screening and Bioassay. J. Chem. Inf. Model. 2013, 53, 343− 353. (19) Jain, A. Surflex-Dock 2.1: Robust Performance from Ligand Energetic Modeling, Ring Flexibility, and Knowledge-based Search. J. Comput.-Aided Mol. Des. 2007, 21, 281−306. (20) Case, D. A.; Darden, T. A.; Cheatham, T. E.; Simmerling, C. L.; Wang, J.; Duke, R. E.; Luo, R.; Walker, R. C.; Zhang, W.; Merz, K. M.; Roberts, B.; Hayik, S.; Roitberg, A.; Seabra, G.; Swails, J.; Götz, A. W.; Kolossváry, I.; Wong, K. F.; Paesani, F.; Vanicek, J.; Wolf, R. M.; Liu, J.; Wu, X.; Brozell, S. R.; Steinbrecher, T.; Gohlke, H.; Cai, Q.; Ye, X.; Wang, J.; Hsieh, M. J.; Cui, G.; Roe, D. R.; Mathews, D. H.; Seetin, M. G.; Salomon-Ferrer, R.; Sagui, C.; Babin, V.; Luchko, T.; Gusarov, S.; Kovalenko, A.; Kollman, P. A. AMBER 12; University of California: San Francisco, 2012. (21) Wang, J. M.; Wang, W.; Kollman, P. A. Antechamber: An Accessory Software Package for Molecular Mechanical Calculations. Abstr. Pap.Am. Chem. Soc. 2001, 222, U403. (22) Jorgensen, W. L.; Chandrasekhar, J.; Madura, J. D.; Impey, R. W.; Klein, M. L. Comparison of Simple Potential Functions for Simulating Liquid Water. J. Chem. Phys. 1983, 79, 926−935. (23) Al-Suwaidan, I. A.; Alanazi, A. M.; El-Azab, A. S.; Al-Obaid, A. M.; ElTahir, K. E. H.; Maarouf, A. R.; Abu El-Enin, M. A.; Abdel-Aziz, A. A. M. Molecular Design, Synthesis and Biological Evaluation of Cyclic Imides Bearing Benzenesulfonamide Fragment as Potential COX-2 Inhibitors. Bioorg. Med. Chem. Lett. 2013, 23, 2601−2605. (24) Stanier, R. Y.; Kunisawa, R.; Mandel, M.; Cohen-Bazire, G. Purification and Properties of Unicellular Blue-Green Algae (Order Chroococcales). Bacteriol. Rev. 1971, 35, 171−205. (25) Nilsson, J. Multiway Calibration in 3D QSAR: Applications to Dopamine Receptor Ligands. Ph. D. Thesis, University of Groningen, Groningen, Germany, 1998. (26) Wold, S.; Ruhe, A.; Wold, H.; Dunn, I. W., III The Collinearity Problem in Linear Regression. The Partial Least Squares (PLS) Approach to Generalized Inverses. SIAM J. Sci. Stat. Comput. 1984, 5, 735−743. (27) Bush, B.; Nachbar, R., Jr. Sample-distance Partial Least Squares: PLS Optimized for Many Variables, with Application to CoMFA. J. Comput.-Aided Mol. Des. 1993, 7, 587−619. (28) Lipinski, C. A.; Lombardo, F.; Dominy, B. W.; Feeney, P. J. Experimental and Computational Approaches to Estimate Solubility and Permeability in Drug Discovery and Development Settings. Adv. Drug Delivery Rev. 2012, 64, 4−17. (29) Sybyl 7.0; Tripos Inc.: St. Louis, MO, 2003; http://www.certara. com. (30) Pegan, S. D.; Rukseree, K.; Franzblau, S. G.; Mesecar, A. D. Structural Basis for Catalysis of a Tetrameric Class IIa Fructose 1,6Bisphosphate Aldolase from Mycobacterium tuberculosis. J. Mol. Biol. 2009, 386, 1038−1053. (31) Hall, D. R.; Leonard, G. A.; Reed, C. D.; Watt, C. I.; Berry, A.; Hunter, W. N. The Crystal Structure of Escherichia Coli Class II Fructose-1,6-bisphosphate Aldolase in Complex with Phosphoglycolohydroxamate Reveals Details of Mechanism and Specificity. J. Mol. Biol. 1999, 287, 383−394. (32) de la Paz Santangelo, M.; Gest, P. M.; Guerin, M. E.; Coincon, M.; Pham, H.; Ryan, G.; Puckett, S. E.; Spencer, J. S.; GonzalezJuarrero, M.; Daher, R.; Lenaerts, A. J.; Schnappinger, D.; Therisod, M.; Ehrt, S.; Sygusch, J.; Jackson, M. Glycolytic and Non-glycolytic Functions of Mycobacterium tuberculosis Fructose-1,6-bisphosphate

Aldolase, an Essential Enzyme Produced by Replicating and Nonreplicating Bacilli. J. Biol. Chem. 2011, 286, 40219−40231. (33) Daher, R.; Coincon, M.; Fonvielle, M.; Gest, P. M.; Guerin, M. E.; Jackson, M.; Sygusch, J.; Therisod, M. Rational Design, Synthesis, and Evaluation of New Selective Inhibitors of Microbial Class II (zinc dependent) Fructose Bis-phosphate Aldolases. J. Med. Chem. 2010, 53, 7836−7842. (34) Hindle, S.; Rarey, M.; Buning, C.; Lengauer, T. Flexible Docking Under Pharmacophore Type Constraints. J. Comput.-Aided Mol. Des. 2002, 16, 129−149. (35) Jain, A. N. Surflex: Fully Automatic Flexible Molecular Docking Using a Molecular Similarity-Based Search Engine. J. Med. Chem. 2003, 46, 499−511. (36) Mahmudov, K. T.; Rahimov, R. A.; Babanly, M. B.; Hasanov, P. Q.; Pashaev, F. G.; Gasanov, A. G.; Kopylovich, M. N.; Pombeiro, A. J. L. Tautomery and Acid−base Properties of Some Azoderivatives of Benzoylacetone. J. Mol. Liq. 2011, 162, 84−88. (37) Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Mennucci, B.; Petersson, G. A.; Nakatsuji, H.; Caricato, M.; Li, X.; Hratchian, H. P.; Izmaylov, A. F.; Bloino, J.; Zheng, G.; Sonnenberg, J. L.; Hada, M.; Ehara, M.; Toyota, K.; Fukuda, R.; Hasegawa, J.; Ishida, M.; Nakajima, T.; Honda, Y.; Kitao, O.; Nakai, H.; Vreven, T.; Montgomery, J. A., Jr.; Peralta, J. E.; Ogliaro, F.; Bearpark, M.; Heyd, J. J.; Brothers, E.; Kudin, K. N.; Staroverov, V. N.; Kobayashi, R.; Normand, J.; Raghavachari, K.; Rendell, A.; Burant, J. C.; Iyengar, S. S.; Tomasi, J.; Cossi, M.; Rega, N.; Millam, J. M.; Klene, M.; Knox, J. E.; Cross, J. B.; Bakken, V.; Adamo, C.; Jaramillo, J.; Gomperts, R.; Stratmann, R. E.; Yazyev, O.; Austin, A. J.; Cammi, R.; Pomelli, C.; Ochterski, J. W.; Martin, R. L.; Morokuma, K.; Zakrzewski, V. G.; Voth, G. A.; Salvador, P.; Dannenberg, J. J.; Dapprich, S.; Daniels, A. D.; Farkas, Ö .; Foresman, J. B.; Ortiz, J. V.; Cioslowski, J.; Fox, D. J. Gaussian 09, revision D.01; Gaussian, Inc.: Wallingford, CT, 2013. (38) Daher, R.; Therisod, M. Highly Selective Inhibitors of Class II Microbial Fructose Bis-phosphate Aldolases. ACS Med. Chem. Lett. 2010, 1, 101−104.

I

DOI: 10.1021/acs.jcim.5b00618 J. Chem. Inf. Model. XXXX, XXX, XXX−XXX