A 3D-QSAR Study of Celebrex-based PDK1 Inhibitors Using CoMFA Method

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1 Journal of the Chinese Chemical Society, 2009, 56, A 3D-QSAR Study of Celebrex-based PDK1 Inhibitors Using CoMFA Method Wen-Hung Wang a ( ),N.R.Jena a ( ), Yi-Ching Wang b ( ) and Ying-Chieh Sun a *( ) a Department of Chemistry, National Taiwan Normal University, 88, TingChow Road, Section 4, Taipei 116, Taiwan, R.O.C. b Department of Life Science, National Taiwan Normal University, 88, TingChow Road, Section 4, Taipei 116, Taiwan, R.O.C. A 3D-QSAR study of celebrex-based compounds of PDK1 inhibitors using comparative molecular field analysis (CoMFA) was carried out. The structures of the compounds were obtained using quantum chemistry calculation. CoMFA calculations for a number of grouped subsets of compounds gave q 2 values of correlation in the range from 0 to 0.8. The low q 2 values should be mainly due to the narrow span of biological activity. Calculations for several subsets of compounds gave high q 2 values, with Factors affecting the results of the calculations are discussed. Calculated results with high q 2 values suggest that further chemical modifications of the compounds could lead to enhanced activity and could be an aid in the design of celebrex-based cancer drugs. Keywords: 3D-QSAR; CoMFA; Celebrex; PDK1 inhibitor; Cancer. I. INTRODUCTION Celebrex, an anti-inflammatory drug, was recently found to be effective in the prevention of colon cancer for some patients 1 and is currently under extensive preclinical and clinical studies for possible use in the treatment of various types of cancers. 1-5 It was further shown that celebrex inhibits 3-phosphoinositide-dependent kinase 1 (PDK1) activity, a key enzyme in the phosphatidylinositol 3-kinase (PI3K)/akt signaling pathway. 6,7 The PI3K/akt signaling pathway has received increasing attention in cancer drug research recently. 8 This pathway is an important regulator of mammalian cell proliferation and survival. 8 In this pathway, PDK1, a Ser/Tyr protein kinase, activates the akt protein, which in turn signals cellular targets of growth translation and related cellular processes. Several studies have shown that PDK1 is the molecular target of celebrex. 6,7 However, celebrex binds to PDK1 weakly. 6,7 In an attempt to design better PDK1 inhibitors based on the celebrex structure, a series of 36 celebrex-based compounds, as shown in Fig. 1, were synthesized and their IC 50 (inhibition concentration 50) values were reported. 9,10 These 36 compounds are derivatives of celebrex and contain various functional groups at two sites on the molecule (see Fig. 1). The potency of these new inhibitors was increased, compared with celebrex, with IC 50 values down to the M level. To aid in the design of better inhibitors and to further understand the correlation between the inhibition effect and the designed chemicals, a quantitative structure and activity relationship (QSAR) study was carried out. A 3D-QSAR method, the CoMFA, 11 wasusedtoexaminethe QSAR for these compounds. CoMFA is a method which uses a probe atom to probe the fields around compounds of interest and correlate these fields with their biological activities. In practice, a lattice field with a finite grid space is used and the partial least square (PLS) 12 is used to correlate the large number of lattice field data sets to a smaller number of activity data. A number of such QSAR studies have shown success in aiding drug design. 11,13-15 In the present study, we carried out CoFMA calculation to examine the correlation between the biological activity and the structures of these 36 newly synthesized celebrex-based compounds in order to gain a better understanding of which functional groups should be further modified in order to achieve enhanced activity. The method used is briefly described in the next section. The results and discussion are presented in Section III. * Corresponding author. sun@ntnu.edu.tw

2 60 J. Chin. Chem. Soc., Vol. 56, No. 1, 2009 Wang et al. II. METHOD The structures of the compounds were obtained by carrying out quantum chemistry calculation at the PM3 level using the Gaussian 98 program. 16 Compound 35, which has the lowest IC 50 value, was the first compound examined. An energy scan along the two torsional angles of this compound, C22-C21-C8-N7 and C8-N7-C4-C5, shown in Fig. 2, was carried out first, to locate the low energy conformation. The obtained conformation of the lowest energy was then subjected to energy minimization to de- Fig. 1. Celebrex (compound 0) and 36 derivatives thereof, which are divided into two groups. The first group contains compounds 1-24, containing variable Ar-functional groups. The compounds in the second group were designed according to compound 23. 9,10 and the functional group is variable at site R.

3 Structure-Activity Relationship of PDK1 Inhibitors J. Chin. Chem. Soc., Vol. 56, No. 1, Fig. 2. The computed 3D structure of compound 35, which has the lowest IC 50 value, using quantum chemistry PM3 calculation (see text for a detailed description). termine the most stable structure of compound 35, which is shown in Fig. 2. Stable structures of other compounds were obtained by the substitution of functional groups using the structure of compound 35 as a template and then subjected to energy minimization. With these structures in hand, we carried out CoMFA calculation. For alignment, three separate calculations using (1) the benzene ring (2) the pyrazole ring and (3) both of these two rings of celebrex as the overlap site, were carried out. Compound 35 was used as the template for overlapping. Case (3) was found to give the best results and these are presented in section III. The field energy at lattice points around the compounds was calculated using a sp 3 carbon probe atom with a charge of +1. The cutoff energy for this calculation is set to be the default value of 30 kcal/ mol. Mulliken charges obtained from the quantum chemistry PM3 calculations were used as partial charges of the atoms. The van der Waals radii of atoms are those values in the Sybyl 7.1 package. 17 The spacing between lattice points was set to 2 Å. Distance-dependent dielectrics with a dielectric constant of 4.0 were used to mimic the protein environment. In the PLS calculations, leave-one-out was chosen in the cross-validation calculation. The other parameters in the CoMFA calculation were the default values. Since the 36 celebrex-based compounds were designed by varying the functional groups at two sites, we carried out CoMFA calculations for the first group of 24 compounds plus celebrex and the second group of 12 compounds plus celebrex separately first. However, these calculations did not result in high q 2 values that were well correlated. To examine this further, we chose subsets of these 37 compounds and carried out CoMFA calculations. Calculations for several subsets of compounds gave good correlations, with high q 2 values. The calculated results are reported and discussed in the next section. III. RESULTS AND DISCUSSION Calculation of q 2 and IC 50 values The calculations for the first 25 compounds gave a q 2 value of The calculation for the second group of compounds plus celebrex gave a q 2 value of Both calculations gave low q 2 values. To examine this issue further, we chose smaller groups and examined the correla-

4 62 J. Chin. Chem. Soc., Vol. 56, No. 1, 2009 Wang et al. tions based on structural similarity. We chose compounds containing two fused benzene rings or connected by a single bond only at the aromatic (Ar) functional group site (see Fig. 1). This gave compounds 0-6, and 20 in this subgroup. A CoMFA calculation gave a q 2 value of To explore this further and to span the biological data space wider, we included compounds 34 and 35, which have the lowest IC 50 values among all the compounds. In addition, compound 23 was included because this compound has the same functional group as compound 34 and 35 at the R functional group site (Fig. 1). The structures of these compounds overlapped at both the benzene and pyrazole rings, as shown in Fig. 3, and a CoMFA calculation gave a high q 2 value of The high q 2 value is attributed to that, at the R site, the group of flat tricyclic aromatic rings is favored in its orientation, shown in Fig. 3, differing structurally from other R groups of high IC 50 values pointing to different orientations and spanning a large space as shown in Fig. 3. The calculated IC 50 values are listed in Table 1(a), and the correlation figure is shown in Fig. 4. The statistical indexes of the CoMFA calculation are listed in Table 1(b). The calculated electrostatic and steric site map with the structure of compound 35 is shown in Fig. 5, and the color codes are Table 1 (a). Experimental and CoMFA calculated pic 50 values for PDK-1 inhibitors No. IC 50 PDK-1 ( M) pic 50 (obsd) pic 50 (calcd) Residual No. 0 indicates Celebrex Superimposed by pyrazole and benzene ring Table 1 (b). Statistical Indexes of CoMFA Leave-One-Out Conventional q 2 No. of components r 2 s F CoMFA given in the caption. This result suggests that, at the Ar site, the size of the functional group should be reduced significantly. Other modifications of functional groups at Ar and R sites according to the color codes should enhance the activity of these compounds. To explore the correlation further, we added compounds 7-9, and 22 to this subset. A calculation using this expanded subset gave a q 2 value of Another calculation with compound 24 added to the list gave a q 2 value of The calculated electrostatic and steric maps for these two subsets are similar to the subset with a high q 2 value of In addition to these calculations, we chose different subsets in order to examine the correlation of the compounds with their activities. However, no higher q 2 values were obtained. One interesting point is that the inclusion of compound 34 led to a substantial enhancement in the q 2 value. This is likely due to its low IC 50, which spans the biological space of the examined compounds. Fig. 3. The structures of compounds 0-6, 20, 23, 34, 35, which overlapped at both the benzene and pyrazole rings, are shown in Fig. 3. CoMFA calculation for this group of compounds gave the highest q 2 value in the present study. Discussion It is generally believed that alignment (superimposition) is a major factor affecting the calculated q 2 value of correlation in CoFMA calculations. Unfortunately, ligand-

5 Structure-Activity Relationship of PDK1 Inhibitors J. Chin. Chem. Soc., Vol. 56, No. 1, Fig. 4. Correlation between the calculated pic 50 and the experimental pic 50. Fig. 5. Steric and electrostatic site map of a potential drug compound obtained in a QSAR calculation based on data of 11 compounds. The contours of the steric map are shown in yellow and green, and those of the electrostatic map are shown in red and blue. Greater values of Bio-Activity Measurement are correlated with: more bulk near the green region; less bulk near the yellow region; more positive charge near the blue region; and a more negative charge near the red region. protein complex structures of these compounds are not yet available. The structures of the compounds in the present study were obtained using quantum chemistry PM3 calculation only. It should be noted that the alignment procedure is based on the assumption that the compounds have the same binding mode when binding to the protein. Subsets of compounds with high q 2 values should have similar binding modes. The other subsets of compounds with low q 2 values could contain compounds having different binding modes. Future studies of complex structures and the mechanism of inhibition could verify the present computed results. Finally, good correlations between the structures and activities for the two large subsets of compounds (compounds 0-24 and 0, 25-36) were not obtained in this case, with a narrow biological activity span. However, a good correlation was obtained for smaller subsets. The prediction from the results showing good correlation could serve as a good guideline for further modifications of functional groups for celebrex-based compounds and should be of aid in designing new inhibitors with better activity. ACKNOWLEDGEMENTS We thank Profs. Max K. Leong, Jung-Hsin Lin and Jhy-Hou Lin for helpful discussion, and NSC for providing support. NCHC is acknowledged for providing computational resources. Our gratitude also goes to the Academic Paper Editing Clinic, NTNU. Received August 11, 2008.

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