Modeling of cyclooxygenase-2 and 5-lipooxygenase inhibitory activity of apoptosis-inducing agents potentially useful in prostate cancer chemotherapy: Derivatives of diarylpyrazole

Figures & data

Table I.  Structures and observed and modeled COX-2 and 5-LOX inhibitory activity of diarylpyrazole derivatives.

				pIC50(M)
				COX-2			5-LOX
S. No.	R1	R2	R3	Obsd.^*	Calcd. Equation (3)	Pred. LOO	Obsd.^*	Calcd. Equation (4)	Pred. LOO
1	4-CH3SO2	H		7.35	7.19	7.11	6.52	6.52	6.56
2	H	H		6.21	5.98	5.94	6.24	6.21	6.20
3	4-F	H		6.02	6.11	6.12	6.32	6.20	6.16
4	4-Cl	H		6.03	6.11	6.12	6.08	6.16	6.18
5	4-CH3	H		6.03	6.11	6.12	6.14	6.12	6.12
6	4-CH3O	H		6.52	6.30	6.28	6.11	6.07	6.06
7	3-CF3O	H		6.09	6.36	6.40	6.07	6.12	6.12
8	4-NH2SO2	H		7.00	7.19	7.27	6.13	6.20	6.22
9	4,5-diCH3	H		6.39	6.23	6.19	6.12	6.10	6.07
10	4,5-diCl	H		6.15	6.23	6.25	6.10	6.12	6.12
11	4-CH3SO2	H		6.51	6.57	6.59	–^*	–	–
12	4-CH3SO2	H		6.13	6.22	6.23	–^*	–	–
13	4-CH3SO2	H		6.24	6.41	6.48	–^*	–	–
14	4-CH3SO2	H		6.04	6.08	6.08	–^*	–	–
15	4-CH3SO2	H		6.66	6.54	6.50	–^*	–	–
16	4-CH3SO2	H		6.05	5.91	5.87	–^*	–	–
17	4-CH3SO2	H		6.35	6.21	6.19	–^*	–	–
18	4-CH3SO2	H		6.06	6.09	6.09	–^*	–	–
19	4-CH3SO2	H		6.15	6.28	6.30	–^*	–	–
20^†	4-NH2SO2	CH3	CF3	7.44	7.32	7.14	–^*	–	–

^* Taken from reference [23]

^† Celecoxib.

Table II.  Descriptor classes used and identified categories for the analysis of COX-2 inhibitory activity of diarylpyrazole derivatives.

Descriptor class (acronyms)^*	Definition and scope	Descriptors' category^†
Constitutional (CONST)	Dimensionless or 0D descriptors; independent from molecular connectivity and conformations	III
Topological (TOPO)	2D-descriptor from molecular graphs andindependent conformations	I
Molecular walk counts (MWC)	2D-descriptors representing self-returning walks counts of different lengths	IV
Modified Burden eigenvalues (BCUT)	2D-descriptors representing positive and negative eigenvalues of the adjacency matrix, weights the diagonal elements and atoms	II
Galvez topological charge indices (GVZ)	2D-descriptors representing the first 10 eigenvalues of corrected adjacency matrix	II
2D-autocorrelations (2DAUTO)	Molecular descriptors calculated from the molecular graphs by summing the products of atom weights of the terminal atoms of all the paths of the considered path length (the lag)	III
Functional groups (FUN)	Molecular descriptors based on the counting of the chemical functional groups	IV
Atom centered fragments (ACF)	Molecular descriptors based on the counting of 120 atom centered fragments, as defined by Ghose-Crippen	IV
Empirical (EMP)	1D-descriptors represent the counts of nonsingle bonds, hydrophilic groups and ratio of the number of aromatic bonds and total bonds in an H-depleted molecule	III
Properties (PROP)	1D-descriptors representing molecular properties of a molecule	IV

^* Reference [30]

^† Descriptor categories identified at the end of second stage; in this the filter values are as follows: filter-1 as 0.3, filter-2 as 2.0, filter-3 as 0.71, and filter-4 as 0.3 ≤ Q² ≤ 1.0, the number of compounds in each dataset is 20.

Table III.  Cross-correlation matrix^* amongst identified descriptors of the models.

Equation (2)				Equation (3)				Equation (4)
	VEA1	T(O..O)	T(S..F)		T(O..O)	T(S..F)	GGI2		BELe7	MATS2v
VEA1	1.000	0.225	0.248	T(O..O)	1.000	0.136	0.261	BELe7	1.000	0.153
T(O..O)		1.000	0.136	T(S..F)		1.000	0.130	MATS2V		1.000
T(S..F)			1.000	GGI2			1.000

^* Matrix elements are the r-values.

Figure 1.  Plot of observed versus calculated [Equation (3)] and predicted (LOO) pIC₅₀(COX-2) values.

Table IV.  Observed and calculated inhibitory activities of compounds with training and test sets statistics.

S. No.	COX-2 Inhibition				5-LOX inhibition
	Obsd.^*	Calcd.^†	Calcd.^‡	Calcd.^¶	Obsd.^*	Calcd.^†	Calcd.^‡	Calcd.^¶
1	7.35	7.11^§	7.17^§	7.11^§	6.52	6.52	6.52	6.52
2	6.21	5.92^§	5.99^§	6.00	6.24	6.20^§	6.20^§	6.20^§
3	6.02	6.01	6.12	6.10	6.32	6.20	6.19	6.19
4	6.03	6.01	6.12^§	6.10	6.08	6.16	6.16	6.15
5	6.03	6.01	6.12	6.10^§	6.14	6.13	6.12	6.12^§
6	6.52	6.21^§	6.31	6.28	6.11	6.09	6.08	6.07
7	6.09	6.26	6.38^§	6.33	6.07	6.12^§	6.12	6.11
8	7.00	7.11	7.17	7.11	6.13	6.20	6.20	6.19
9	6.39	6.11^§	6.25	6.20^§	6.12	6.11	6.10	6.10
10	6.15	6.11	6.25	6.20	6.10	6.12	6.12^§	6.11
11	6.51	6.59	6.55^§	6.58	–	–	–	–
12	6.13	6.20	6.22	6.24	–	–	–	–
13	6.24	6.42	6.39	6.44	–	–	–	–
14	6.04	6.06	6.08	6.10^§	–	–	–	–
15	6.66	6.49	6.54	6.52	–	–	–	–
16	6.05	5.92	5.90	5.96	–	–	–	–
17	6.35	6.19	6.21	6.22	–	–	–	–
18	6.06	6.10^§	6.08	6.13	–	–	–	–
19	6.15	6.25	6.29	6.29^§	–	–	–	–
20	7.44	7.27	7.28	7.26	–	–	–	–
Training set r^2		0.919	0.893	0.862		0.824	0.819	0.826
s		0.134	0.151	0.171		0.076	0.078	0.078
F		41.582	30.698	22.810		11.725	11.343	11.858
LOF		0.036	0.047	0.060		0.014	0.015	0.015
FIT		5.198	3.837	2.851		1.954	1.890	1.976
AIC		0.031	0.040	0.051		0.013	0.013	0.013
Q^2LOO		0.756	0.680	0.668		0.527	0.589	0.592
Test set r^2		0.726	0.859	0.902		–^∥	–^∥	–^∥
s		0.123	0.368	0.151		–^∥	–^∥	–^∥
F		21.807	2.556	17.671		–^∥	–^∥	–^∥

^* Taken from Ref. [23]

^† Test set from the cluster analysis of all descriptors used in deriving Equation (3) for COX-2 and Equation (4) for 5-LOX

^‡ Test set from the cluster analysis of the respective activity of the compounds

^¶ Test set from random selection of the compounds. The training models have 15 and 8 compounds each for COX-2 and 5-LOX respectively

^§ Calculated activities of test set compounds

^∥ Values cannot be determined as the number of data-points in test set were two only.

Figure 2.  Plot of observed versus calculated [Equation (4)] and predicted (LOO) pIC₅₀(5-LOX) values.

N Pommery, T Taverne, A Telliez, L Goossens, C Charlier, J Pommery, JF Goossens, R Houssin, F Durant, and JH Henichart. (2004). New COX-2/5-LOX inhibitors: Apoptosis-inducing agents potentially useful in prostate cancer chemotherapy. J Med Chem 47:6195–6206.

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