Modeling of the growth hormone secretagogue receptor antagonistic activity using chemometric tools

Figures & data

Table I.  The structures of the 2, 4-diaminopyrimidine analogues included in training set along with their GHS-R binding activity.

S. No.	R1	R2	X	Y	Binding IC50 (nM)^a
1	CH3	H	NHCH2	Cl	310
2	CH3	H	NHCH2	SO2CH3	7.4
3^b	CH3	H	NHCH2	SO2CH3	2.4
4	CH3	H	NHCH2	NO2	11
5	CH3	H	NHCH2	COCH3	57
6	CH3	H	NHCH2	CHOHCH3	13
7	CH3	H	NHCH2	CN	160
8	CH3	H	NHCH2	SO2CF3	21
9	OCH2Ph	H	NHCH2	Cl	19
10	OCH2Ph	H	NHCH2	NO2	0.2
11	OCH2Ph	H	NHCH2	SO2CH3	0.3
12	OCH2Ph	H	NHCH2	SO2CF3	1.0
13	OCH2Ph	H	NHCH2	COCH3	1.2
14	OCH2Ph	H	NHCH2	CN	2.8
15	OCH2Ph	H	NHCH2	CF3	2.9
16	OCH2Ph	H	NHCH2	OCH3	7.7
17	OCH2Ph	H	NHCH2	H	50
18	CH2Ph	H	NHCH2	Cl	3170
19	OCH2Ph	H	OCH2	SO2CH3	6.9
20	OCH2Ph	H	OCH2	CN	83
21	OCH2Ph	H	CH2NH	NO2	0.8
22	CH3	H	CH2NH	NO2	9.2
23	CH3	H	CH2NH	SO2CH3	9.8
24	CH3	H	CH2NH	Cl	300
25	CH3	Cl	NHCH2	SO2CH3	4.2
26	CH3	Br	NHCH2	SO2CH3	5.7
27	CH3	H	N(CH3)CH2	SO2CH3	3.7

^aTaken from Ref. [16]. ^bCompound having 3,5-F₂ at terminal phenyl ring.

Table II.  Descriptor classes used for modeling the binding activity of the 2,4-diaminopyrimidine analogues and identified categories in modeling the activity.

Descriptor class (acronyms)^a	Definition and scope	Descriptor’s category^b
Constitutional (CONST)	Dimensionless or 0D descriptors; independent from molecular connectivity and conformations	I
Topological (TOPO)	2D-descriptor from molecular graphs and independent conformations	I
Molecular walk counts (MWC)	2D-descriptors representing self-returning walks counts of different lengths	II
Modified Burden eigenvalues (BCUT)	2D-descriptors representing positive and negative eigenvalues of the adjacency matrix, weights the diagonal elements and atoms	I
Galvez topological charge indices (GVZ)	2D-descriptors representing the first 10 eigenvalues of corrected adjacency matrix	I
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)	I
Functional groups (FUNC)	Molecular descriptors based on the counting of the chemical functional groups	II
Atom centered fragments (ACF)	Molecular descriptors based on the counting of 120 atom centered fragments, as defined by Ghose-Crippen	I
Empirical (EMP)	1D-descriptors represent the counts of non-single 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	I

^aReference [20]. ^bDescriptor categories identified at the end of second stage; in this the filter values are: 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 27.

Table III.  Observed, calculated and predicted (LOO) pIC₅₀ values of training set compounds.

S. No.	Obsd.	Calc. F.B.	pIC50 (M)^a
			Eq. (2)		Eq. (12)		Eq. (13)		Eq. (14)		Eq. (15)		Eq. (16)
			Calc.	LOO	Calc.	LOO	Calc.	LOO	Calc.	LOO	Calc.	LOO	Calc.	LOO
1	6.51	6.48	6.59	6.59	6.47	6.47	6.33	6.28	6.64	6.66	6.68	6.71	6.50	6.50
2	8.13	8.10	8.08	8.08	7.67	7.64	8.16	8.16	8.14	8.14	8.18	8.18	7.96	7.94
3	8.62	–^b	8.08	8.08	9.16	9.68	8.02	7.96	8.14	8.10	8.18	8.14	8.85	8.92
4	7.96	8.03	7.96	7.96	7.89	7.88	8.17	8.24	8.14	8.16	8.18	8.20	8.17	8.25
5	7.24	7.37	7.62	7.62	7.04	7.02	7.50	7.52	7.39	7.40	7.43	7.44	7.84	7.89
6	7.89	–^b	7.55	6.65	7.04	6.96	7.53	7.51	8.04	8.12	7.43	7.40	7.86	7.84
7	6.80	6.97	6.65	7.96	7.24	7.36	6.81	6.82	6.64	6.61	6.68	6.67	6.96	6.98
8	7.68	7.62	7.96	8.06	8.14	8.19	8.03	8.07	8.14	8.18	8.18	8.23	8.01	8.04
9	7.72	7.90	8.06	9.43	7.79	7.79	7.53	7.50	7.77	7.78	7.80	7.81	7.70	7.70
10	9.70	9.46	9.44	9.56	9.23	9.10	9.39	9.30	9.44	9.39	9.45	9.41	9.24	9.05
11	9.52	9.53	9.55	9.43	8.98	8.90	9.05	8.99	9.28	9.24	9.29	9.26	9.02	8.95
12	9.00	9.05	9.43	9.09	9.43	9.52	9.02	9.02	9.28	9.31	9.29	9.33	9.08	9.10
13	8.92	8.80	9.09	8.12	8.38	8.33	8.41	8.35	8.52	8.49	8.54	8.51	8.91	8.91
14	8.55	8.40	8.12	7.86	8.61	8.63	8.16	8.02	7.94	7.86	7.97	7.88	8.01	7.95
15	8.54	–^b	7.86	8.43	8.98	9.04	7.23	7.09	7.77	7.64	7.80	7.66	9.09	9.17
16	8.11	–^b	8.43	7.06	7.76	7.72	8.40	8.46	8.47	8.49	8.49	8.52	7.71	7.63
17	7.30	–^b	7.06	6.59	7.32	7.32	7.50	7.53	7.77	7.85	7.80	7.88	7.70	7.78
18	5.50	–^b	6.59	8.34	6.70	6.92	6.72	6.92	5.80	5.95	5.87	6.05	5.60	5.66
19	8.16	8.19	8.34	6.90	8.12	8.11	8.54	8.74	8.72	8.94	8.65	8.93	8.55	8.71
20	7.08	7.06	6.90	9.43	7.76	7.83	7.86	7.91	7.63	7.87	7.57	7.88	7.54	7.76
21	9.10	9.36	9.44	7.96	9.23	9.27	9.60	9.77	9.43	9.48	9.44	9.50	9.23	9.28
22	8.04	7.93	7.96	8.08	7.89	7.86	8.40	8.48	8.12	8.12	8.16	8.17	8.16	8.21
23	8.01	8.00	8.08	6.59	7.67	7.65	8.10	8.11	8.12	8.13	8.16	8.17	7.95	7.95
24	6.52	6.37	6.59	8.08	6.47	6.46	6.57	6.58	6.64	6.65	6.68	6.71	6.50	6.50
25	8.38	–^b	8.08	8.08	8.11	8.08	8.35	8.35	8.12	8.09	8.16	8.14	7.97	7.93
26	8.24	–^b	8.08	8.08	8.11	8.09	8.48	8.50	8.12	8.11	8.16	8.15	7.98	7.95
27	8.43	–^b	8.08	7.54	8.43	8.43	7.76	7.61	7.48	7.03	7.45	6.82	7.54	7.10

^apIC₅₀ expressed as negative logarithm on molar basis, taken from Ref. [16]. ^bNot included in the Fujita-Ban study.

Table IV.  The Fujita-Ban contributions of substituents and parent moiety to the GHS-R binding activity of the 2,4-diaminopyrimidine analogues.

Position	Substituent	Contribution to pIC50
Parent moiety	μ	6.476(±0.22)
R1	OCH2C6H5	1.429(±0.18)
X	CH2NH	−0.103(±0.22)
	OCH2	−1.346(±0.30)
Y	CN	0.497(±0.30)
	COCH3	0.892(±0.31)
	NO2	1.559(±0.26)
	SO2CF3	1.149(±0.31)
	SO2CH3	1.628(±0.27)

Table V.  The selected QSAR models, emerged in one and two descriptors from different descriptor classes belonging to category-I.

Descriptor’s Class	Constant	Descriptor-1	Descriptor-2	r^a	s	F	Q^2	Eq.
CONS	6.742	0.722nO	—	0.769	0.638	34.731	0.472	(3)
	3.860	0.544nN	0.755nO	0.815	0.590	22.822	0.525	(4)
TOPO	6.841	0.012T(N..O)	—	0.756	0.653	32.028	0.487	(5)
	4.828	0.396S3K	0.012T(N..O)	0.835	0.561	26.388	0.601	(6)
BCUT	−72.914	8.789BEHv8	29.021BELp2	0.791	0.624	19.181	0.475	(7)
GVZ	3.369	8.441GGI8	22.027JGI3	0.795	0.618	19.801	0.525	(8)
2D-AUTO	10.902	−10.23MATS7v	−3.771GATS1e	0.821	0.582	23.743	0.578	(9)
ACF	8.223	−1.128C-002	0.484O-058	0.754	0.669	15.160	0.449	(10)
PROP	2.291	0.031MR	0.032PSA	0.767	0.653	16.457	0.439	(11)

^a, in all the number of compounds (n) are 27, r is the correlation coefficient, Q² is cross-validated index from leave-one-out (LOO) procedure, s is the standard error of the estimate and F is the F-ratio between the variances of calculated and observed activities. CONS: nO, Number of oxygen atoms; nN, Number of nitrogen atoms; TOPO: T(N..O), Sum of topological distances between N..O; S3K, 3-Path Kier alpha-modified shape index; BCUT: BEHv8, Highest eigenvalue n.8 of Burden Marix/weighted by atomic van der Waals volumes; BELp2, Lowest eigenvalue n.2 of Burden Marix/weighted by atomic polarizabilities, GVZ: GGI8, Topological charge index of order 8; JGI3, Mean topological charge index of order 3; 2D-AUTO: MATS7v, Moran autocorrelation of lag 7/weighted by atomic van der Waals volumes; GATS1e, Geary autocorrelation of lag 1/weighted by atomic Sanderson electronegativities; ACF: C-002, CH2R2; O-058, O =; PROP: MR, Ghose-Crippen molar refractivity; PSA, Fragment based polar surface area.

Table VI.  Descriptors identified for modeling the binding affinities of 2,4-diaminopyrimidine derivatives at the growth hormone secretagogue receptors along with the average regression coefficients and the total incidences.

Descriptor’s Class	Descriptor^a	Avg reg coeff (incidence)^b	Descriptor^a	Avg reg coeff (incidence)^b	Descriptor^a	Avg reg coeff (incidence)^b
CONS	Mv	−40.938(3)	RBN	0.642(3)	RBF	28.436(1)
	nN	0.811(23)	—	—	—	—
TOPO	HNar	−5.473(1)	GNar	−8.763(1)	MAXDP	0.636(43)
	X0A	36.292(1)	XMOD	0.067(1)	IC2	2.446(8)
	TIC2	0.033(6)	TIC3	0.017(1)	T(N..N)	0.011(10)
	T(N..O)	0.012(9)	—	—	—	—
BCUT	BELm5	5.952(1)	BELm8	10.419(5)	BEHv8	8.628(6)
	BELv2	16.592(3)	BELv8	5.489(2)	BEHe2	11.367(3)
	BELe8	8.072(7)	BEHp8	9.263(6)	BELp8	5.262(2)
GVZ	GGI5	4.981(2)	GGI8	8.710 (15)	JGI3	27.530(1)
2D-AUTO	MATS2v	11.081(7)	MATS7v	−10.027(1)	MATS8v	6.125(1)
	MATS5e	7.223(5)	GATS8v	−5.759(1)	GATS1e	−3.136(2)
	GATS8e	−2.814(2)	—	—	—	—
FUNC	nNHRPh	0.741(2)	nNO2Ph	1.012(14)	nROR	0.974(5)
	nRORPh	−0.910(1)	nHDon	0.649(7)	—	—
ACF	C-002	−0.980(16)	C-025	0.642(1)	H-047	0.120(1)
	O-061	0.506(1)	N-076	1.012(14)	—	—
PROP	MLOGP	−0.601(1)	—	—	—	—

^aThe descriptors are identified from the three parameter model emerged from CP-MLR protocol with filter-1 as 0.30; filter-2 as 2.0; filter-3 as 0.911; filter-4 as 0.3 ≤ Q² ≤ 1.0; number of compounds in the study are 27; CONS: Mv, Mean atomic van der Waals volume (scaled on Carbon atom); RBN, Number of rotatable bonds; RBF, Rotatable bond fraction; nN, Number of nitrogen atoms; TOPO: HNar, Narumi harmonic topological index; GNar, Narumi geometric topological index; MAXDP, Maximal electrotopological positive variation; X0A, Average connectivity index of 0 order; XMOD, Modofied Randic chi-1 index; IC2, Information content index (neighbourhood symmetry of 2-order); TIC2 and TIC3, Total information content index (neighbourhood symmetry of 2 and 3-order, respectively); T(N..N) and T(N..O), Sum of topological distances between N..N and N..O, respectively; BCUT: BELm5 and BELm8, Lowest eigenvalue n.5 and 8, respectively, of Burden Marix/weighted by atomic masses; BEHv8, Highest eigenvalue n.8 of Burden Marix/weighted by atomic van der Waals volumes; BELv2 and BELv8, Lowest eigenvalue n.2 and 8, respectively, of Burden Marix/weighted by atomic van der Waals volumes; BEHe2, Highest eigenvalue n. 2 of Burden Marix/weighted by atomic Sanderson electronegativities; BELe8, Lowest eigenvalue n.8 of Burden Marix/weighted by atomic Sanderson electronegativities; BEHp8, Highest eigenvalue n.8 of Buden Marix/weighted by atomic polarizabilities; BELp8, Lowest eigenvalue n.8 of Burden Marix/weighted by atomic polarizabilities; GVZ: GGI5 and GGI8, Topological charge index of order 5 and 8, respectively; JGI3, Mean topological charge index of order 3; 2D-AUTO: MATS2v, MATS7v and MATS8v Moran autocorrelation -lag 2, 7 and 8, respectively/weighted by atomic van der waals volumes; MATS5e, Moran autocorrelation-lag 5/weighted by atomic Sanderson electronegativities; GATS8v, Geary autocorrelation-lag 8/weighted by atomic van der waals volumes; GATS1e and GATS8e, Moran autocorrelation-lag 1 and 8, respectively/weighted by atomic Sanderson electronegativities; FUNC: nNHRPh, Number of secondary aromatic amines; nNO2Ph, Number of nitro groups (aromatic); nROR, Number of ethers (aliphatic); nRORPh, Number of ethers (aromatic); nHDon, Number of donor atoms for H-bonds (with N and O); ACF: C-002, CH2R2; C-025, R-CR-R; H-047 H attached to C1(sp3)/C0(sp2); O-061, O–; N-076, Ar-NO2/R-N(-R)-O/RO-NO2; PROP: MLOGP, Moriguchi octanol-water partition coefficient (logP). ^bThe average regression coefficient of the descriptor corresponding to all models and the total number of its incidences; the arithmetic sign of the coefficient represents the actual sign of the regression coefficient in the models.

Table VII.  Cross-correlation matrix^a amongst predictor variables in models.

		Eq. (2)					Eq. (12)
	HA(R1)	MRY	IX	IY		nN	GGI8	JGI3
HA(R1)	1.000	0.295	0.316	0.047	nN	1.000	0.205	0.157
MRY		1.000	0.042	0.235	GGI8		1.000	0.257
IX			1.000	0.118	JGI3			1.000
IY				1.000
		Eq. (13)					Eq. (14)
	nN	T(N..O)	MATS7v			T(N..O)	nHDon	C-002
nN	1.000	0.022	0.197		T(N..O)	1.000	0.197	0.199
T(N..O)		1.000	0.250		nHDon		1.000	0.207
MATS7v			1.000		C-002			1.000
		Eq. (15)					Eq. (16)
	T(N..O)	nNHRPh	C-002			MAXDP	nNO2Ph	nHDon	C-002
T(N..O)	1.000	0.183	0.199		MAXDP	1.000	0.008	0.094	0.000
nNHRPh		1.000	0.163		nNO2Ph		1.000	0.082	0.069
C-002			1.000		nHDon			1.000	0.207
					C-002				1.000

^aMatrix elements are the r-values.

Figure 1.  Plot of observed versus calculated and predicted pIC₅₀ values.

Table VIII.  The structures^a of the 2, 4-diaminopyrimidine analogues included in test set and the predictions with corresponding test set r².

S.No.	R1	R3	Obsd.	pIC50 (M) Calculated
				Eq. (12)	Eq. (13)	Eq. (14)	Eq. (15)	Eq. (16)
28	CH3		6.96	7.26	6.54	6.64	6.68	6.50
29	CH3		6.54	6.38	5.82	6.64	6.68	6.50
30	OCH2Ph		8.82	8.54	7.98	7.92	7.94	7.70
31	OCH2Ph		8.20	7.58	7.26	7.77	7.80	7.70
32	OCH2Ph		7.68	8.17	8.24	7.92	7.94	7.70
33	OCH2Ph		7.37	7.58	7.45	7.77	7.80	7.70
34	OCH2Ph		7.17	7.78	7.44	7.77	7.80	7.70
35	OCH2Ph		6.89	8.36	7.57	7.91	7.93	7.72
	Test set r^2			0.456	0.497	0.563	0.558	0.552

^aIn all the structures: X =NHCH₂, R₂ = H.

Serby MD, Zhao H, Szczepankiewicz BG, Kosogof C, Xin Z, Liu B, Liu M, Nelson LTJ, Kaszubska W, Falls HD, Schaefer V, Bush EN, Shapiro R, Droz BA, Knourek-Segel VE, Fay TA, Brune ME, Beno DWA, Turner TM, Collins CA, Jacobson PB, Sham HL, Liu G. 2,4-Diaminopyrimidine derivatives as potent growth hormone secretagouge receptor antagonists. J Med Chem 2006;49:2568–2578.

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DRAGON software version 3.0-2003. By Todeschini R, Consonni V, Mauri A, Pavan M. Milano, Italy. http//disat.unimib.it/chm/Dragon.htm.

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