Chemometric study of some α, β-unsaturated ketone as potential antifungal agents using density function theory and GFA (ATCC 10231 and NCIM 3446 cell line)

Figures & data

Table 1. The main structure of unsaturated ketone (a)

	X	Y	Z	A	B	Activity (ATCC 10231) pMIC		Activity (NCIM 3446) pMIC
F	Fluconazole						F
1	F	H	H	SCH3	H	1.739	21	1.535
2	Cl	H	H	SCH3	H	1.464	22	1.163
3	Br	H	H	SCH3	H	0.923	23	0.525
4	Cl	H	Cl	SCH3	H	0.813	24	0.211
5	NO2	H	H	SCH3	H	0.780	25	0.479
6	OCH3	H	H	SCH3	H	1.457	26	1.156
7	H	H	H	SCH3	H	1.083	27	0.782
8	OH	H	H	SCH3	H	1.134	28	0.833
9	H	H	OH	SCH3	H	1.134	29	1.134
10	H	OH	H	SCH3	H	1.134	30	0.833
11	Phenyl	H	H	SCH3	H	0.522	31	0.124
12	OCH3	–	–	–	OCH3	1.199	32	1.500

Table 2. The main structure of the unsaturated ketone (b)

	X	Y	Activity (ATCC 10231) pMIC		Activity (NCIM 3446) pMIC
13		H	1.739	33	1.739
14		Br	0.946	34	0.849
15		H	1.483	35	1.182
16		Br	0.885	36	0.584
17		H	0.483	37	0.086
18		Br	0.584	38	0.186
19		H	1.111	39	1.111
20		Br	0.528	40	0.829

Table 3. Parameters for energy minimization

Parameters	Value
Force field	MMFF (Merck Molecular Force Field)
Maximum no of cycles	1,00,000
Convergence criteria	0.001 cal/molǺ
Dielectric constant	1 (in a vacuum)
Gradient type	Analytical

Table 4. List of descriptors used in this study

Descriptor	Type	Significance	VIF	1/VIF (Tolerance)
BCUTw-1l	BCUT	Designed to encode atomic properties that govern intermolecular interaction	1.34	0.75
PNSA-3	CPSA	Charge weighted partial negative surface area	1.18	0.85
MOMI-XZ	Moment of inertial	Is the ratio of x to y	1.93	0.52
Polar surface area	Dimensional	It combines shape and electronic information to characterize molecule	1.27	0.79
MAX ELPOT	Quantum electronics	Is a measure of energy lowering due to the maximal energy flow between donor and acceptors	1.28	0.78
Logp	Lipophilicity	The logarithm of the partition coefficient between n-octanol and water	1.32	0.76

Table 5. Univariate analysis of the observed data

		A: pMIC
1	Number of sample points	32
2	Range	1.65300000
3	Maximum	1.73900000
4	Minimum	0.08600000
5	Mean	0.88575000
6	Median	0.84100000
7	Variance	0.16562000
8	Standard deviation	0.41347700
9	Mean absolute deviation	0.32584400
10	Skewness	0.02125400
11	Kurtosis	−0.66976600

Table 6. Experimental pMIC and GFA-predicted pMIC for the training set

	Actual values for A: pMIC	Predicted values	Residual values
1	1.46400000	1.17415500	0.28984500
2	0.92300000	1.09714100	−0.17414100
3	0.81300000	1.13876000	−0.32576000
4	0.78000000	0.62494400	0.15505600
5	1.45700000	1.59743200	−0.14043200
6	1.13400000	1.15515100	−0.02115100
7	1.13400000	1.21516000	−0.08116000
8	0.52200000	0.31406600	0.20793400
9	1.19900000	1.24385700	−0.04485700
10	0.94600000	0.99292000	−0.04692000
11	0.88500000	1.08261800	−0.19761800
12	0.48300000	0.48121300	0.00178700
13	0.58400000	0.42352200	0.16047800
14	1.11100000	0.89727600	0.21372400
15	0.82900000	0.87721400	−0.04821400
16	1.53500000	1.41141100	0.12358900
17	0.52500000	0.54215300	−0.01715300
18	0.21100000	0.18402400	0.02697600
19	0.47900000	0.41776600	0.06123400
20	1.15600000	1.17350700	−0.01750700
21	0.78200000	0.71369000	0.06831000
22	0.83300000	0.71784500	0.11515500
23	1.13400000	1.00680700	0.12719300
24	0.83300000	1.12437100	−0.29137100
25	0.12400000	0.31406600	−0.19006600
26	1.50000000	1.25590100	0.24409900
27	1.73900000	1.46277400	0.27622600
28	0.84900000	0.69688500	0.15211500
29	1.18200000	1.05402700	0.12797300
30	0.58400000	0.66801500	−0.08401500
31	0.08600000	0.40811300	−0.32211300
32	0.52800000	0.87721400	−0.34921400

Table 7. Validation of the genetic function approximation

		Equation (1)
1	Friedman LOF	0.18672200
2	R^2	0.80845500
3	$R_{\text{adj}}^2$	0.76248400
4	$R_{\text{cv}}^2$	0.70000000
5	Significant regression	Yes
6	Significance of F-value	17.58623400
7	Critical SOR F-value (95%)	2.50303300
8	Lack-of-fit points	23
9	Computed experimental error	0.24950200

Table 8. Best model

Y = −0.1052a + 0.006425b + 0.0743c − 0.07419d + 0.009784e − 0.604521f + 3.5836

Note: a = BCUTw-1l, b = PNSA-3, c = MOMI-XZ, d = polar surface area, e = max elpot and f = Logp.

Table 9. External validation of the best model (three outliers were detected i.e. compound 9, 38, and 39)

Compds	BCUTw-1l	PNSA-3	MOMI-XZ	PSA	MaxELpot	Logp	Observed Activity	Predicted Activity	Residua
1	11.998	−30.60	8.83	14.3	90.17	1.97	1.74	1.41	0.33
7	11.996	−28.35	7.68	14.3	94.45	2.25	1.08	1.21	−0.13
13	11.996	−33.81	14.88	14.7	92.03	2.57	1.74	1.46	0.28
15	11.998	−37.26	6.67	20.7	99.51	1.59	1.48	1.05	0.43
22	20.729	−60.22	0	0	0	0	1.16	1.02	0.15

Figure 1. The Williams plot, the plot of the standardized residuals against the leverage values.

Figure 2. Relation between the predicted and observed activity using Table 6, for training and tests sets.

Figure 3. The residual against observed activity for the training and test sets.

Figure 4(a) and (b). Outlier analysis.

Figure 5. The graph of the variable usage against generation number.