QSAR Models for CXCR2 Receptor Antagonists Based on the Genetic Algorithm for Data Preprocessing Prior to Application of the PLS Linear Regression Method and Design of the New Compounds Using In Silico Virtual Screening
Abstract
:1. Introduction
2. Data and Methods
2.1. Data Set
2.2. Computer Hardware and Software
2.3. Structural Descriptors
2.4. Model Validation
3. Results and Discussion
3.1. Stepwise Multiple Linear Regression (MLR)
3.2. Interpretation of the Selected Descriptors
3.3. Partial Least Squares (PLS)
3.4. Partial Least Squares combined with Genetic Algorithm (GA-PLS)
3.5. In Silico Screening
4. Conclusions
References
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Compound | R1 | R2 | R3 | R4 | IC50 for CXCR2 (µM) | pIC50 |
---|---|---|---|---|---|---|
1 | Me | CN | H | H | 0.07 | 7.14 |
2 | Me | Br | H | H | 0.17 | 6.77 |
3 | Et | CN | H | H | 0.06 | 7.19 |
4 | n-Pr | CN | H | H | 1.30 | 5.89 |
5 | Bn | CN | H | H | 1.40 | 5.85 |
6 | i-Pr | CN | H | H | 0.22 | 6.66 |
7 | Ph | CN | H | H | 0.26 | 6.58 |
8 | CF3 | CN | H | H | 0.09 | 7.06 |
9 | Me | CN | OMe | H | 0.16 | 6.80 |
10 | Me | CN | Me | H | 0.02 | 7.72 |
11 | Me | Br | - | - | 0.25 | 6.60 |
12 | Me | CN | - | - | 0.64 | 6.19 |
13 | Ph | Br | - | - | 0.12 | 6.92 |
14 | Ph | CN | - | - | 0.14 | 6.85 |
15 | o-Cl-Phenyl | CN | - | - | 0.40 | 6.40 |
16 | p-F-Phenyl | CN | - | - | 0.52 | 6.28 |
17 | Me | Me | H | - | 0.05 | 7.30 |
18 | Me | H | H | - | 0.12 | 6.92 |
19 | H | H | H | - | 0.07 | 7.18 |
20 | Et | Et | H | - | 1.10 | 5.96 |
21 | n-Butyl | H | H | - | 1.10 | 5.96 |
22 | Ph | H | H | - | 0.88 | 6.05 |
23 | -CH2CH2OMe | H | H | - | 0.26 | 6.58 |
24 | Me | Me | OMe | - | 0.06 | 7.24 |
25 | Me | Me | Me | - | 0.02 | 7.62 |
Compound | R | IC50 CXCR2 (nM) | pIC50 |
---|---|---|---|
26 | 5-H | 0.005 | 8.3 |
27 | 5-Me | 0.006 | 8.24 |
28 | 5-Et | 0.004 | 8.39 |
29 | 5-Br | 0.005 | 8.33 |
30 | 5-Cl | 0.005 | 8.32 |
31 | 5-CF3 | 0.017 | 7.76 |
32 | 5-CF2H | 0.007 | 8.17 |
33 | 5-CH2OH | 0.003 | 8.55 |
34 | 5-CH2N(Me)2 | 0.094 | 7.03 |
35 | 5-CON(Me)2 | 0.171 | 6.77 |
36 | 5-(20Cl)Ph | 0.049 | 7.31 |
37 | 5-(2-CF3)Ph | 0.15 | 6.82 |
38 | 5-(3-Cl)Ph | 0.058 | 7.24 |
39 | 5-(3-CF3)Ph | 0.087 | 7.06 |
40 | 4-Cl | 0.0045 | 8.35 |
41 | 4-Br | 0.005 | 8.30 |
42 | 4-(4-Pyridyl) | 0.009 | 8.02 |
43 | 4-(3-Thienyl) | 0.008 | 8.09 |
44 | 4-(3,5-Dimethyl-4-isoxazoyl) | 0.008 | 8.12 |
45 | 2,3-Benzofuran | 0.003 | 8.46 |
46 | 3-Br | 0.016 | 7.78 |
47 | 8.6 | 8.06 | |
48 | 10.9 | 7.96 | |
49 | 9.8 | 8.01 | |
50 | 9.8 | 8.01 | |
51 | 7.5 | 8.12 | |
52 | 8.2 | 8.10 | |
53 | 8.0 | 8.10 | |
54 | 5.8 | 8.24 | |
55 | 6.2 | 8.21 | |
56 | 6.2 | 8.21 | |
57 | 21 | 7.68 | |
58 | 50 | 7.30 |
Compound | R1 | R2 | R3 | R4 | R5 | R6 | IC50 for CXCR2 (nM) | pIC50 |
---|---|---|---|---|---|---|---|---|
59 | OH | H | Cl | H | Br | H | 906 | 6.04 |
60 | OH | Cl | Cl | H | Br | H | 63 | 7.20 |
61 | OH | CONH2 | Cl | H | Br | H | 10 | 8.00 |
62 | OH | CH2NH2 | Cl | H | Br | H | 114 | 6.94 |
63 | OH | SO2NH2 | Cl | H | Br | H | 7 | 8.15 |
64 | OH | SO2NMe2 | Cl | H | Br | H | 12 | 7.92 |
65 | OH | H | CN | H | Br | H | 25 | 7.60 |
66 | OH | Br | CN | H | Br | H | 6 | 8.22 |
67 | OH | Cl | CN | H | Br | H | 22 | 7.66 |
68 | OH | CN | Cl | H | Br | H | 57 | 7.24 |
69 | OH | H | NO2 | H | Br | H | 22 | 7.66 |
70 | OH | H | NO2 | H | H | H | 320 | 6.49 |
71 | OH | NO2 | H | H | H | H | 860 | 6.07 |
72 | OH | H | H | NO2 | H | H | 10900 | 4.96 |
73 | OH | H | CN | H | H | H | 200 | 6.70 |
74 | OH | SO2NH2 | Cl | H | Cl | Cl | 9.3 | 8.03 |
75 | –N=N–NH– | CN | H | Br | H | 39 | 7.49 |
Compound | R | IC50 for CXCR2 (nM) | pIC50 |
---|---|---|---|
76 | -SO2C2H5 | 130 | 6.87 |
77 | -SO2CH(CH3)2 | 400 | 6.40 |
78 | 460 | 6.34 | |
79 | -SO2C6H5 | 90 | 7.05 |
80 | 32 | 7.49 | |
81 | -SO2CH2C6H5 | 280 | 6.55 |
82 | Cl | 1000 | 6.00 |
Compound | R1 | R2 | IC50 for CXCR2 (nM) | pIC50 |
---|---|---|---|---|
83 | C6H5CH2 | C6H5 | 2400 | 5.62 |
84 | 3-OHC6H4CH2 | C6H5 | 4400 | 5.36 |
85 | C6H5CH2 | 4-Pyridinyl | 7700 | 5.11 |
86 | C6H5CH2 | 2-Furanyl | 4200 | 5.38 |
87 | C6H5CH2 | 4-CNC6H4 | 3500 | 5.46 |
88 | C6H5CH2 | 3-CF3C6H4 | 3500 | 5.46 |
89 | C6H5CH2 | 4-CF3C6H4 | 2800 | 5.55 |
90 | C6H5CH2 | 4-CH3OC6H4 | 2300 | 5.64 |
91 | C6H5CH2 | 3,5-diClC6H3 | 2000 | 5.70 |
92 | C6H5CH2 | 2-Thienyl | 2000 | 5.70 |
93 | C6H5CH2 | 2-CH3C6H4 | 1400 | 5.85 |
94 | C6H5CH2 | 2-CH3OC6H4 | 1400 | 5.85 |
95 | C6H5CH2 | 3-ClC6H4 | 1000 | 6.00 |
96 | C6H5CH2 | 2-FC6H4 | 890 | 6.05 |
97 | C6H5CH2 | 4-ClC6H4 | 830 | 6.08 |
98 | C6H5CH2 | 3,4-diClC6H3 | 800 | 6.10 |
99 | C6H5CH2 | 2,5-diClC6H3 | 670 | 6.17 |
100 | C6H5CH2 | 2-ClC6H4 | 450 | 6.35 |
101 | C6H5CH2 | 2,4-diClC6H3 | 410 | 6.39 |
102 | C6H5CH2 | 2-BrC6H4 | 350 | 6.46 |
103 | C6H5CH2 | 2,3-diClC6H3 | 350 | 6.46 |
104 | 4- CH3OC6H4CH2 | 2,4-diClC6H3 | 10000 | 5.00 |
105 | 3-CH3OC6H4CH2 | 2,4-diClC6H3 | 4200 | 5.38 |
106 | 3-CH3C6H4CH2 | 2,4-diClC6H3 | 730 | 6.14 |
107 | 4-Cl C6H4CH2 | 2,4-diClC6H3 | 300 | 6.52 |
108 | 3-C6H5O C6H4CH2 | 2,4-diClC6H3 | 170 | 6.77 |
109 | 3-Cl C6H4CH2 | 2,4-diClC6H3 | 92 | 7.04 |
110 | 3-Cl C6H4CH2 | 2-ClC6H4 | 28 | 7.55 |
Compound | IC50 for CXCR2 (nM) | pIC50 | |
---|---|---|---|
111 | 160 | 6.80 | |
112 | 4 | 8.40 | |
113 | 13 | 7.89 | |
114 | 630 | 6.20 | |
115 | 7 | 8.15 | |
116 | 280 | 6.55 | |
117 | 140 | 6.85 | |
118 | 280 | 6.55 | |
119 | 850 | 6.07 | |
120 | 5 | 8.30 | |
121 | 350 | 6.46 | |
122 | 16 | 7.80 | |
123 | 2 | 8.70 | |
124 | 45 | 7.35 | |
125 | 2500 | 5.60 | |
126 | 220 | 6.66 |
Compound | R | IC50 for CXCR2 (nM) | pIC50 |
---|---|---|---|
1a 10a | 3 1 | 8.52 9 | |
1b 10b | 4 1 | 8.40 9.00 | |
1c 10c | 13 2 | 7.89 8.70 | |
1d 10d | 13 5 | 7.89 8.30 | |
1e 10e | 35 5 | 7.46 8.30 | |
1f 10f | 120 60 | 6.92 7.22 |
Parameter | PLS | GA-PLS | SMLR |
---|---|---|---|
RMSEP | 0.50 | 0.51 | 0.56 |
AREPred. | 5.98 | 5.53 | 1.3 |
R2 | 0.748 | 0.779 | 0.78 |
R2Training Set | 0.727 | 0.88 | 0.68 |
Q2 | 0.68 | 0.713 | 0.66 |
SEP | 0.50 | 0.51 | 0.53 |
R2 − Ro2/R2 | −0.291 | −0.254 | −0.254 |
K | 1.019 | 1.035 | 0.962 |
Iteration | PLS | GA-PLS | ||
---|---|---|---|---|
R2 | Q2 | R2 | Q2 | |
1 | 0.0047 | −0.949 | 0.010 | −0.577 |
2 | 0.005 | −0.423 | 0.010 | −0.919 |
3 | 0.039 | −0.467 | 0.036 | −0.417 |
4 | 0.12 | −0.198 | 0.019 | −0.506 |
5 | 0.005 | −0.955 | 0.006 | −0.878 |
6 | 0.005 | −0.955 | 0.153 | −0.063 |
7 | 0.006 | −0.967 | 0.084 | −0.245 |
8 | 0.186 | −1.601 | 0.001 | −0.699 |
9 | 0.002 | −0.753 | 0.073 | −1.21 |
10 | 0.171 | −1.57 | 0.147 | −0.41 |
pIC50 | MATS5v | GATS8p | MATS2m | BEHp2 | |
---|---|---|---|---|---|
pIC50 | 1 | ||||
MATS5v | −0.26863 | 1 | |||
GATS8P | −0.16055 | −0.00856 | 1 | ||
MATS2m | 0.001149 | −0.08958 | −0.0286 | 1 | |
BEHp2 | 0.214723 | −0.04342 | −05904 | 0.000615 | 1 |
Descriptora | Coefficient | MFb |
---|---|---|
MATS5v | −8.9918 (±8.729) | −0.254 |
GATS8P | −5.409 (±0.463) | −0.063 |
MATS2m | −1.337 (±0.349) | 1.484 |
BEHp2 | 31.527 (±7.936) | −0.166 |
Constant | −3.539 (±1.156) |
No. | pIC50 (Exp.) | PLS | GA-PLS | SMLR | |||
---|---|---|---|---|---|---|---|
pIC50 (Pred.) | Residual | pIC50 (Pred.) | Residual | pIC50 (Pred.) | Residual | ||
10 | 7.24 | 7.34 | 0.10 | 6.79 | −0.45 | 7.42 | 0.18 |
12 | 6.50 | 6.32 | −0.17 | 6.71 | 0.22 | 6.35 | −0.14 |
17 | 7.50 | 7.44 | −0.06 | 7.82 | 0.32 | 7.26 | −0.24 |
2 | 7.20 | 7.80 | 0.60 | 8.31 | 1.11 | 7.67 | 0.47 |
21 | 6.34 | 6.64 | 0.30 | 6.67 | 0.33 | 6.68 | 0.35 |
25 | 6.00 | 6.51 | 0.51 | 6.52 | 0.52 | 6.10 | 0.10 |
25a | 8.70 | 7.81 | −0.89 | 8.72 | 0.02 | 7.85 | −0.84 |
37b | 6.58 | 6.46 | −0.13 | 6.57 | −0.01 | 6.16 | −0.43 |
40 | 5.70 | 5.73 | 0.03 | 6.00 | 0.30 | 5.28 | −0.42 |
43 | 6.00 | 5.52 | −0.48 | 5.78 | −0.22 | 5.65 | −0.35 |
45b | 5.96 | 5.22 | −0.73 | 5.60 | −0.36 | 6.55 | 0.59 |
47 | 6.14 | 6.80 | 0.62 | 6.70 | 0.52 | 5.60 | −0.57 |
51 | 6.45 | 6.58 | 0.12 | 6.30 | −0.15 | 6.10 | −0.35 |
53b | 6.85 | 6.45 | −0.41 | 6.61 | −0.24 | 6.30 | −0.56 |
58c | 8.39 | 7.60 | −0.79 | 7.31 | −1.08 | 7.67 | −0.71 |
6 | 7.92 | 8.50 | 0.58 | 7.64 | −0.28 | 8.21 | 0.29 |
ID | Definition | Group |
---|---|---|
1 | RBN, RBF | Constitutional |
2 | D/D, J, MAXDN, MAXDP, X5, X0v, X1v, X3v, X4Av, X5Av, X0sol, X0sol, X1sol, X2sol, X3sol, X4sol, X5sol, S0K, S1K, IDDE, IVDE, SIC0, CIC0, IC1, SIC1, CIC1,IC2, BIC4, BIC5, D/Dr05, D/dr06, T(N..O), T(N..S), T(O..O) | Topological |
3 | BEHm1, BEHm2, BEHm3, BEHm4, BEHm5, BEHm6, BEHv6, BEHv7, BEHe3, BEHe4, BELe5, BELe6 | BUCUT |
4 | GGI2,GGI3,GGI10, JGI1 | Galvez topol. Charge indices |
5 | ATS8m, ATS8v, MATS5e, MTAS6e, GATS4e, GATS5e | 2D Autocorrelations |
6 | qnmax, Qpos | Charge descriptors |
7 | FDI, PJI3, DISPv, QYYv | Geometrical |
8 | RDF06u, RDF065u, RDF120u, RDF125u, RDF130u, RDF135u, RDF030m, RDF035m, RDF080m, RDF085m, RDF120m, RDF125m, RDF105v, RDF110v | RDF |
9 | Mor17u, Mor18u, Mor29u, Mor30u, Mor08m, Mor09m, Mor14m, Mor15m, Mor22m, Mor23m, Mor24m, Mor25m, Mor30m, Mor31m, Mor17v, Mor18v, Mor19v, Mor20v, Mor21v, Mor22v, Mor27v, Mor28v, Mor18e, Mor28e, Mor11p, Mor12p | 3D-MoRSE |
10 | E2u, E3u, E3e, G1p, G2p, E1p, L2s, L3s, G1s, G2s, Au, Am | WHIM |
11 | HIC, HGM, H3u, H4u, H3m, H4m, H7m, H8m, HATS2m, HATS3m, HATS1e, HATS2e, HATS7p, HATS8p, RARS, REIG, R5u, R6u, R3u+, R4u+, RTu+, R2m, RTm, R1m+, R8m+, RTm+, R1v, R2v, RTv, R1v+, R2e, R3e, RTp,R1p+ | GETAWAY |
12 | MR, PSA, MLOGP | Properties |
Cross validation | Random subset |
Number of subset | 4 |
Window width | 2 |
Initial term % | 20% |
Maximum generation | 100 |
Convergence (%) | 80 |
Cross-over | Double |
ID | X | Y | GA-PLS (pIC50 predicted) | Leverage-limit |
---|---|---|---|---|
1c | H | Br | 7.10 | 0.07 |
2c | H | Cl | 5.63 | 0.05 |
3c | H | NO2 | 6.17 | 0.05 |
4c | H | OMe | 6.01 | 0.04 |
5c | H | Me | 5.50 | 0.03 |
6c | H | Et | 5.50 | 0.04 |
7c | Br | NO2 | 5.48 | 0.04 |
8c | Br | Me | 7.20 | 0.05 |
9c | Br | OMe | 6.67 | 0.04 |
10c | Br | Et | 8.50 | 0.06 |
11c | H | H | 6.49 | 0.04 |
ID | X | GA-PLS (pIC50 predicted) | Leverage-limit |
---|---|---|---|
10c | O | 8.50 | 0.04 |
2d | NH | 7.74 | 0.07 |
3d | NMe | 8.82 | 0.05 |
4d | NOH | 7.91 | 0.07 |
5d | NOMe | 8.42 | 0.06 |
6d | NNH2 | 7.99 | 0.06 |
7d | NNHMe | 8.39 | 0.05 |
8d | NNMe2 | 8.10 | 0.08 |
9d | S | 8.98 | 0.05 |
© 2011 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
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Asadollahi, T.; Dadfarnia, S.; Shabani, A.M.H.; Ghasemi, J.B.; Sarkhosh, M. QSAR Models for CXCR2 Receptor Antagonists Based on the Genetic Algorithm for Data Preprocessing Prior to Application of the PLS Linear Regression Method and Design of the New Compounds Using In Silico Virtual Screening. Molecules 2011, 16, 1928-1955. https://doi.org/10.3390/molecules16031928
Asadollahi T, Dadfarnia S, Shabani AMH, Ghasemi JB, Sarkhosh M. QSAR Models for CXCR2 Receptor Antagonists Based on the Genetic Algorithm for Data Preprocessing Prior to Application of the PLS Linear Regression Method and Design of the New Compounds Using In Silico Virtual Screening. Molecules. 2011; 16(3):1928-1955. https://doi.org/10.3390/molecules16031928
Chicago/Turabian StyleAsadollahi, Tahereh, Shayessteh Dadfarnia, Ali Mohammad Haji Shabani, Jahan B. Ghasemi, and Maryam Sarkhosh. 2011. "QSAR Models for CXCR2 Receptor Antagonists Based on the Genetic Algorithm for Data Preprocessing Prior to Application of the PLS Linear Regression Method and Design of the New Compounds Using In Silico Virtual Screening" Molecules 16, no. 3: 1928-1955. https://doi.org/10.3390/molecules16031928