3D QSAR Pharmacophore Modeling, in Silico Screening, and Density Functional Theory (DFT) Approaches for Identification of Human Chymase Inhibitors
Abstract
:1. Introduction
2. Results and Discussion
2.1. Pharmacophore Modeling
2.2. Pharmacophore Validation
2.2.1. Test Set Prediction Method
2.2.2. Fischer Randomization Method
2.3. Search for New Potential Compounds Using Database Screening
2.4. Molecular Docking
2.5. Density Functional Theory Calculations
2.5.1. Analysis of Orbital Energies
2.5.2. Molecular Electrostatic Potential (MESP) Profiles
3. Materials and Methods
3.1. Pharmacophore Modeling
3.1.1. Selection of Training Set Compounds and Diverse Conformation Generation
3.1.2. Pharmacophore Model Generation
3.1.3. Pharmacophore Model Validation and Database Searching
3.2. Molecular Docking
3.3. Density Functional Theory (DFT) Calculations
3.3.1. Data Set of DFT Study
3.3.2. Calculation of Molecular Electrostatic Potential (MESP)
4. Conclusion
Acknowledgements
References
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Hypothesis | Total cost | ΔCost a | RMSD (Å) | Correlation (r) | Features |
---|---|---|---|---|---|
1 | 89.663 | 92.703 | 1.176 | 0.942 | HBA, HBA, HY-AR, HY-AR, HY-AR |
2 | 91.454 | 90.912 | 1.25 | 0.934 | HBA, HBA, HY-AR, HY-AR, HY-AR |
3 | 94.811 | 87.555 | 1.348 | 0.924 | HBA, HY-AR, HY-AR, RA |
4 | 95.086 | 87.28 | 1.388 | 0.919 | HBA, HBA, HY-AR, HY-AR, HY-AR |
5 | 95.379 | 86.987 | 1.387 | 0.919 | HBA, HY-AR, RA, RA |
6 | 95.458 | 86.908 | 1.396 | 0.918 | HBA, HBA, HY-AR, HY-AR, HY-AR |
7 | 95.656 | 86.71 | 1.406 | 0.916 | HBA, HBA, HY-AR, HY-AR, HY-AR |
8 | 95.855 | 86.511 | 1.409 | 0.916 | HBA, HBA, HY-AR, HY-AR, HY-AR |
9 | 95.538 | 86.828 | 1.411 | 0.916 | HBD, HY-AR, RA, RA |
10 | 96.124 | 86.242 | 1.421 | 0.915 | HBA, HBA, HY-AR, HY-AR, HY-AR |
Compound | Experimental activity (nM) | Estimated activity | Error | Activity scale a | Estimated activity scale |
---|---|---|---|---|---|
1 | 0.46 | 0.27 | −1.7 | ++++ | ++++ |
2 | 2.1 | 1.9 | −1.1 | ++++ | ++++ |
3 | 11 | 16 | 1.4 | ++++ | ++++ |
4 | 20 | 49 | 2.5 | +++ | +++ |
5 | 57 | 50 | −1.1 | +++ | +++ |
6 | 91 | 80 | −1.1 | +++ | +++ |
7 | 110 | 650 | 5.9 | +++ | ++ |
8 | 170 | 170 | 1 | +++ | +++ |
9 | 220 | 720 | 3.3 | ++ | ++ |
10 | 250 | 650 | 2.6 | ++ | ++ |
11 | 360 | 710 | 2 | ++ | ++ |
12 | 410 | 760 | 1.9 | ++ | ++ |
13 | 730 | 660 | −1.1 | ++ | ++ |
14 | 900 | 610 | −1.5 | ++ | ++ |
15 | 1300 | 930 | −1.4 | ++ | ++ |
16 | 1600 | 650 | −2.6 | ++ | ++ |
17 | 2200 | 860 | −2.6 | + | ++ |
18 | 3000 | 850 | −3.5 | + | ++ |
19 | 3500 | 830 | −4.2 | + | ++ |
20 | 5900 | 4800 | −1.2 | + | + |
Name | IC50 nM
| Error c | Activity scale d | Name | IC50 nM
| Error | Activity scale
| ||||
---|---|---|---|---|---|---|---|---|---|---|---|
Exp. a | Est. b | Exp. | Est. | Exp. | Est. | Exp. | Est. | ||||
21 | 0.5 | 0.48 | −1.0 | ++++ | ++++ | 70 | 500 | 491.7 | −1.0 | ++ | ++ |
22 | 1 | 1.00 | −1.0 | ++++ | ++++ | 71 | 550 | 592.4 | 1.0 | ++ | ++ |
23 | 2 | 65.84 | 32.9 | ++++ | +++ | 72 | 580 | 579.668 | −1.0 | ++ | ++ |
24 | 3.1 | 3.16 | 1.0 | ++++ | ++++ | 73 | 600 | 601.005 | 1.0 | ++ | ++ |
25 | 5 | 12.84 | 2.5 | ++++ | ++++ | 74 | 609 | 609.043 | 1.0 | ++ | ++ |
26 | 5.6 | 16.38 | 2.9 | ++++ | ++++ | 75 | 700 | 1545.30 | 2.2 | ++ | ++ |
27 | 6 | 6.38 | 1.0 | ++++ | ++++ | 76 | 700 | 697.894 | −1.0 | ++ | ++ |
28 | 13 | 15.57 | 1.1 | ++++ | ++++ | 77 | 710 | 709.97 | −1.0 | ++ | ++ |
29 | 19 | 19.30 | 1.0 | ++++ | ++++ | 78 | 780 | 779.896 | −1.0 | ++ | ++ |
30 | 20 | 524.55 | 26.2 | +++ | ++ | 79 | 800 | 798.863 | −1.0 | ++ | ++ |
31 | 24 | 23.99 | −1.0 | +++ | +++ | 80 | 860 | 860.59 | 1.0 | ++ | ++ |
32 | 26 | 26.03 | 1.0 | +++ | +++ | 81 | 890 | 889.222 | −1.0 | ++ | ++ |
33 | 27 | 27.18 | 1.0 | +++ | +++ | 82 | 890 | 889.127 | −1.0 | ++ | ++ |
34 | 30 | 526.07 | 17.5 | +++ | ++ | 83 | 1100 | 1103.48 | 1.0 | ++ | ++ |
35 | 32 | 42.12 | 1.3 | +++ | +++ | 84 | 1200 | 1209.95 | 1.0 | ++ | ++ |
36 | 37 | 37.00 | −1.0 | +++ | +++ | 85 | 1200 | 1193.16 | −1.0 | ++ | ++ |
37 | 37 | 35.56 | −1.0 | +++ | +++ | 86 | 1400 | 1399.23 | −1.0 | ++ | ++ |
38 | 40 | 10.60 | −3.7 | +++ | +++ | 87 | 1400 | 552.461 | −2.5 | ++ | ++ |
39 | 50 | 50.85 | 1.0 | +++ | +++ | 88 | 1650 | 1645.71 | −1.0 | ++ | ++ |
40 | 50 | 50.17 | 1.0 | +++ | +++ | 89 | 1650 | 551.849 | −2.9 | ++ | ++ |
41 | 58 | 56.72 | −1.0 | +++ | +++ | 90 | 1700 | 524.94 | −3.2 | ++ | ++ |
42 | 70 | 71.11 | 1.0 | +++ | +++ | 91 | 1800 | 1821.04 | 1.0 | ++ | ++ |
43 | 70 | 70.25 | 1.0 | +++ | +++ | 92 | 1800 | 1776.13 | −1.0 | ++ | ++ |
44 | 77 | 76.65 | −1.0 | +++ | +++ | 93 | 1800 | 1530.73 | −1.1 | ++ | ++ |
45 | 82 | 408.48 | 4.9 | +++ | ++ | 94 | 1900 | 1901.07 | 1.0 | ++ | ++ |
46 | 109 | 517.17 | 4.7 | +++ | ++ | 95 | 1900 | 1876.01 | −1.0 | ++ | ++ |
47 | 110 | 532.07 | 4.8 | +++ | ++ | 96 | 2040 | 2022.46 | −1.0 | + | + |
48 | 130 | 518.66 | 3.9 | +++ | ++ | 97 | 2100 | 2095.67 | −1.0 | + | + |
49 | 130 | 60.13 | −2.1 | +++ | +++ | 98 | 2200 | 1991.66 | −1.1 | + | ++ |
50 | 140 | 140.46 | 1.0 | +++ | +++ | 99 | 2400 | 2386.02 | −1.0 | + | + |
51 | 150 | 514.80 | 3.4 | +++ | ++ | 100 | 2500 | 2594.48 | 1.0 | + | + |
52 | 150 | 149.81 | −1.0 | +++ | +++ | 101 | 2500 | 2373.56 | −1.0 | + | + |
53 | 170 | 531.86 | 3.1 | +++ | ++ | 102 | 2600 | 2653.51 | 1.0 | + | + |
54 | 170 | 520.35 | 3.0 | +++ | ++ | 103 | 2600 | 1980.42 | −1.3 | + | ++ |
55 | 190 | 92.38 | −2.0 | +++ | +++ | 104 | 2700 | 2668.93 | −1.0 | + | + |
56 | 220 | 519.50 | 2.3 | ++ | ++ | 105 | 3000 | 2980.04 | −1.0 | + | + |
57 | 250 | 249.79 | −1.0 | ++ | ++ | 106 | 3100 | 3021.26 | −1.0 | + | + |
58 | 270 | 40.16 | −6.7 | ++ | ++ | 107 | 3200 | 3351.54 | 1.0 | + | + |
59 | 300 | 546.21 | 1.8 | ++ | ++ | 108 | 3300 | 3370.61 | 1.0 | + | + |
60 | 300 | 521.04 | 1.7 | ++ | ++ | 109 | 3300 | 3333.56 | 1.0 | + | + |
61 | 300 | 301.67 | 1.0 | ++ | ++ | 110 | 3300 | 3277.62 | −1.0 | + | + |
62 | 300 | 289.88 | −1.0 | ++ | ++ | 111 | 3700 | 4354.53 | 1.1 | + | + |
63 | 370 | 580.52 | 1.5 | ++ | ++ | 112 | 4000 | 1316.33 | −3.0 | + | ++ |
64 | 380 | 531.50 | 1.3 | ++ | ++ | 113 | 4300 | 4440.06 | 1.0 | + | + |
65 | 400 | 517.75 | 1.2 | ++ | ++ | 114 | 4600 | 3529.94 | −1.3 | + | + |
66 | 400 | 513.35 | 1.2 | ++ | ++ | 115 | 4700 | 4603.40 | −1.0 | + | + |
67 | 430 | 515.92 | 1.2 | ++ | ++ | 116 | 5000 | 5036.50 | 1.0 | + | + |
68 | 430 | 515.00 | 1.1 | ++ | ++ | 117 | 5860 | 2779.37 | −2.1 | + | + |
69 | 430 | 431.38 | 1.0 | ++ | ++ |
Trial No. | Total cost | Fixed cost | RMSD | Correlation (r) |
---|---|---|---|---|
Hypo1 | 89.663 | 75.791 | 1.176 | 0.942 |
Results after randomization | ||||
1 | 114.486 | 77.911 | 1.821 | 0.858 |
2 | 108.259 | 72.031 | 1.796 | 0.863 |
3 | 98.26 | 74.85 | 1.529 | 0.9 |
4 | 113.25 | 77.605 | 1.851 | 0.851 |
5 | 112.27 | 77.909 | 1.729 | 0.874 |
6 | 108.84 | 75.77 | 1.749 | 0.869 |
7 | 141.304 | 78.861 | 2.463 | 0.717 |
8 | 109.86 | 72 | 1.857 | 0.852 |
9 | 112.265 | 77.915 | 1.849 | 0.851 |
10 | 113.941 | 77.584 | 1.774 | 0.867 |
11 | 101.143 | 72.068 | 1.593 | 0.894 |
12 | 116.666 | 74.077 | 1.959 | 0.834 |
13 | 114.356 | 69.48 | 1.97 | 0.834 |
14 | 98.277 | 77.638 | 1.433 | 0.913 |
15 | 108.878 | 72.047 | 1.753 | 0.872 |
16 | 117.228 | 78.041 | 1.961 | 0.831 |
17 | 102.183 | 78.085 | 1.359 | 0.926 |
18 | 113.597 | 77.563 | 1.891 | 0.843 |
19 | 106.121 | 74.044 | 1.706 | 0.876 |
© 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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Arooj, M.; Thangapandian, S.; John, S.; Hwang, S.; Park, J.K.; Lee, K.W. 3D QSAR Pharmacophore Modeling, in Silico Screening, and Density Functional Theory (DFT) Approaches for Identification of Human Chymase Inhibitors. Int. J. Mol. Sci. 2011, 12, 9236-9264. https://doi.org/10.3390/ijms12129236
Arooj M, Thangapandian S, John S, Hwang S, Park JK, Lee KW. 3D QSAR Pharmacophore Modeling, in Silico Screening, and Density Functional Theory (DFT) Approaches for Identification of Human Chymase Inhibitors. International Journal of Molecular Sciences. 2011; 12(12):9236-9264. https://doi.org/10.3390/ijms12129236
Chicago/Turabian StyleArooj, Mahreen, Sundarapandian Thangapandian, Shalini John, Swan Hwang, Jong Keun Park, and Keun Woo Lee. 2011. "3D QSAR Pharmacophore Modeling, in Silico Screening, and Density Functional Theory (DFT) Approaches for Identification of Human Chymase Inhibitors" International Journal of Molecular Sciences 12, no. 12: 9236-9264. https://doi.org/10.3390/ijms12129236