Discovery of Potential Plant-Derived Peptide Deformylase (PDF) Inhibitors for Multidrug-Resistant Bacteria Using Computational Studies
Abstract
:1. Introduction
2. Experimental Section
2.1. Ligand-Based Approach
2.1.1. Dataset Construction and Its Composition
2.1.2. Generation of the Pharmacophore Model
2.2. Generation of the Receptor-Based Pharmacophore Model
2.3. Validation of the Pharmacophore Models
2.3.1. Ligand-Based Pharmacophore Model Validation
2.3.2. Receptor-Based Pharmacophore Model Validation
2.3.3. Decoy Set Method of Validation
2.4. Virtual Screening of the TIP Database
2.5. Drug-Like Assessment
2.6. Molecular Docking Studies
2.7. Molecular Dynamics Simulation Studies
2.8. Novelty Assessment of the Compounds
3. Results
3.1. Generation of the Pharmacophore Model
3.1.1. Ligand-Based Pharmacophore Generation
3.1.2. Generation of Structure-Based Pharmacophore Generation
3.2. Validation of the Pharmacophore Models
3.2.1 Validation of PharmL
Fischer’s Randomization Method
Test Set Method
3.2.2. Validation of PharmR
Receiver Operating Characteristic (ROC) Plot Analysis
Decoy Set Method of Validation for PharmL and PharmR
3.3. Virtual Screening of Taiwan Indigenous Plants (TIP) Database
3.4. Molecular Docking-Based Screening
3.5. Molecular Dynamics Simulations
3.6. Probing the Novelty of the Hits
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
References
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Hypo Number | Total Cost | Cost Difference a | RMSD | Correlation | Features b | Maximum Fit |
---|---|---|---|---|---|---|
Hypo1 | 127.67 | 113.10 | 1.77 | 0.90 | 2HBA, HBD, HyP | 13.23 |
Hypo2 | 131.722 | 109.06 | 2.06 | 0.86 | 2HBA, HyP, HyP, HyP | 13.34 |
Hypo3 | 132.165 | 108.62 | 1.94 | 0.88 | 2HBA, HBD, HyP | 12.71 |
Hypo4 | 133.398 | 107.38 | 2.00 | 0.87 | 2HBA, HBD, HyP | 12.27 |
Hypo5 | 133.808 | 106.97 | 2.14 | 0.85 | 2HBA, HyP, HyP, HyP | 12.08 |
Hypo6 | 133.895 | 106.89 | 1.87 | 0.89 | 2HBA, HBD, HyP | 13.88 |
Hypo7 | 135.009 | 105.77 | 2.09 | 0.86 | 2HBA, HBD, HyP | 11.53 |
Hypo8 | 135.104 | 105.68 | 2.17 | 0.85 | 2HBD, HyP, HyP, HyP | 12.29 |
Hypo9 | 135.444 | 105.34 | 1.97 | 0.88 | 2HBA, HBD, HyP | 13.30 |
Hypo10 | 135.564 | 105.22 | 2.01 | 0.87 | 2HBA, HBD, HyP | 12.91 |
Name | Fit | IC50 (nmol/L) | RMSE a | Activity Scale | ||
---|---|---|---|---|---|---|
Experimental | Predicted | Experimental | Predicted | |||
C1 | 13.03 | 0.1 | 0.55 | 5.5 | +++ | +++ |
C2 | 12.29 | 0.3 | 3 | 10 | +++ | +++ |
C3 | 12.99 | 0.41 | 0.61 | 1.5 | +++ | +++ |
C4 | 12.98 | 0.5 | 0.62 | 1.2 | +++ | +++ |
C5 | 12.72 | 1 | 1.1 | 1.1 | +++ | +++ |
C6 | 12.54 | 2.1 | 1.7 | −1.2 | +++ | +++ |
C7 | 12.72 | 8 | 1.1 | −7 | +++ | +++ |
C8 | 11.44 | 15 | 22 | 1.4 | +++ | +++ |
C9 | 11.16 | 30 | 41 | 1.4 | +++ | +++ |
C10 | 10.24 | 52 | 350 | 6.6 | +++ | +++ |
C11 | 9.5 | 74 | 190 | 6 | +++ | +++ |
C12 | 9.46 | 300 | 2100 | 6.9 | +++ | ++ |
C13 | 9.66 | 430 | 130 | 3 | +++ | +++ |
C14 | 9.32 | 800 | 2800 | 3.5 | ++ | ++ |
C15 | 9.61 | 3000 | 1400 | −2.1 | ++ | ++ |
C16 | 9.97 | 7400 | 630 | −12 | ++ | ++ |
C17 | 8.07 | 28,000 | 51,000 | 1.8 | + | + |
C18 | 9.65 | 54,000 | 1300 | −40 | + | ++ |
C19 | 8.79 | 100,000 | 9600 | −10 | + | ++ |
C20 | 8.8 | 560,000 | 9400 | −6.0 | + | ++ |
Pharmacophore | Number of Features | Feature Set | Selectivity Score |
---|---|---|---|
Pharmacophore_1 | 6 | HBA, HBD, HBD, HyP, HyP, HyP | 11.498 |
Pharmacophore_2 | 6 | HBA, HBD, HBD, HyP, HyP, HyP | 11.498 |
Pharmacophore_3 | 6 | HBA, HBD, HBD, HyP, HyP, HyP | 11.498 |
Pharmacophore_4 | 6 | HBA, HBD, HBD, HyP, HyP, HyP | 11.498 |
Pharmacophore_5 | 6 | HBA, HBD, HBD, HyP, HyP, HyP | 11.498 |
Pharmacophore_6 | 6 | HBA, HBD, HBD, HyP, HyP, HyP | 11.498 |
Pharmacophore_7 | 6 | HBA, HBD, HBD, HyP, HyP, HyP | 11.498 |
Pharmacophore_8 | 6 | HBA, HBD, HBD, HyP, HyP, HyP | 11.498 |
Pharmacophore_9 | 6 | HBA, HBD, HBD, HyP, HyP, HyP | 11.498 |
Pharmacophore_10 | 6 | HBA, HBD, HBD, HyP, HyP, HyP | 11.498 |
Model Number | RMSD |
---|---|
1 | 1.41 |
2 | 1.63 |
3 | 1.87 |
4 | 2.03 |
5 | 2.11 |
6 | 2.14 |
7 | 2.47 |
8 | 2.92 |
9 | 2.94 |
10 | 2.99 |
Name | Fit | IC50 (nmol/L) | RMSE a | Activity Scale | ||
---|---|---|---|---|---|---|
Experimental | Predicted | Experimental | Predicted | |||
C1 | 13.21 | 0.19 | 0.45 | 2.3 | +++ | +++ |
C2 | 13.21 | 0.19 | 0.45 | 2.3 | +++ | +++ |
C3 | 12.9 | 0.22 | 0.92 | 4.2 | +++ | +++ |
C4 | 13.07 | 0.31 | 0.61 | 2 | +++ | +++ |
C5 | 12.15 | 3 | 5.1 | 1.7 | +++ | +++ |
C6 | 13.07 | 4.4 | 0.62 | −7.1 | +++ | +++ |
C7 | 11.54 | 7 | 21 | 3 | +++ | +++ |
C8 | 11.81 | 10 | 11 | 1.1 | +++ | +++ |
C9 | 10.95 | 16 | 81 | 5.1 | +++ | +++ |
C10 | 11.64 | 20 | 17 | −1.2 | +++ | +++ |
C11 | 11.54 | 40 | 21 | −1.9 | +++ | +++ |
C12 | 10.14 | 64 | 520 | 8.1 | +++ | +++ |
C13 | 10.81 | 100 | 98 | 1.1 | +++ | +++ |
C14 | 10.75 | 120 | 130 | 1.1 | ++ | ++ |
C15 | 10.02 | 170 | 690 | 4.1 | ++ | ++ |
C16 | 9.7 | 180 | 1400 | 8.2 | ++ | ++ |
C17 | 10.11 | 290 | 560 | 1.9 | ++ | ++ |
C18 | 9.43 | 330 | 2700 | 8.1 | ++ | ++ |
C19 | 10.01 | 590 | 700 | 1.2 | ++ | ++ |
C20 | 9.7 | 1000 | 1400 | 1.4 | ++ | ++ |
C21 | 9.86 | 1400 | 990 | −1.4 | ++ | ++ |
C22 | 9.88 | 2200 | 950 | −2.3 | ++ | ++ |
C23 | 8.89 | 4100 | 9200 | 2.2 | ++ | ++ |
C24 | 8.92 | 7500 | 8600 | 1.1 | ++ | ++ |
C25 | 8.39 | 21,000 | 29,000 | 1.4 | + | + |
C26 | 8.36 | 34,000 | 32,000 | −1.1 | + | + |
C27 | 9.36 | 61,000 | 31,000 | 2.0 | + | + |
C28 | 9.48 | 80,000 | 24,000 | 3.4 | + | + |
C29 | 9.57 | 100,000 | 1900 | −52 | + | ++ |
C30 | 8.95 | 200,000 | 8100 | −25 | + | ++ |
C31 | 7.18 | 380,000 | 480,000 | 1.3 | + | + |
Parameters | PharmL | PharmR |
---|---|---|
Total number of molecules in database (D) | 1000 | 1000 |
Total number of actives in database (A) | 20 | 20 |
Total number of hit molecules (Ht) | 25 | 24 |
Total number of active molecules (Ha) | 19 | 20 |
% Yield of active ((Ha/Ht) × 100) | 76.0 | 83.3 |
% Ratio of actives ((Ha/A) × 100) | 95 | 100 |
Enrichment factor (EF) | 38.0 | 41.5 |
False negatives (A-Ha) | 1 | 0 |
False positives (Ht–Ha) | 5 | 4 |
Goodness of fit score (GF) | 0.79 | 0.83 |
Name | Hydrogen Bond (<3 Å) | Alkyl/π- alkyl | Van der Waals Interactions |
---|---|---|---|
Ref | Arg56: HH21-O5 (2.7) Leu112: HN-O24 (2.9) Asn117: HD22-O5 (2.8) Asn117: OD1-H35 (2.1) | Val59, Val151, His159 | Ser57, Gly58, Gly60, Leu105, Gly108, Glu109, CDS111, Tyr147, Glu155, Glu185 |
Hit1 | Ser57: HG-O17 (2.1) Gln65: HE22-O23 (1.8) Gly108: O-H49 (2.4) Leu112: HN-O23 (2.6) | - | Gly58, Val59, Leu61, Leu105, Thr107, Glu109, CSD111, Ile150, Val151, His154, Glu185 His186 |
Hit2 | Ser57: HG-O16 (2.7) Val59: HN1-O23 (1.8) Gly60: O-H44 (1.7) | Val151 | Arg56, Gly58, Gln65, Leu61, Leu105, Gly108, Glu109, CDS111, Leu112, Arg124, Tyr147, Ile150, Glu155, Glu185 |
Hit3 | Val59: HN-O22 (2.9) Gly60: O-H50 (1.8) Gly110: O-H46 (1.8) Tyr147: HH-O1 (2.1) | Val59 | Leu41, Arg56, Ser57, Gly58, Leu61, Gln65, Pro78, Ile77, Glu109, Gly110, CSD111, Leu112, Ile150, His154, His158, Glu185 |
Compound Name | -CDOCKER Energy | -CDOCKER Interaction Energy | GoldScore | ChemScore |
---|---|---|---|---|
Reference1 | 4.00 | 46.42 | 42.86 | –19.68 |
Actinonin | 29.12 | 45.94 | 41.05 | –18.56 |
Hit1 | 30.66 | 51.11 | 51.29 | –26.55 |
Hit2 | 30.76 | 50.13 | 48.55 | –27.00 |
Hit3 | 21.78 | 47.32 | 55.33 | –28.97 |
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Rampogu, S.; Zeb, A.; Baek, A.; Park, C.; Son, M.; Lee, K.W. Discovery of Potential Plant-Derived Peptide Deformylase (PDF) Inhibitors for Multidrug-Resistant Bacteria Using Computational Studies. J. Clin. Med. 2018, 7, 563. https://doi.org/10.3390/jcm7120563
Rampogu S, Zeb A, Baek A, Park C, Son M, Lee KW. Discovery of Potential Plant-Derived Peptide Deformylase (PDF) Inhibitors for Multidrug-Resistant Bacteria Using Computational Studies. Journal of Clinical Medicine. 2018; 7(12):563. https://doi.org/10.3390/jcm7120563
Chicago/Turabian StyleRampogu, Shailima, Amir Zeb, Ayoung Baek, Chanin Park, Minky Son, and Keun Woo Lee. 2018. "Discovery of Potential Plant-Derived Peptide Deformylase (PDF) Inhibitors for Multidrug-Resistant Bacteria Using Computational Studies" Journal of Clinical Medicine 7, no. 12: 563. https://doi.org/10.3390/jcm7120563