The Spectrum of Design Solutions for Improving the Activity-Selectivity Product of Peptide Antibiotics against Multidrug-Resistant Bacteria and Prostate Cancer PC-3 Cells
Abstract
:1. Introduction
2. Materials and Methods
2.1. Chemicals (Reagents)
2.2. Peptide Design Methods
- (a)
- physicochemical properties of helical peptides based on their sequence:HeliQuest tool [30]:
- (b)
- the probability for a peptide to be an antimicrobial peptide:CAMPR3 artificial intelligence algorithms for predicting AMPs [31]:
- (c)
- the probability for a peptide to be a cell-penetrating peptide:Cell-penetrating peptide (CPP) prediction, according to CPPrex-FL [32] and MLCPP [33] algorithms with respective links http://server.malab.cn/SkipCPP-Pred/Index.html and http://thegleelab.org/MLCPP/MLCPP.html.
- (d)
- the probability for a peptide to be an anticancer peptide:Anticancer probability servers used were that of:
2.3. Bacterial Strains and Antimicrobial Activity Assay
2.4. Cytotoxicity on Cancer Cells and Fibroblasts
2.5. Hemolysis of Human Erythrocytes
3. Results
3.1. Peptide Design
3.2. The Performance Parameters for Ranking Peptides When Antibacterial Activity and Toxicity to Human Erythrocytes are Both Taken into Account
3.3. Activity and Selectivity against Prostate Cancer Cells
4. Discussion
4.1. Effect of Charge and Helical Content on Activity
4.2. Effect of Amphipathic Motifs on Activity
4.3. Specific Advantages of Novel Folds
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Sample Availability: Samples of the compounds are not available from the authors. |
Name [Abbreviation] | A Sequence with Added or Substituted Residues in Bold Font and Underlined | Reference * | Amphipathic Helix Pred. ** | SMIC ¶ Template/Peptide | Anticancer Prediction & | CAMPR3 AMP Pred. All AI Classifiers $ | CPP Prediction # |
---|---|---|---|---|---|---|---|
Trichoplaxin-2 [T2] | HHWRRYARIGFRAVRTVIGK-NH2 | This work | 75% | 138 | 0.65/0.98/0.96 | >0.85 Yes | 0.73/0.88 |
Trichoplaxin-2A [T2R1] | RHHWRRYARIGFRAVRTVIGK-NH2 | This work | 72% | 138/58 | 0.85/0.98/0.96 | >0.87 Yes | 0.73/0.91 |
Adepantin-1A [A1A] | GIKKAVGKALKGLKGLLKALGES-NH2 | This work | 78% | 513/517 | 0.24/0.98/1.0 | >0.91 Yes | 0.93/0.39 |
Pexiganan-L18 [PEXA] | GIGKFLKKAKKFGKAFVLILKK-NH2 | [23] | 77% | 352/435 | 0.82/0.98/1.0 | >0.99 Yes | 0.91/0.75 |
Flexampin [FLEX] | GIKKWVKGVAKGVAKDLAKKIL-NH2 | [22] | 82% | 170/1460 | 0.29/0.98/1.0 | ≥0.99 Yes | 0.74/0.56 |
Zyk-1 [ZYK1] | GIGREIIKKIIKKIGKKIGRII-NH2 | This work | 86% | 180/1098 | 0.43/0.97/0.99 | >0.97 Yes | 0.83/0.64 |
DiPGLa-H [PG2] | KIAKVALKALKIAKVALKAL-NH2 | [24] | 75% | 16/204 | 0.61/0.98/0.99 | >0.48 | 0.94/0.85 |
Kiadin-1 [KIA1] | KIAKVALKALKIAKGALKAL-NH2 | [24] | 80% | 16/251 | 0.61/0.98/0.99 | >0.48 | 0.97/0.86 |
Mapegin [MAPA] | KIGKKILKALKGALKELA-NH2 | This work | 78% | 92/253 | 0.74/0.98/1.0 | >0.59 Yes | 0.95/0.71 |
Polybia-MP1 [MP1] | IDWKKLLDAAKQIL-NH2 | [45] | 50% | 25 | 0.91/0.98/0.95 | >0.78 Yes | 0.57/0.53 |
T2 | T2R1 | A1A | PEXA | FLEX | ZYK1 | PG2 | KIA1 | MAPA | MP1 | |
---|---|---|---|---|---|---|---|---|---|---|
MIC (E. coli ATCC 25922) | 0.5–1 | 1 | 1 | 0.5–1 | 0.25 | 1 | 1.5 | 0.75 | 1–2 | |
MIC (E. coli MG1655) | >32 | 4 | 2 | 4 | 16 | 4 | 16 | 8 | 4 | >32 |
MIC (E. coli clin. isolate) | 8 | 4 | 32 | 4 | 0.5 | 2 | 6 | 12 | 8–16 | |
MIC (P. aerug. ATCC 27853) | 4 | 1 | 64 | 4 | 2 | 16 | 6 | 6 | 32–64 | |
MIC (P. aerug. clin. isolate) | 32 | 8 | >64 | 16 | 2–4 | 16 | 6 | 3 | 32 | |
MIC (K. pneum. ATCC 13883) | 4 | 2 | 4 | 2 | 0.5–1 | 2 | 3 | 3 | 8 | |
MIC (K. pneum. clin. isolate) | 8 | 2–4 | 8 | 4 | 2–4 | 4 | 12 | 12 | 8 | |
MIC (A. baum. ATCC 19606) | 1 | 2 | 2 | 1–2 | 0.5–1 | 2 | 1.5 | 1.5 | 1–2 | |
MIC (A. baum. clin. isolate) | 8 | 8 | 4–8 | 1–2 | 1 | 2 | 1.5–3 | 1.5 | 4 | |
MIC (S. aureus ATCC 29213) | 1 | 0.5 | 1 | 0.5 | 0.25 | 1 | 0.75 | 1 | 0.5 | |
MIC (S. aureus clin. isolate) | 4 | 4 | 4 | 2 | 4 | 2 | 1.5 | 3 | 8 | |
HC10 | 1.4 | 3 | 25 | 1.6 | 6 | 3 | 3 | 3 | 1.7 | 20 |
HC20 | 3 | 25 | 80 | 7 | 25 | 8 | 14 | 6 | 3 | 37 |
HC50 * | 28 | 7000 * | 125 * | 520 * | 1600 * | 29 | 18 | 20 | 20 | 170 |
SIc = HC20/MIC(coli) & | 4 | 25 | 80 | 9.3 | 100 | 8 | 9.3 | 8 | 2 | |
SIa = HC20/MIC(aureus) & | 3 | 50 | 80 | 14 | 100 | 8 | 18.7 | 6 | 6 | |
PEc(20) = SIc/MIC(coli) $ | 5.3 | 25 | 80 | 12.4 | 400 | 8 | 3.1 | 10.7 | 1.3 | |
PEa(20) = SI/MIC(aureus) $ | 3 | 100 | 80 | 24.9 | 400 | 8 | 24.9 | 6 | 12 |
T2 | T2R1 | A1A | PEXA | FLEX | ZYK1 | PG2 | KIA1 | MAPA | MP1 | |
---|---|---|---|---|---|---|---|---|---|---|
IC50F (Fibroblasts) | 35 | 80 | 30 | 12 | 30 | 10 | 10 | 15 | 25 | 150 |
IC50C (PC-3) | 10 | 8 | 12 | 4 | 6.25 | 1.5 | 6 | 15 | 8 | 60 |
TI (IC50F/IC50C) | 3.5 | 10 | 2.5 | 3 | 4.8 | 6.7 | 1.7 | 1.0 | 3.1 | 2.5 |
TI (HC20/IC20C) | 1 | 5 | 27 | 6.7 | 25 | 8.6 | 6 | 1 | 1 | 1 |
TI/ IC50C | 0.35 | 1.25 | 0.21 | 0.75 | 0.77 | 4.47 | 0.28 | 0.07 | 0.39 | 0.04 |
(TI/ IC50C) vs. MP1 * | 8.4 | 30 | 5 | 18 | 18.5 | 107 | 6.8 | 1.6 | 9.3 | 1.0 |
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Juretić, D.; Golemac, A.; Strand, D.E.; Chung, K.; Ilić, N.; Goić-Barišić, I.; Pellay, F.-X. The Spectrum of Design Solutions for Improving the Activity-Selectivity Product of Peptide Antibiotics against Multidrug-Resistant Bacteria and Prostate Cancer PC-3 Cells. Molecules 2020, 25, 3526. https://doi.org/10.3390/molecules25153526
Juretić D, Golemac A, Strand DE, Chung K, Ilić N, Goić-Barišić I, Pellay F-X. The Spectrum of Design Solutions for Improving the Activity-Selectivity Product of Peptide Antibiotics against Multidrug-Resistant Bacteria and Prostate Cancer PC-3 Cells. Molecules. 2020; 25(15):3526. https://doi.org/10.3390/molecules25153526
Chicago/Turabian StyleJuretić, Davor, Anja Golemac, Denise E. Strand, Keshi Chung, Nada Ilić, Ivana Goić-Barišić, and François-Xavier Pellay. 2020. "The Spectrum of Design Solutions for Improving the Activity-Selectivity Product of Peptide Antibiotics against Multidrug-Resistant Bacteria and Prostate Cancer PC-3 Cells" Molecules 25, no. 15: 3526. https://doi.org/10.3390/molecules25153526