參考文獻 |
1. US CDC. Antibiotic Resistance Threats in the United States. http://www.cdc.gov/drugresistance/threat-report-2013/.
2. McKenna, M., Antibiotic resistance: the last resort. Nature 2013, 499 (7459), 394-6.
3. Zasloff, M., Magainins, a class of antimicrobial peptides from Xenopus skin: isolation, characterization of two active forms, and partial cDNA sequence of a precursor. Proc Natl Acad Sci U S A 1987, 84 (15), 5449-53.
4. Mookherjee, N.; Anderson, M. A.; Haagsman, H. P.; Davidson, D. J., Antimicrobial host defence peptides: functions and clinical potential. Nat Rev Drug Discov 2020, 19 (5), 311-332.
5. Huan, Y.; Kong, Q.; Mou, H.; Yi, H., Antimicrobial Peptides: Classification, Design, Application and Research Progress in Multiple Fields. Front Microbiol 2020, 11, 582779.
6. Pirtskhalava, M.; Vishnepolsky, B.; Grigolava, M.; Managadze, G., Physicochemical Features and Peculiarities of Interaction of AMP with the Membrane. Pharmaceuticals (Basel) 2021, 14 (5).
7. Waghu, F. H.; Barai, R. S.; Gurung, P.; Idicula-Thomas, S., CAMPR3: a database on sequences, structures and signatures of antimicrobial peptides. Nucleic Acids Res 2016, 44 (D1), D1094-7.
8. Wang, G.; Li, X.; Wang, Z., APD3: the antimicrobial peptide database as a tool for research and education. Nucleic Acids Res 2016, 44 (D1), D1087-93.
9. Pirtskhalava, M.; Amstrong, A. A.; Grigolava, M.; Chubinidze, M.; Alimbarashvili, E.; Vishnepolsky, B.; Gabrielian, A.; Rosenthal, A.; Hurt, D. E.; Tartakovsky, M., DBAASP v3: database of antimicrobial/cytotoxic activity and structure of peptides as a resource for development of new therapeutics. Nucleic Acids Research 2021, 49 (D1), D288-D297.
10. Chen, C. H.; Starr, C. G.; Troendle, E.; Wiedman, G.; Wimley, W. C.; Ulmschneider, J. P.; Ulmschneider, M. B., Simulation-Guided Rational de Novo Design of a Small Pore-Forming Antimicrobial Peptide. Journal of the American Chemical Society 2019, 141 (12), 4839-4848.
11. Brogden, K. A., Antimicrobial peptides: pore formers or metabolic inhibitors in bacteria? Nat Rev Microbiol 2005, 3 (3), 238-50.
12. Epand, R. M.; Vogel, H. J., Diversity of antimicrobial peptides and their mechanisms of action. Biochimica et Biophysica Acta (BBA) - Biomembranes 1999, 1462 (1-2), 11-28.
13. Bechinger, B., The structure, dynamics and orientation of antimicrobial peptides in membranes by multidimensional solid-state NMR spectroscopy. Biochim Biophys Acta 1999, 1462 (1-2), 157-83.
14. Vishnepolsky, B.; Gabrielian, A.; Rosenthal, A.; Hurt, D. E.; Tartakovsky, M.; Managadze, G.; Grigolava, M.; Makhatadze, G. I.; Pirtskhalava, M., Predictive Model of Linear Antimicrobial Peptides Active against Gram-Negative Bacteria. J Chem Inf Model 2018, 58 (5), 1141-1151.
15. Lee, E. Y.; Fulan, B. M.; Wong, G. C. L.; Ferguson, A. L., Mapping membrane activity in undiscovered peptide sequence space using machine learning. Proceedings of the National Academy of Sciences 2016, 113 (48), 13588-13593.
16. Veltri, D.; Kamath, U.; Shehu, A., Deep learning improves antimicrobial peptide recognition. Bioinformatics 2018, 34 (16), 2740-2747.
17. Chen, Y.; Guarnieri, M. T.; Vasil, A. I.; Vasil, M. L.; Mant, C. T.; Hodges, R. S., Role of peptide hydrophobicity in the mechanism of action of alpha-helical antimicrobial peptides. Antimicrob Agents Chemother 2007, 51 (4), 1398-406.
18. Jiang, Z. Q.; Vasil, A. I.; Gera, L.; Vasil, M. L.; Hodges, R. S., Rational Design of alpha-Helical Antimicrobial Peptides to Target Gram-negative Pathogens, Acinetobacter baumannii and Pseudomonas aeruginosa: Utilization of Charge, ′Specificity Determinants,′ Total Hydrophobicity, Hydrophobe Type and Location as Design Parameters to Improve the Therapeutic Ratio. Chem Biol Drug Des 2011, 77 (4), 225-240.
19. Yin, L. M.; Edwards, M. A.; Li, J.; Yip, C. M.; Deber, C. M., Roles of hydrophobicity and charge distribution of cationic antimicrobial peptides in peptide-membrane interactions. J Biol Chem 2012, 287 (10), 7738-45.
20. Deslouches, B.; Steckbeck, J. D.; Craigo, J. K.; Doi, Y.; Mietzner, T. A.; Montelaro, R. C., Rational Design of Engineered Cationic Antimicrobial Peptides Consisting Exclusively of Arginine and Tryptophan, and Their Activity against Multidrug-Resistant Pathogens. Antimicrob Agents Ch 2013, 57 (6), 2511-2521.
21. Deslouches, B.; Phadke, S. M.; Lazarevic, V.; Cascio, M.; Islam, K.; Montelaro, R. C.; Mietzner, T. A., De novo generation of cationic antimicrobial peptides: influence of length and tryptophan substitution on antimicrobial activity. Antimicrob Agents Chemother 2005, 49 (1), 316-22.
22. Elliott, A. G.; Huang, J. X.; Neve, S.; Zuegg, J.; Edwards, I. A.; Cain, A. K.; Boinett, C. J.; Barquist, L.; Lundberg, C. V.; Steen, J.; Butler, M. S.; Mobli, M.; Porter, K. M.; Blaskovich, M. A. T.; Lociuro, S.; Strandh, M.; Cooper, M. A., An amphipathic peptide with antibiotic activity against multidrug-resistant Gram-negative bacteria. Nat Commun 2020, 11 (1).
23. Craven, T. W.; Cho, M. K.; Traaseth, N. J.; Bonneau, R.; Kirshenbaum, K., A Miniature Protein Stabilized by a Cation-pi Interaction Network. J Am Chem Soc 2016, 138 (5), 1543-50.
24. Zhong, W.; Gallivan, J. P.; Zhang, Y.; Li, L.; Lester, H. A.; Dougherty, D. A., From ab initio quantum mechanics to molecular neurobiology: a cation-pi binding site in the nicotinic receptor. Proc Natl Acad Sci U S A 1998, 95 (21), 12088-93.
25. Pless, S. A.; Millen, K. S.; Hanek, A. P.; Lynch, J. W.; Lester, H. A.; Lummis, S. C. R.; Dougherty, D. A., A Cation-pi Interaction in the Binding Site of the Glycine Receptor Is Mediated by a Phenylalanine Residue. J Neurosci 2008, 28 (43), 10937-10942.
26. Lolicato, M.; Arrigoni, C.; Mori, T.; Sekioka, Y.; Bryant, C.; Clark, K. A.; Minor, D. L., Jr., K2P2.1 (TREK-1)-activator complexes reveal a cryptic selectivity filter binding site. Nature 2017, 547 (7663), 364-368.
27. Yen, T. J.; Lolicato, M.; Thomas-Tran, R.; Du Bois, J.; Minor, D. L., Jr., Structure of the saxiphilin:saxitoxin (STX) complex reveals a convergent molecular recognition strategy for paralytic toxins. Sci Adv 2019, 5 (6), eaax2650.
28. Waheed, Q.; Khan, H. M.; He, T.; Roberts, M.; Gershenson, A.; Reuter, N., Interfacial Aromatics Mediating Cation-pi Interactions with Choline-Containing Lipids Can Contribute as Much to Peripheral Protein Affinity for Membranes as Aromatics Inserted below the Phosphates. J Phys Chem Lett 2019, 10 (14), 3972-3977.
29. Petersen, F. N.; Jensen, M. O.; Nielsen, C. H., Interfacial tryptophan residues: a role for the cation-pi effect? Biophys J 2005, 89 (6), 3985-96.
30. Hirano, Y.; Gao, Y. G.; Stephenson, D. J.; Vu, N. T.; Malinina, L.; Simanshu, D. K.; Chalfant, C. E.; Patel, D. J.; Brown, R. E., Structural basis of phosphatidylcholine recognition by the C2-domain of cytosolic phospholipase A2alpha. Elife 2019, 8, e44760.
31. Goh, B. C.; Wu, H.; Rynkiewicz, M. J.; Schulten, K.; Seaton, B. A.; McCormack, F. X., Elucidation of Lipid Binding Sites on Lung Surfactant Protein A Using X-ray Crystallography, Mutagenesis, and Molecular Dynamics Simulations. Biochemistry 2016, 55 (26), 3692-701.
32. Weber, D. K.; Yao, S.; Rojko, N.; Anderluh, G.; Lybrand, T. P.; Downton, M. T.; Wagner, J.; Separovic, F., Characterization of the Lipid-Binding Site of Equinatoxin II by NMR and Molecular Dynamics Simulation. Biophys J 2015, 108 (8), 1987-96.
33. Broemstrup, T.; Reuter, N., How does proteinase 3 interact with lipid bilayers? Phys Chem Chem Phys 2010, 12 (27), 7487-96.
34. Roberts, M. F.; Khan, H. M.; Goldstein, R.; Reuter, N.; Gershenson, A., Search and Subvert: Minimalist Bacterial Phosphatidylinositol-Specific Phospholipase C Enzymes. Chem Rev 2018, 118 (18), 8435-8473.
35. Yang, B.; Pu, M.; Khan, H. M.; Friedman, L.; Reuter, N.; Roberts, M. F.; Gershenson, A., Quantifying transient interactions between Bacillus phosphatidylinositol-specific phospholipase-C and phosphatidylcholine-rich vesicles. J Am Chem Soc 2015, 137 (1), 14-7.
36. Grauffel, C.; Yang, B.; He, T.; Roberts, M. F.; Gershenson, A.; Reuter, N., Cation−π Interactions As Lipid-Specific Anchors for Phosphatidylinositol-Specific Phospholipase C. Journal of the American Chemical Society 2013, 135 (15), 5740-5750.
37. Grauffel, C.; Yang, B.; He, T.; Roberts, M. F.; Gershenson, A.; Reuter, N., Cation-pi interactions as lipid-specific anchors for phosphatidylinositol-specific phospholipase C. J Am Chem Soc 2013, 135 (15), 5740-50.
38. Gaede, H. C.; Yau, W. M.; Gawrisch, K., Electrostatic contributions to indole-lipid interactions. J Phys Chem B 2005, 109 (26), 13014-23.
39. Yau, W. M.; Wimley, W. C.; Gawrisch, K.; White, S. H., The preference of tryptophan for membrane interfaces. Biochemistry 1998, 37 (42), 14713-8.
40. Blaser, G.; Sanderson, J. M.; Wilson, M. R., Free-energy relationships for the interactions of tryptophan with phosphocholines. Org Biomol Chem 2009, 7 (24), 5119-28.
41. Chakrapani, N.; Nigam, A.; Shanthi, V.; Sethumadhavan, R.; Ramanathan, K., Computational Investigation of Cation-<I>π</I> Interactions in the Structural Stability of Antimicrobial Peptides. Journal of Bioinformatics and Intelligent Control 2013, 2 (1), 34-39.
42. Spodsberg, N. Polypeptides having antimicrobial activity and polynucleotides encoding same. WO 2007/023163 A1, 2007.
43. Liu, H.; Fu, H.; Shao, X.; Cai, W.; Chipot, C., Accurate Description of Cation−π Interactions in Proteins with a Nonpolarizable Force Field at No Additional Cost. Journal of Chemical Theory and Computation 2020, 16 (10), 6397-6407.
44. Jo, S.; Kim, T.; Iyer, V. G.; Im, W., CHARMM-GUI: A web-based graphical user interface for CHARMM. Journal of Computational Chemistry 2008, 29 (11), 1859-1865.
45. Wu, E. L.; Cheng, X.; Jo, S.; Rui, H.; Song, K. C.; Dávila-Contreras, E. M.; Qi, Y.; Lee, J.; Monje-Galvan, V.; Venable, R. M.; Klauda, J. B.; Im, W., CHARMM-GUI Membrane Builder toward realistic biological membrane simulations. Journal of Computational Chemistry 2014, 35 (27), 1997-2004.
46. Phillips, J. C.; Hardy, D. J.; Maia, J. D. C.; Stone, J. E.; Ribeiro, J. V.; Bernardi, R. C.; Buch, R.; Fiorin, G.; Hénin, J.; Jiang, W.; McGreevy, R.; Melo, M. C. R.; Radak, B. K.; Skeel, R. D.; Singharoy, A.; Wang, Y.; Roux, B.; Aksimentiev, A.; Luthey-Schulten, Z.; Kalé, L. V.; Schulten, K.; Chipot, C.; Tajkhorshid, E., Scalable molecular dynamics on CPU and GPU architectures with NAMD. The Journal of Chemical Physics 2020, 153 (4), 044130.
47. Huang, J.; MacKerell Jr, A. D., CHARMM36 all-atom additive protein force field: Validation based on comparison to NMR data. Journal of Computational Chemistry 2013, 34 (25), 2135-2145.
48. Jorgensen, W. L.; Chandrasekhar, J.; Madura, J. D.; Impey, R. W.; Klein, M. L., Comparison of simple potential functions for simulating liquid water. The Journal of Chemical Physics 1983, 79 (2), 926-935.
49. Feller, S. E.; Zhang, Y.; Pastor, R. W.; Brooks, B. R., Constant pressure molecular dynamics simulation: The Langevin piston method. The Journal of Chemical Physics 1995, 103 (11), 4613-4621.
50. P.Valleau, G. M. T., Monte Carlo free energy estimates using non-Boltzmann sampling: Application to the sub-critical Lennard-Jones fluid. Chemical Physics Letters 1974.
51. G.M.TorrieJ.P.Valleau, Nonphysical sampling distributions in Monte Carlo free-energy estimation: Umbrella sampling. Journal of Computational Physics 1977.
52. Edwards, I. A. β-hairpin antimicrobial peptides: structure, function and mode of action. The University of Queensland, 2018.
53. Sgrignani, J.; Magistrato, A., QM/MM MD Simulations on the Enzymatic Pathway of the Human Flap Endonuclease (hFEN1) Elucidating Common Cleavage Pathways to RNase H Enzymes. ACS Catalysis 2015, 5 (6), 3864-3875.
54. Voice, A. T.; Tresadern, G.; Twidale, R. M.; van Vlijmen, H.; Mulholland, A. J., Mechanism of covalent binding of ibrutinib to Bruton′s tyrosine kinase revealed by QM/MM calculations. Chem Sci 2021, 12 (15), 5511-5516.
55. Kästner, J., Umbrella sampling. WIREs Computational Molecular Science 2011, 1 (6), 932-942.
56. ROSENBERG, S. K. a. J. M., Mu1 t i dimensional Fr e e - Ene r gy Calculations Using the Weighted Histogram Analysis Method. Journal of Computational Chemistry 1995.
57. Gapsys, V.; de Groot, B. L.; Briones, R., Computational analysis of local membrane properties. Journal of Computer-Aided Molecular Design 2013, 27 (10), 845-858.
58. Infield, D. T.; Rasouli, A.; Galles, G. D.; Chipot, C.; Tajkhorshid, E.; Ahern, C. A., Cation-pi Interactions and their Functional Roles in Membrane Proteins. J Mol Biol 2021, 433 (17), 167035.
59. Humphrey, W.; Dalke, A.; Schulten, K., VMD: Visual molecular dynamics. Journal of Molecular Graphics 1996, 14 (1), 33-38.
60. Matsuzaki, K., Magainins as paradigm for the mode of action of pore forming polypeptides. Bba-Rev Biomembranes 1998, 1376 (3), 391-400.
61. Imura, Y.; Choda, N.; Matsuzaki, K., Magainin 2 in action: distinct modes of membrane permeabilization in living bacterial and mammalian cells. Biophys J 2008, 95 (12), 5757-65.
62. Bylund, J.; Christophe, T.; Boulay, F.; Nyström, T.; Karlsson, A.; Dahlgren, C., Proinflammatory activity of a cecropin-like antibacterial peptide from Helicobacter pylori. Antimicrob Agents Chemother 2001, 45 (6), 1700-4.
63. Lin, F.-Y.; MacKerell Jr, A. D., Improved Modeling of Cation-π and Anion-Ring Interactions Using the Drude Polarizable Empirical Force Field for Proteins. Journal of Computational Chemistry 2020, 41 (5), 439-448.
64. Khan, H. M.; Grauffel, C.; Broer, R.; MacKerell, A. D.; Havenith, R. W. A.; Reuter, N., Improving the Force Field Description of Tyrosine–Choline Cation−π Interactions: QM Investigation of Phenol–N(Me)4+ Interactions. Journal of Chemical Theory and Computation 2016, 12 (11), 5585-5595.
65. Turupcu, A.; Tirado-Rives, J.; Jorgensen, W. L., Explicit Representation of Cation−π Interactions in Force Fields with 1/r4 Nonbonded Terms. Journal of Chemical Theory and Computation 2020, 16 (11), 7184-7194.
66. Wu, J. M.; Wei, S. Y.; Chen, H. L.; Weng, K. Y.; Cheng, H. T.; Cheng, J. W., Solution structure of a novel D-naphthylalanine substituted peptide with potential antibacterial and antifungal activities. Biopolymers 2007, 88 (5), 738-45.
67. Haug, B. E.; Skar, M. L.; Svendsen, J. S., Bulky aromatic amino acids increase the antibacterial activity of 15-residue bovine lactoferricin derivatives. J Pept Sci 2001, 7 (8), 425-32.
68. Cheng, K. T.; Wu, C. L.; Yip, B. S.; Chih, Y. H.; Peng, K. L.; Hsu, S. Y.; Yu, H. Y.; Cheng, J. W., The Interactions between the Antimicrobial Peptide P-113 and Living Candida albicans Cells Shed Light on Mechanisms of Antifungal Activity and Resistance. Int J Mol Sci 2020, 21 (7).
69. Davis, M. R.; Dougherty, D. A., Cation-pi interactions: computational analyses of the aromatic box motif and the fluorination strategy for experimental evaluation. Phys Chem Chem Phys 2015, 17 (43), 29262-70.
70. Dougherty, D. A., The cation-pi interaction. Acc Chem Res 2013, 46 (4), 885-93.
71. Cheng, J.; Goldstein, R.; Gershenson, A.; Stec, B.; Roberts, M. F., The cation-pi box is a specific phosphatidylcholine membrane targeting motif. J Biol Chem 2013, 288 (21), 14863-73.
72. Nagarajan, D.; Roy, N.; Kulkarni, O.; Nanajkar, N.; Datey, A.; Ravichandran, S.; Thakur, C.; T, S.; Aprameya, I. V.; Sarma, S. P.; Chakravortty, D.; Chandra, N., Omega76: A designed antimicrobial peptide to combat carbapenem- and tigecycline-resistant Acinetobacter baumannii. Sci Adv 2019, 5 (7), eaax1946.
73. Tsai, C.-Y.; Salawu, E. O.; Li, H.; Lin, G.-Y.; Kuo, T.-Y.; Voon, L.; Sharma, A.; Hu, K.-D.; Cheng, Y.-Y.; Sahoo, S.; Stuart, L.; Chen, C.-W.; Chang, Y.-Y.; Lu, Y.-L.; Ke, S.; Ortiz, C. L. D.; Fang, B.-S.; Wu, C.-C.; Lan, C.-Y.; Fu, H.-W.; Yang, L.-W., Helical structure motifs made searchable for functional peptide design. Nat Commun 2022, 13 (1), 102. |