Design methods for antimicrobial peptides with improved performance

James Mwangi; Peter Muiruri Kamau; Rebecca Caroline Thuku; Ren Lai

doi:10.24272/j.issn.2095-8137.2023.246

Volume 44 Issue 6

Nov. 2023

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James Mwangi, Peter Muiruri Kamau, Rebecca Caroline Thuku, Ren Lai. Design methods for antimicrobial peptides with improved performance. Zoological Research, 2023, 44(6): 1095-1114. doi: 10.24272/j.issn.2095-8137.2023.246

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James Mwangi, Peter Muiruri Kamau, Rebecca Caroline Thuku, Ren Lai. Design methods for antimicrobial peptides with improved performance. Zoological Research, 2023, 44(6): 1095-1114. doi: 10.24272/j.issn.2095-8137.2023.246

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Design methods for antimicrobial peptides with improved performance

doi: 10.24272/j.issn.2095-8137.2023.246

James Mwangi^{1, 3},
Peter Muiruri Kamau^{1, 3},
Rebecca Caroline Thuku^{1, 3},
Ren Lai^{1, 2
,
,}

1.
Key Laboratory of Bioactive Peptides of Yunnan Province, Engineering Laboratory of Peptides of Chinese Academy of Sciences, KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, National Resource Centre for Non-Human Primates, Kunming Primate Research Centre, National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Sino-African Joint Research Centre, New Cornerstone Science Institute, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650107, China
2.
Centre for Evolution and Conservation Biology, Southern Marine Science and Engineering Guangdong Laboratory, Guangzhou, Guangdong 511458, China
3.
Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan 650204, China

The authors declare that they have no competing interests.
J.M., P.M.K., and R.C.T. prepared and wrote the manuscript. R.L. reviewed and edited the manuscript. All authors read and approved the final version of the manuscript.

Funds: This work was supported by the National Natural Science Foundation of China (31930015, 32200397), Ministry of Science and Technology of China (2018YFA0801403), Chinese Academy of Sciences (XDB31000000, KFJ-BRP-008-003), Yunnan Province Grant (202003AD150008, 202002AA100007), Kunming Science and Technology Bureau (2023SCP001), and New Cornerstone Investigator Program

More Information

Corresponding author: E-mail: rlai@mail.kiz.ac.cn
Received Date: 2023-08-02
Accepted Date: 2023-09-19

Published Online: 2023-09-21

Publish Date: 2023-11-18

Abstract

Abstract

The recalcitrance of pathogens to traditional antibiotics has made treating and eradicating bacterial infections more difficult. In this regard, developing new antimicrobial agents to combat antibiotic-resistant strains has become a top priority. Antimicrobial peptides (AMPs), a ubiquitous class of naturally occurring compounds with broad-spectrum antipathogenic activity, hold significant promise as an effective solution to the current antimicrobial resistance (AMR) crisis. Several AMPs have been identified and evaluated for their therapeutic application, with many already in the drug development pipeline. Their distinct properties, such as high target specificity, potency, and ability to bypass microbial resistance mechanisms, make AMPs a promising alternative to traditional antibiotics. Nonetheless, several challenges, such as high toxicity, lability to proteolytic degradation, low stability, poor pharmacokinetics, and high production costs, continue to hamper their clinical applicability. Therefore, recent research has focused on optimizing the properties of AMPs to improve their performance. By understanding the physicochemical properties of AMPs that correspond to their activity, such as amphipathicity, hydrophobicity, structural conformation, amino acid distribution, and composition, researchers can design AMPs with desired and improved performance. In this review, we highlight some of the key strategies used to optimize the performance of AMPs, including rational design and de novo synthesis. We also discuss the growing role of predictive computational tools, utilizing artificial intelligence and machine learning, in the design and synthesis of highly efficacious lead drug candidates.
- Antimicrobial resistance,
- Antimicrobial peptides,
- Design methods,
- Peptidomimetics,
- Artificial intelligence

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References(228)

References

[1]	Ahmad A, Akbar S, Khan S, et al. 2021. Deep-AntiFP: prediction of antifungal peptides using distanct multi-informative features incorporating with deep neural networks. Chemometrics and Intelligent Laboratory Systems, 208: 104214. doi: 10.1016/j.chemolab.2020.104214
[2]	Al Musaimi O, Lombardi L, Williams DR, et al. 2022. Strategies for improving peptide stability and delivery. Pharmaceuticals, 15(10): 1283. doi: 10.3390/ph15101283
[3]	Asante V, Mortier J, Wolber G, et al. 2014. Impact of fluorination on proteolytic stability of peptides: a case study with α-chymotrypsin and pepsin. Amino Acids, 46(12): 2733−2744. doi: 10.1007/s00726-014-1819-7
[4]	Assoni L, Milani B, Carvalho MR, et al. 2020. Resistance mechanisms to antimicrobial peptides in gram-positive bacteria. Frontiers in Microbiology, 11: 593215. doi: 10.3389/fmicb.2020.593215
[5]	Avram S, Buiu C, Borcan F, et al. 2012. More effective antimicrobial mastoparan derivatives, generated by 3D-QSAR-Almond and computational mutagenesis. Molecular BioSystems, 8(2): 587−594. doi: 10.1039/C1MB05297G
[6]	Bao KF, Yuan WY, Ma CB, et al. 2018. Modification targeting the "rana box" motif of a novel nigrocin peptide from Hylarana latouchii enhances and broadens its potency against multiple bacteria. Frontiers in Microbiology, 9: 2846. doi: 10.3389/fmicb.2018.02846
[7]	Bellm L, Giles FJ, Redman R, et al. 2002. Iseganan HCl: a novel antimicrobial agent. Expert Opinion on Investigational Drugs, 11(8): 1161−1170. doi: 10.1517/13543784.11.8.1161
[8]	Benedetto Tiz D, Bagnoli L, Rosati O, et al. 2022. New halogen-containing drugs approved by FDA in 2021: an overview on their syntheses and pharmaceutical use. Molecules, 27(5): 1643. doi: 10.3390/molecules27051643
[9]	Benfield AH, Henriques ST. 2020. Mode-of-action of antimicrobial peptides: membrane disruption vs. Intracellular mechanisms. Frontiers in Medical Technology, 2: 610997. doi: 10.3389/fmedt.2020.610997
[10]	Berger AA, Völler JS, Budisa N, et al. 2017. Deciphering the fluorine code-the many hats fluorine wears in a protein environment. Accounts of Chemical Research, 50(9): 2093−2103. doi: 10.1021/acs.accounts.7b00226
[11]	Bhadra P, Yan JL, Li JY, et al. 2018. AmPEP: sequence-based prediction of antimicrobial peptides using distribution patterns of amino acid properties and random forest. Scientific Reports, 8(1): 1697. doi: 10.1038/s41598-018-19752-w
[12]	Bhatt D, Patel C, Talsania H, et al. 2021. CNN variants for computer vision: history, architecture, application, challenges and future scope. Electronics, 10(20): 2470. doi: 10.3390/electronics10202470
[13]	Biswaro LS, da Costa Sousa MG, Rezende TMB, et al. 2018. Antimicrobial peptides and nanotechnology, recent advances and challenges. Frontiers in Microbiology, 9: 855. doi: 10.3389/fmicb.2018.00855
[14]	Bowler P, Murphy C, Wolcott R. 2020. Biofilm exacerbates antibiotic resistance: is this a current oversight in antimicrobial stewardship?. Antimicrobial Resistance & Infection Control, 9(1): 162.
[15]	Brade KD, Rybak JM, Rybak MJ. 2016. Oritavancin: a new lipoglycopeptide antibiotic in the treatment of Gram-positive infections. Infectious Diseases and Therapy, 5(1): 1−15. doi: 10.1007/s40121-016-0103-4
[16]	Breijyeh Z, Jubeh B, Karaman R. 2020. Resistance of gram-negative bacteria to current antibacterial agents and approaches to resolve it. Molecules, 25(6): 1340. doi: 10.3390/molecules25061340
[17]	Brinckerhoff LH, Kalashnikov VV, Thompson LW, et al. 1999. Terminal modifications inhibit proteolytic degradation of an immunogenic MART-1_27–35 peptide: implications for peptide vaccines. International Journal of Cancer, 83(3): 326−334. doi: 10.1002/(SICI)1097-0215(19991029)83:3<326::AID-IJC7>3.0.CO;2-X
[18]	Bruna T, Maldonado-Bravo F, Jara P, et al. 2021. Silver nanoparticles and their antibacterial applications. International Journal of Molecular Sciences, 22(13): 7202. doi: 10.3390/ijms22137202
[19]	Cai JF, Wei LL. 2021. Editorial of special column "novel peptides and peptidomimetics in drug discovery". Acta Pharmaceutica Sinica B, 11(9): 2606−2608. doi: 10.1016/j.apsb.2021.08.023
[20]	Casciaro B, Moros M, Rivera-Fernández S, et al. 2017. Gold-nanoparticles coated with the antimicrobial peptide esculentin-1a(1-21)NH₂ as a reliable strategy for antipseudomonal drugs. Acta Biomaterialia, 47: 170−181. doi: 10.1016/j.actbio.2016.09.041
[21]	Cervantes J, Garcia-Lamont F, Rodríguez-Mazahua L, et al. 2020. A comprehensive survey on support vector machine classification: applications, challenges and trends. Neurocomputing, 408: 189−215. doi: 10.1016/j.neucom.2019.10.118
[22]	Cesaro A, Der Torossian Torres M, de la Fuente-Nunez C. 2022. Methods for the design and characterization of peptide antibiotics. Methods in Enzymology, 663: 303−326.
[23]	Chan LY, Zhang VM, Huang YH, et al. 2013. Cyclization of the antimicrobial peptide gomesin with native chemical ligation: influences on stability and bioactivity. ChemBioChem, 14(5): 617−624. doi: 10.1002/cbic.201300034
[24]	Chen L, Kashina A. 2021. Post-translational modifications of the protein termini. Frontiers in Cell and Developmental Biology, 9: 719590. doi: 10.3389/fcell.2021.719590
[25]	Cheneval O, Schroeder CI, Durek T, et al. 2014. Fmoc-based synthesis of disulfide-rich cyclic peptides. The Journal of Organic Chemistry, 79(12): 5538−5544. doi: 10.1021/jo500699m
[26]	Cheng QP, Zeng P. 2022. Hydrophobic-hydrophilic alternation: an effective pattern to de novo designed antimicrobial peptides. Current Pharmaceutical Design, 28(44): 3527−3537. doi: 10.2174/1381612828666220902124856
[27]	Corey R, Naderer OJ, O'riordan WD, et al. 2014. Safety, tolerability, and efficacy of GSK1322322 in the treatment of acute bacterial skin and skin structure infections. Antimicrobial Agents and Chemotherapy, 58(11): 6518−6527. doi: 10.1128/AAC.03360-14
[28]	Croft NP, Purcell AW. 2011. Peptidomimetics: modifying peptides in the pursuit of better vaccines. Expert Review of Vaccines, 10(2): 211−226. doi: 10.1586/erv.10.161
[29]	Crowther GS, Baines SD, Todhunter SL, et al. 2013. Evaluation of NVB302 versus vancomycin activity in an in vitro human gut model of Clostridium difficile infection. Journal of Antimicrobial Chemotherapy, 68(1): 168−176. doi: 10.1093/jac/dks359
[30]	Cruz J, Flórez J, Torres R, et al. 2017. Antimicrobial activity of a new synthetic peptide loaded in polylactic acid or poly(lactic-co-glycolic) acid nanoparticles against Pseudomonas aeruginosa, Escherichia coli O157: H7 and methicillin resistant Staphylococcus aureus (MRSA). Nanotechnology, 28(13): 135102. doi: 10.1088/1361-6528/aa5f63
[31]	Cutler A, Cutler DR, Stevens JR. 2012. Random forests. In: Zhang C, Ma YQ. Ensemble Machine Learning: Methods and Applications. New York: Springer, 157–175.
[32]	Dargan S, Kumar M, Ayyagari MR, et al. 2020. A survey of deep learning and its applications: a new paradigm to machine learning. Archives of Computational Methods in Engineering, 27(4): 1071−1092. doi: 10.1007/s11831-019-09344-w
[33]	Datta A, Kundu P, Bhunia A. 2016. Designing potent antimicrobial peptides by disulphide linked dimerization and N-terminal lipidation to increase antimicrobial activity and membrane perturbation: structural insights into lipopolysaccharide binding. Journal of Colloid and Interface Science, 461: 335−345. doi: 10.1016/j.jcis.2015.09.036
[34]	de Breij A, Riool M, Cordfunke RA, et al. 2018. The antimicrobial peptide SAAP-148 combats drug-resistant bacteria and biofilms. Science Translational Medicine, 10(423): eaan4044. doi: 10.1126/scitranslmed.aan4044
[35]	Dennison SR, Morton LHG, Phoenix DA. 2012. Effect of amidation on the antimicrobial peptide aurein 2.5 from Australian southern bell frogs. Protein & Peptide Letters, 19(6): 586−591.
[36]	Dennison SR, Mura M, Harris F, et al. 2015. The role of C-terminal amidation in the membrane interactions of the anionic antimicrobial peptide, maximin H5. Biochimica et Biophysica Acta (BBA) - Biomembranes, 1848(5): 1111−1118. doi: 10.1016/j.bbamem.2015.01.014
[37]	Dennison SR, Phoenix DA. 2011. Influence of C-terminal amidation on the efficacy of modelin-5. Biochemistry, 50(9): 1514−1523. doi: 10.1021/bi101687t
[38]	Domhan C, Uhl P, Kleist C, et al. 2019. Replacement of L-amino acids by D-amino acids in the antimicrobial peptide ranalexin and its consequences for antimicrobial activity and biodistribution. Molecules, 24(16): 2987. doi: 10.3390/molecules24162987
[39]	Douafer H, Andrieu V, Phanstiel IV O, et al. 2019. Antibiotic adjuvants: make antibiotics great again! Journal of Medicinal Chemistry, 62(19): 8665–8681.
[40]	D’Souza AR, Necelis MR, Kulesha A, et al. 2021. Beneficial impacts of incorporating the non-natural amino acid azulenyl-alanine into the Trp-rich antimicrobial peptide buCATHL4B. Biomolecules, 11(3): 421. doi: 10.3390/biom11030421
[41]	Durek T, Cromm PM, White AM, et al. 2018. Development of novel melanocortin receptor agonists based on the cyclic peptide framework of sunflower trypsin inhibitor-1. Journal of Medicinal Chemistry, 61(8): 3674−3684. doi: 10.1021/acs.jmedchem.8b00170
[42]	Edwards IA, Elliott AG, Kavanagh AM, et al. 2016. Contribution of amphipathicity and hydrophobicity to the antimicrobial activity and cytotoxicity of β-hairpin peptides. ACS Infectious Diseases, 2(6): 442−450. doi: 10.1021/acsinfecdis.6b00045
[43]	Elnagdy S, Alkhazindar M. 2020. The potential of antimicrobial peptides as an antiviral therapy against COVID-19. ACS Pharmacology & Translational Science, 3(4): 780−782.
[44]	Erdem Büyükkiraz M, Kesmen Z. 2022. Antimicrobial peptides (AMPs): a promising class of antimicrobial compounds. Journal of Applied Microbiology, 132(3): 1573−1596. doi: 10.1111/jam.15314
[45]	Fadaka AO, Sibuyi NRS, Madiehe AM, et al. 2021. Nanotechnology-based delivery systems for antimicrobial peptides. Pharmaceutics, 13(11): 1795. doi: 10.3390/pharmaceutics13111795
[46]	Fang YQ, He XQ, Zhang PC, et al. 2019. In vitro and in vivo antimalarial activity of LZ1, a peptide derived from snake cathelicidin. Toxins, 11(7): 379. doi: 10.3390/toxins11070379
[47]	Farhadi T, Hashemian SM. 2018. Computer-aided design of amino acid-based therapeutics: a review. Drug Design, Development and Therapy, 12: 1239−1254. doi: 10.2147/DDDT.S159767
[48]	Flamm RK, Rhomberg PR, Simpson KM, et al. 2015. In vitro spectrum of pexiganan activity when tested against pathogens from diabetic foot infections and with selected resistance mechanisms. Antimicrobial Agents and Chemotherapy, 59(3): 1751−1754. doi: 10.1128/AAC.04773-14
[49]	Flint AJ, Davis AP. 2022. Vancomycin mimicry: towards new supramolecular antibiotics. Organic & Biomolecular Chemistry, 20(39): 7694−7712.
[50]	Fridkin SK, Edwards JR, Courval JM, et al. 2001. The effect of vancomycin and third-generation cephalosporins on prevalence of vancomycin-resistant enterococci in 126 U. S. adult intensive care units. Annals of Internal Medicine, 135(3): 175−183. doi: 10.7326/0003-4819-135-3-200108070-00009
[51]	Gan BH, Gaynord J, Rowe SM, et al. 2021. The multifaceted nature of antimicrobial peptides: current synthetic chemistry approaches and future directions. Chemical Society Reviews, 50(13): 7820−7880. doi: 10.1039/D0CS00729C
[52]	Gao JY, Na H, Zhong RB, et al. 2020. One step synthesis of antimicrobial peptide protected silver nanoparticles: the core-shell mutual enhancement of antibacterial activity. Colloids and Surfaces B:Biointerfaces, 186: 110704. doi: 10.1016/j.colsurfb.2019.110704
[53]	Gautier R, Douguet D, Antonny B, et al. 2008. HELIQUEST: a web server to screen sequences with specific α-helical properties. Bioinformatics, 24(18): 2101−2102. doi: 10.1093/bioinformatics/btn392
[54]	Ghosh C, Haldar J. 2015. Membrane-active small molecules: designs inspired by antimicrobial peptides. ChemMedChem, 10(10): 1606−1624. doi: 10.1002/cmdc.201500299
[55]	Giangaspero A, Sandri L, Tossi A. 2001. Amphipathic α helical antimicrobial peptides. European Journal of Biochemistry, 268(21): 5589−5600. doi: 10.1046/j.1432-1033.2001.02494.x
[56]	Gogoladze G, Grigolava M, Vishnepolsky B, et al. 2014. DBAASP: database of antimicrobial activity and structure of peptides. FEMS Microbiology Letters, 357(1): 63−68. doi: 10.1111/1574-6968.12489
[57]	Gómez-Sequeda N, Ruiz J, Ortiz C, et al. 2020. Potent and specific antibacterial activity against Escherichia coli O157: H7 and methicillin resistant Staphylococcus aureus (MRSA) of G17 and G19 peptides encapsulated into poly-lactic-Co-glycolic acid (PLGA) nanoparticles. Antibiotics, 9(7): 384. doi: 10.3390/antibiotics9070384
[58]	Gottler LM, Ramamoorthy A. 2009. Structure, membrane orientation, mechanism, and function of pexiganan-a highly potent antimicrobial peptide designed from magainin. Biochimica et Biophysica Acta (BBA) - Biomembranes, 1788(8): 1680−1686. doi: 10.1016/j.bbamem.2008.10.009
[59]	Grundmann H, Aires-de-Sousa M, Boyce J, et al. 2006. Emergence and resurgence of meticillin-resistant Staphylococcus aureus as a public-health threat. The Lancet, 368(9538): 874−885. doi: 10.1016/S0140-6736(06)68853-3
[60]	Guan QK, Huang SH, Jin Y, et al. 2019. Recent advances in the exploration of therapeutic analogues of gramicidin S, an old but still potent antimicrobial peptide. Journal of Medicinal Chemistry, 62(17): 7603−7617. doi: 10.1021/acs.jmedchem.9b00156
[61]	Gupta S, Azadvari N, Hosseinzadeh P. 2022. Design of protein segments and peptides for binding to protein targets. BioDesign Research, 2022: 9783197. doi: 10.34133/2022/9783197
[62]	Han YJ, Zhang ML, Lai R, et al. 2021. Chemical modifications to increase the therapeutic potential of antimicrobial peptides. Peptides, 146: 170666. doi: 10.1016/j.peptides.2021.170666
[63]	Haney EF, Straus SK, Hancock REW. 2019. Reassessing the host defense peptide landscape. Frontiers in Chemistry, 7: 43. doi: 10.3389/fchem.2019.00043
[64]	Hellinger R, Muratspahić E, Devi S, et al. 2021. Importance of the cyclic cystine knot structural motif for immunosuppressive effects of cyclotides. ACS Chemical Biology, 16(11): 2373−2386. doi: 10.1021/acschembio.1c00524
[65]	Huan YC, Kong Q, Mou HJ, et al. 2020. Antimicrobial peptides: classification, design, application and research progress in multiple fields. Frontiers in Microbiology, 11: 582779. doi: 10.3389/fmicb.2020.582779
[66]	Huhmann S, Koksch B. 2018. Fine-tuning the proteolytic stability of peptides with fluorinated amino acids. European Journal of Organic Chemistry, 2018(27-28): 3667−3679. doi: 10.1002/ejoc.201800803
[67]	Iepsen EW, Torekov SS, Holst JJ. 2015. Liraglutide for type 2 diabetes and obesity: a 2015 update. Expert Review of Cardiovascular Therapy, 13(7): 753−767. doi: 10.1586/14779072.2015.1054810
[68]	Jackson SH, Martin TS, Jones JD, et al. 2010. Liraglutide (victoza): the first once-daily incretin mimetic injection for type-2 diabetes. P & T:A Peer-Reviewed Journal for Formulary Management, 35(9): 498−529.
[69]	Jang WS, Li XS, Sun JN, et al. 2008. The P-113 fragment of histatin 5 requires a specific peptide sequence for intracellular translocation in Candida albicans, which is independent of cell wall binding. Antimicrobial Agents and Chemotherapy, 52(2): 497−504. doi: 10.1128/AAC.01199-07
[70]	Jerala R. 2007. Synthetic lipopeptides: a novel class of anti-infectives. Expert Opinion on Investigational Drugs, 16(8): 1159−1169. doi: 10.1517/13543784.16.8.1159
[71]	Jhong JH, Yao LT, Pang YX, et al. 2022. dbAMP 2.0: updated resource for antimicrobial peptides with an enhanced scanning method for genomic and proteomic data. Nucleic Acids Research, 50(D1): D460−D470. doi: 10.1093/nar/gkab1080
[72]	Jia FJ, Yu Q, Wang RL, et al. 2023. Optimized antimicrobial peptide jelleine-I derivative Br-J-I inhibits fusobacterium nucleatum to suppress colorectal cancer progression. International Journal of Molecular Sciences, 24(2): 1469. doi: 10.3390/ijms24021469
[73]	Jia FJ, Zhang Y, Wang JY, et al. 2019. The effect of halogenation on the antimicrobial activity, antibiofilm activity, cytotoxicity and proteolytic stability of the antimicrobial peptide Jelleine-I. Peptides, 112: 56−66. doi: 10.1016/j.peptides.2018.11.006
[74]	Jiang SQ, Zhang LJ, Cui DB, et al. 2016. The important role of halogen bond in substrate selectivity of enzymatic catalysis. Scientific Reports, 6: 34750. doi: 10.1038/srep34750
[75]	Jin L, Bai XW, Luan N, et al. 2016. A designed tryptophan- and lysine/arginine-rich antimicrobial peptide with therapeutic potential for clinical antibiotic-resistant Candida albicans vaginitis. Journal of Medicinal Chemistry, 59(5): 1791−1799. doi: 10.1021/acs.jmedchem.5b01264
[76]	Jin Y, Yang YD, Duan W, et al. 2021. Synergistic and on-demand release of Ag-AMPs loaded on porous silicon nanocarriers for antibacteria and wound healing. ACS Applied Materials & Interfaces, 13(14): 16127−16141.
[77]	Jing YK, Bian YM, Hu ZH, et al. 2018. Deep learning for drug design: an artificial intelligence paradigm for drug discovery in the big data era. The AAPS Journal, 20(3): 58. doi: 10.1208/s12248-018-0210-0
[78]	Joseph S, Karnik S, Nilawe P, et al. 2012. ClassAMP: a prediction tool for classification of antimicrobial peptides. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 9(5): 1535−1538. doi: 10.1109/TCBB.2012.89
[79]	Jubeh B, Breijyeh Z, Karaman R. 2020. Resistance of gram-positive bacteria to current antibacterial agents and overcoming approaches. Molecules, 25(12): 2888. doi: 10.3390/molecules25122888
[80]	Kang SJ, Nam SH, Lee BJ. 2022. Engineering approaches for the development of antimicrobial peptide-based antibiotics. Antibiotics, 11(10): 1338. doi: 10.3390/antibiotics11101338
[81]	Kang XY, Dong FY, Shi C, et al. 2019. DRAMP 2.0, an updated data repository of antimicrobial peptides. Scientific Data, 6(1): 148. doi: 10.1038/s41597-019-0154-y
[82]	Karlsson AJ, Flessner RM, Gellman SH, et al. 2010. Polyelectrolyte multilayers fabricated from antifungal β-peptides: design of surfaces that exhibit antifungal activity against Candida albicans. Biomacromolecules, 11(9): 2321–2328.
[83]	Keyvanpour MR, Shirzad MB. 2021. An analysis of QSAR research based on machine learning concepts. Current Drug Discovery Technologies, 18(1): 17−30. doi: 10.2174/1570163817666200316104404
[84]	Kitchen CM, Nuño M, Kitchen SG, et al. 2008. Enfuvirtide antiretroviral therapy in HIV-1 infection. Therapeutics and Clinical Risk Management, 4(2): 433−439.
[85]	Kodama T, Ashitani JI, Matsumoto N, et al. 2008. Ghrelin treatment suppresses neutrophil-dominant inflammation in airways of patients with chronic respiratory infection. Pulmonary Pharmacology & Therapeutics, 21(5): 774−779.
[86]	Kudrimoti M, Curtis A, Azawi S, et al. 2017. Dusquetide: reduction in oral mucositis associated with enduring ancillary benefits in tumor resolution and decreased mortality in head and neck cancer patients. Biotechnology Reports, 15: 24−26. doi: 10.1016/j.btre.2017.05.002
[87]	Kumar P, Kizhakkedathu JN, Straus SK. 2018. Antimicrobial peptides: diversity, mechanism of action and strategies to improve the activity and biocompatibility in vivo. Biomolecules, 8(1): 4. doi: 10.3390/biom8010004
[88]	Kuppusamy R, Willcox M, Black DS, et al. 2019. Short cationic peptidomimetic antimicrobials. Antibiotics, 8(2): 44. doi: 10.3390/antibiotics8020044
[89]	Kwon S, Bosmans F, Kaas Q, et al. 2016. Efficient enzymatic cyclization of an inhibitory cystine knot-containing peptide. Biotechnology and Bioengineering, 113(10): 2202−2212. doi: 10.1002/bit.25993
[90]	Lachowicz JI, Szczepski K, Scano A, et al. 2020. The best peptidomimetic strategies to undercover antibacterial peptides. International Journal of Molecular Sciences, 21(19): 7349. doi: 10.3390/ijms21197349
[91]	Lata S, Mishra NK, Raghava GPS. 2010. AntiBP2: improved version of antibacterial peptide prediction. BMC Bioinformatics, 11(S1): S19. doi: 10.1186/1471-2105-11-S1-S19
[92]	Lee EY, Lee MW, Fulan BM, et al. 2017. What can machine learning do for antimicrobial peptides, and what can antimicrobial peptides do for machine learning?. Interface Focus, 7(6): 20160153. doi: 10.1098/rsfs.2016.0153
[93]	Lee S, Trinh THT, Yoo M, et al. 2019. Self-assembling peptides and their application in the treatment of diseases. International Journal of Molecular Sciences, 20(23): 5850. doi: 10.3390/ijms20235850
[94]	Lee YCJ, Shirkey JD, Park J, et al. 2022. An overview of antiviral peptides and rational biodesign considerations. BioDesign Research, 2022: 9898241. doi: 10.34133/2022/9898241
[95]	Lei J, Sun LC, Huang SY, et al. 2019. The antimicrobial peptides and their potential clinical applications. American Journal of Translational Research, 11(7): 3919−3931.
[96]	Lei RY, Hou JC, Chen QX, et al. 2018. Self-assembling myristoylated human α-defensin 5 as a next-generation nanobiotics potentiates therapeutic efficacy in bacterial infection. ACS Nano, 12(6): 5284−5296. doi: 10.1021/acsnano.7b09109
[97]	Lenci E, Trabocchi A. 2020. Peptidomimetic toolbox for drug discovery. Chemical Society Reviews, 49(11): 3262−3277. doi: 10.1039/D0CS00102C
[98]	Leptihn S, Har JY, Wohland T, et al. 2010. Correlation of charge, hydrophobicity, and structure with antimicrobial activity of S1 and MIRIAM peptides. Biochemistry, 49(43): 9161−9170. doi: 10.1021/bi1011578
[99]	Lertampaiporn S, Vorapreeda T, Hongsthong A, et al. 2021. Ensemble-AMPPred: robust AMP prediction and recognition using the ensemble learning method with a new hybrid feature for differentiating AMPs. Genes, 12(2): 137. doi: 10.3390/genes12020137
[100]	Lévêque L, Tahiri N, Goldsmith MR, et al. 2022. Quantitative Structure-Activity Relationship (QSAR) modeling to predict the transfer of environmental chemicals across the placenta. Computational Toxicology, 21: 100211. doi: 10.1016/j.comtox.2021.100211
[101]	Li CK, Sutherland D, Hammond SA, et al. 2022. AMPlify: attentive deep learning model for discovery of novel antimicrobial peptides effective against WHO priority pathogens. BMC Genomics, 23(1): 77. doi: 10.1186/s12864-022-08310-4
[102]	Li DD, Yang YH, Li RF, et al. 2021. N-terminal acetylation of antimicrobial peptide L163 improves its stability against protease degradation. Journal of Peptide Science, 27(9): e3337. doi: 10.1002/psc.3337
[103]	Li J, Xu X, Xu C, et al. 2007. Anti-infection peptidomics of amphibian skin. Molecular & Cellular Proteomics, 6(5): 882−894.
[104]	Lin LM, Chi JY, Yan YL, et al. 2021a. Membrane-disruptive peptides/peptidomimetics-based therapeutics: promising systems to combat bacteria and cancer in the drug-resistant era. Acta Pharmaceutica Sinica B, 11(9): 2609−2644. doi: 10.1016/j.apsb.2021.07.014
[105]	Lin TT, Yang LY, Lu IH, et al. 2021c. AI4AMP: an antimicrobial peptide predictor using physicochemical property-based encoding method and deep learning. mSystems, 6(6): e0029921. doi: 10.1128/mSystems.00299-21
[106]	Lin TT, Yang LY, Wang CT, et al. 2021b. Discovering novel antimicrobial peptides in generative adversarial network. BioRxiv, doi: https://doi.org/10.1101/2021.11.22.469634.
[107]	Lipsky BA, Hoey C. 2009. Topical antimicrobial therapy for treating chronic wounds. Clinical Infectious Diseases, 49(10): 1541−1549. doi: 10.1086/644732
[108]	Liu TQ, Zhu NY, Zhong C, et al. 2020. Effect of N-methylated and fatty acid conjugation on analogs of antimicrobial peptide Anoplin. European Journal of Pharmaceutical Sciences, 152: 105453. doi: 10.1016/j.ejps.2020.105453
[109]	Liu YL, Wang YR, Zhang J. 2012. New machine learning algorithm: random forest. In: Third International Conference on Information Computing and Applications. Chengde: Springer, 246–252.
[110]	Lombardi L, Falanga A, Del Genio V, et al. 2019. A new hope: self-assembling peptides with antimicrobial activity. Pharmaceutics, 11(4): 166. doi: 10.3390/pharmaceutics11040166
[111]	Lopalco L. 2010. CCR5: from natural resistance to a new anti-HIV strategy. Viruses, 2(2): 574−600. doi: 10.3390/v2020574
[112]	López Cascales JJ, Zenak S, García de la Torre J, et al. 2018. Small cationic peptides: influence of charge on their antimicrobial activity. ACS Omega, 3(5): 5390−5398. doi: 10.1021/acsomega.8b00293
[113]	Mahlapuu M, Sidorowicz A, Mikosinski J, et al. 2021. Evaluation of LL-37 in healing of hard-to-heal venous leg ulcers: a multicentric prospective randomized placebo-controlled clinical trial. Wound Repair and Regeneration, 29(6): 938−950. doi: 10.1111/wrr.12977
[114]	Makobongo MO, Gancz H, Carpenter BM, et al. 2012. The oligo-acyl lysyl antimicrobial peptide C₁₂K-2β₁₂ exhibits a dual mechanism of action and demonstrates strong in vivo efficacy against Helicobacter pylori. Antimicrobial Agents and Chemotherapy, 56(1): 378–390.
[115]	Malina A, Shai Y. 2005. Conjugation of fatty acids with different lengths modulates the antibacterial and antifungal activity of a cationic biologically inactive peptide. Biochemical Journal, 390(Pt 3): 695–702.
[116]	Maltarollo VG, Kronenberger T, Espinoza GZ, et al. 2019. Advances with support vector machines for novel drug discovery. Expert Opinion on Drug Discovery, 14(1): 23−33. doi: 10.1080/17460441.2019.1549033
[117]	Mardirossian M, Rubini M, Adamo MFA, et al. 2021. Natural and synthetic halogenated amino acids-structural and bioactive features in antimicrobial peptides and peptidomimetics. Molecules, 26(23): 7401. doi: 10.3390/molecules26237401
[118]	Matthyssen T, Li WY, Holden JA, et al. 2022. The potential of modified and multimeric antimicrobial peptide materials as superbug killers. Frontiers in Chemistry, 9: 795433. doi: 10.3389/fchem.2021.795433
[119]	Meher PK, Sahu TK, Saini V, et al. 2017. Predicting antimicrobial peptides with improved accuracy by incorporating the compositional, physico-chemical and structural features into Chou’s general PseAAC. Scientific Reports, 7(1): 42362. doi: 10.1038/srep42362
[120]	Méndez-Samperio P. 2014. Peptidomimetics as a new generation of antimicrobial agents: current progress. Infection and Drug Resistance, 7: 229−237.
[121]	Mercer DK, Robertson JC, Miller L, et al. 2020. NP213 (Novexatin®): a unique therapy candidate for onychomycosis with a differentiated safety and efficacy profile. Medical Mycology, 58(8): 1064−1072. doi: 10.1093/mmy/myaa015
[122]	Michalopoulos AS, Tsiodras S, Rellos K, et al. 2005. Colistin treatment in patients with ICU-acquired infections caused by multiresistant Gram-negative bacteria: the renaissance of an old antibiotic. Clinical Microbiology and Infection, 11(2): 115−121. doi: 10.1111/j.1469-0691.2004.01043.x
[123]	Mishra AK, Choi J, Moon E, et al. 2018. Tryptophan-rich and proline-rich antimicrobial peptides. Molecules, 23(4): 815. doi: 10.3390/molecules23040815
[124]	Mitchell JBO. 2014. Machine learning methods in chemoinformatics. WIREs Computational Molecular Science, 4(5): 468−481. doi: 10.1002/wcms.1183
[125]	Mohamed H, Gurrola T, Berman R, et al. 2022. Targeting CCR5 as a component of an HIV-1 therapeutic strategy. Frontiers in Immunology, 12: 816515. doi: 10.3389/fimmu.2021.816515
[126]	Molchanova N, Hansen PR, Franzyk H. 2017. Advances in development of antimicrobial peptidomimetics as potential drugs. Molecules, 22(9): 1430. doi: 10.3390/molecules22091430
[127]	Moravej H, Moravej Z, Yazdanparast M, et al. 2018. Antimicrobial peptides: features, action, and their resistance mechanisms in bacteria. Microbial Drug Resistance, 24(6): 747−767. doi: 10.1089/mdr.2017.0392
[128]	Mouchlis VD, Afantitis A, Serra A, et al. 2021. Advances in de novo drug design: from conventional to machine learning methods. International Journal of Molecular Sciences, 22(4): 1676. doi: 10.3390/ijms22041676
[129]	Mullane K, Lee C, Bressler A, et al. 2015. Multicenter, randomized clinical trial to compare the safety and efficacy of LFF571 and vancomycin for Clostridium difficile infections. Antimicrobial Agents and Chemotherapy, 59(3): 1435−1440. doi: 10.1128/AAC.04251-14
[130]	Müller AT, Gabernet G, Hiss JA, et al. 2017. modlAMP: python for antimicrobial peptides. Bioinformatics, 33(17): 2753−2755. doi: 10.1093/bioinformatics/btx285
[131]	Müller K, Faeh C, Diederich F. 2007. Fluorine in pharmaceuticals: looking beyond intuition. Science, 317(5846): 1881−1886. doi: 10.1126/science.1131943
[132]	Mura M, Wang JP, Zhou YH, et al. 2016. The effect of amidation on the behaviour of antimicrobial peptides. European Biophysics Journal, 45(3): 195−207. doi: 10.1007/s00249-015-1094-x
[133]	Murray CJL, Ikuta KS, Sharara F, et al. 2022. Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. The Lancet, 399(10325): 629−655. doi: 10.1016/S0140-6736(21)02724-0
[134]	Mwangi J, Hao X, Lai R, et al. 2019a. Antimicrobial peptides: new hope in the war against multidrug resistance. Zoological Research, 40(6): 488−505. doi: 10.24272/j.issn.2095-8137.2019.062
[135]	Mwangi J, Yin YZ, Wang G, et al. 2019b. The antimicrobial peptide ZY4 combats multidrug-resistant Pseudomonas aeruginosa and Acinetobacter baumannii infection. Proceedings of the National Academy of Sciences of the United States of America, 116(52): 26516−26522.
[136]	Nagarajan D, Nagarajan T, Roy N, et al. 2018. Computational antimicrobial peptide design and evaluation against multidrug-resistant clinical isolates of bacteria. Journal of Biological Chemistry, 293(10): 3492−3509. doi: 10.1074/jbc.M117.805499
[137]	Natan M, Banin E. 2017. From Nano to Micro: using nanotechnology to combat microorganisms and their multidrug resistance. FEMS Microbiology Reviews, 41(3): 302−322. doi: 10.1093/femsre/fux003
[138]	Nawrocki KL, Crispell EK, McBride SM. 2014. Antimicrobial peptide resistance mechanisms of gram-positive bacteria. Antibiotics, 3(4): 461−492. doi: 10.3390/antibiotics3040461
[139]	Nevitt C, Tooley JG, Schaner Tooley CE. 2018. N-terminal acetylation and methylation differentially affect the function of MYL9. Biochemical Journal, 475(20): 3201−3219. doi: 10.1042/BCJ20180638
[140]	Nizet V. 2006. Antimicrobial peptide resistance mechanisms of human bacterial pathogens. Current Issues in Molecular Biology, 8(1): 11−26.
[141]	Olsen CA, Bonke G, Vedel L, et al. 2007. α-peptide/β-peptoid chimeras. Organic Letters, 9(8): 1549−1552. doi: 10.1021/ol070316c
[142]	Omardien S, Brul S, Zaat SAJ. 2016. Antimicrobial activity of cationic antimicrobial peptides against gram-positives: current progress made in understanding the mode of action and the response of bacteria. Frontiers in Cell and Developmental Biology, 4: 111.
[143]	Pachón-Ibáñez ME, Smani Y, Pachón J, et al. 2017. Perspectives for clinical use of engineered human host defense antimicrobial peptides. FEMS Microbiology Reviews, 41(3): 323−342. doi: 10.1093/femsre/fux012
[144]	Panda BP, Krishnamoorthy R, Bhattamisra SK, et al. 2019. Fabrication of second generation smarter PLGA based nanocrystal carriers for improvement of drug delivery and therapeutic efficacy of gliclazide in type-2 diabetes rat model. Scientific Reports, 9(1): 17331. doi: 10.1038/s41598-019-53996-4
[145]	Papanastasiou EA, Hua Q, Sandouk A, et al. 2009. Role of acetylation and charge in antimicrobial peptides based on human β-defensin-3. APMIS, 117(7): 492−499. doi: 10.1111/j.1600-0463.2009.02460.x
[146]	Parmar S, Patel K, Pinilla-Ibarz J. 2014. Ibrutinib (imbruvica): a novel targeted therapy for chronic lymphocytic leukemia. P & T:A Peer-Reviewed Journal for Formulary Management, 39(7): 483−519.
[147]	Pastore A, Raimondi F, Rajendran L, et al. 2020. Why does the Aβ peptide of Alzheimer share structural similarity with antimicrobial peptides?. Communications Biology, 3(1): 135. doi: 10.1038/s42003-020-0865-9
[148]	Peek NFAW, Nell MJ, Brand R, et al. 2020. Ototopical drops containing a novel antibacterial synthetic peptide: safety and efficacy in adults with chronic suppurative otitis media. PLoS One, 15(4): e0231573. doi: 10.1371/journal.pone.0231573
[149]	Prieto-Martínez FD, López-López E, Eurídice Juárez-Mercado K, et al. 2019. Computational drug design methods—current and future perspectives. In: Roy K. In Silico Drug Design: Repurposing Techniques and Methodologies. London: Academic Press, 19–44.
[150]	Qian S, Wang WC, Yang L, et al. 2008. Structure of the alamethicin pore reconstructed by X-ray diffraction analysis. Biophysical Journal, 94(9): 3512−3522. doi: 10.1529/biophysj.107.126474
[151]	Qvit N, Rubin SJS, Urban TJ, et al. 2017. Peptidomimetic therapeutics: scientific approaches and opportunities. Drug Discovery Today, 22(2): 454−462. doi: 10.1016/j.drudis.2016.11.003
[152]	Radek K, Gallo R. 2007. Antimicrobial peptides: natural effectors of the innate immune system. Seminars in Immunopathology, 29(1): 27−43. doi: 10.1007/s00281-007-0064-5
[153]	Rai A, Pinto S, Velho TR, et al. 2016. One-step synthesis of high-density peptide-conjugated gold nanoparticles with antimicrobial efficacy in a systemic infection model. Biomaterials, 85: 99−110. doi: 10.1016/j.biomaterials.2016.01.051
[154]	Rajasekaran G, Kim EY, Shin SY. 2017. LL-37-derived membrane-active FK-13 analogs possessing cell selectivity, anti-biofilm activity and synergy with chloramphenicol and anti-inflammatory activity. Biochimica et Biophysica Acta (BBA) - Biomembranes, 1859(5): 722−733. doi: 10.1016/j.bbamem.2017.01.037
[155]	Rajchakit U, Sarojini V. 2017. Recent developments in antimicrobial-peptide-conjugated gold nanoparticles. Bioconjugate Chemistry, 28(11): 2673−2686. doi: 10.1021/acs.bioconjchem.7b00368
[156]	Ramadan RA, Gebriel MG, Kadry HM, et al. 2018. Carbapenem-resistant Acinetobacter baumannii and Pseudomonas aeruginosa: characterization of carbapenemase genes and E-test evaluation of colistin-based combinations. Infection and Drug Resistance, 11: 1261−1269. doi: 10.2147/IDR.S170233
[157]	Ramezanzadeh M, Saeedi N, Mesbahfar E, et al. 2021. Design and characterization of new antimicrobial peptides derived from aurein 1.2 with enhanced antibacterial activity. Biochimie, 181: 42−51. doi: 10.1016/j.biochi.2020.11.020
[158]	Robalo JR, Huhmann S, Koksch B, et al. 2017. The multiple origins of the hydrophobicity of fluorinated apolar amino acids. Chem, 3(5): 881−897. doi: 10.1016/j.chempr.2017.09.012
[159]	Rounds T, Straus SK. 2020. Lipidation of antimicrobial peptides as a design strategy for future alternatives to antibiotics. International Journal of Molecular Sciences, 21(24): 9692. doi: 10.3390/ijms21249692
[160]	Sader HS, Fedler KA, Rennie RP, et al. 2004. Omiganan pentahydrochloride (MBI 226), a topical 12-amino-acid cationic peptide: spectrum of antimicrobial activity and measurements of bactericidal activity. Antimicrobial Agents and Chemotherapy, 48(8): 3112−3118. doi: 10.1128/AAC.48.8.3112-3118.2004
[161]	Sandín D, Valle J, Chaves-Arquero B, et al. 2021. Rationally modified antimicrobial peptides from the N-Terminal domain of human RNase 3 show exceptional serum stability. Journal of Medicinal Chemistry, 64(15): 11472−11482. doi: 10.1021/acs.jmedchem.1c00795
[162]	Schnaider L, Rosenberg A, Kreiser T, et al. 2020. Peptide self-assembly is linked to antibacterial, but not antifungal, activity of histatin 5 derivatives. mSphere, 5(2): e00021−20.
[163]	Schneider P, Schneider G. 2016. De novo design at the edge of chaos. Journal of Medicinal Chemistry, 59(9): 4077−4086. doi: 10.1021/acs.jmedchem.5b01849
[164]	Sergiev PG. 1944. Clinical use of gramicidin S. The Lancet, 244(6327): 717−718. doi: 10.1016/S0140-6736(00)88379-8
[165]	Sforça ML, Oyama Jr S, Canduri F, et al. 2004. How C-terminal carboxyamidation alters the biological activity of peptides from the venom of the eumenine solitary wasp. Biochemistry, 43(19): 5608−5617. doi: 10.1021/bi0360915
[166]	Shah MB, Liu JB, Zhang QH, et al. 2017. Halogen-π interactions in the cytochrome P450 active site: structural insights into human CYP2B6 substrate selectivity. ACS Chemical Biology, 12(5): 1204−1210. doi: 10.1021/acschembio.7b00056
[167]	Shahrour H, Ferrer-Espada R, Dandache I, et al. 2019. AMPs as anti-biofilm agents for human therapy and prophylaxis. Advances in Experimental Medicine and Biology, 1117: 257−279.
[168]	Sharma D, Misba L, Khan AU. 2019. Antibiotics versus biofilm: an emerging battleground in microbial communities. Antimicrobial Resistance & Infection Control, 8: 76.
[169]	Sheard DE, O’Brien-Simpson NM, Wade JD, et al. 2019. Combating bacterial resistance by combination of antibiotics with antimicrobial peptides. Pure and Applied Chemistry, 91(2): 199−209. doi: 10.1515/pac-2018-0707
[170]	Shearer J, Castro JL, Lawson ADG, et al. 2022. Rings in clinical trials and drugs: present and future. Journal of Medicinal Chemistry, 65(13): 8699−8712. doi: 10.1021/acs.jmedchem.2c00473
[171]	Shi GB, Kang XY, Dong FY, et al. 2022. DRAMP 3.0: an enhanced comprehensive data repository of antimicrobial peptides. Nucleic Acids Research, 50(D1): D488−D496. doi: 10.1093/nar/gkab651
[172]	Sieprawska-Lupa M, Mydel P, Krawczyk K, et al. 2004. Degradation of human antimicrobial peptide LL-37 by Staphylococcus aureus-derived proteinases. Antimicrobial Agents and Chemotherapy, 48(12): 4673−4679. doi: 10.1128/AAC.48.12.4673-4679.2004
[173]	Singh J, Joshi S, Mumtaz S, et al. 2016. Enhanced cationic charge is a key factor in promoting staphylocidal activity of α-melanocyte stimulating hormone via selective lipid affinity. Scientific Reports, 6: 31492. doi: 10.1038/srep31492
[174]	Smirnova MP, Afonin VG, Shpen’ VM, et al. 2004. Structure-Function relationship between analogues of the antibacterial peptide indolicidin. I. Synthesis and biological activity of analogues with increased amphipathicity and elevated net positive charge of the molecule. Russian Journal of Bioorganic Chemistry, 30(5): 409−416. doi: 10.1023/B:RUBI.0000043782.21640.c2
[175]	Spänig S, Heider D. 2019. Encodings and models for antimicrobial peptide classification for multi-resistant pathogens. BioData Mining, 12: 7. doi: 10.1186/s13040-019-0196-x
[176]	Srinivas N, Jetter P, Ueberbacher BJ, et al. 2010. Peptidomimetic antibiotics target outer-membrane biogenesis in Pseudomonas aeruginosa. Science, 327(5968): 1010–1013.
[177]	Stewart PS. 2002. Mechanisms of antibiotic resistance in bacterial biofilms. International Journal of Medical Microbiology, 292(2): 107−113. doi: 10.1078/1438-4221-00196
[178]	Syed YY, Scott LJ. 2015. Oritavancin: a review in acute bacterial skin and skin structure infections. Drugs, 75(16): 1891−1902. doi: 10.1007/s40265-015-0478-7
[179]	Tabatabaei Mirakabad FS, Nejati-Koshki K, Akbarzadeh A, et al. 2014. PLGA-based nanoparticles as cancer drug delivery systems. Asian Pacific Journal of Cancer Prevention, 15(2): 517−535. doi: 10.7314/APJCP.2014.15.2.517
[180]	Taboureau O. 2010. Methods for building quantitative structure-activity relationship (QSAR) descriptors and predictive models for computer-aided design of antimicrobial peptides. In: Giuliani A, Rinaldi AC. Antimicrobial Peptides: Methods and Protocols. Totowa: Humana, 77–86.
[181]	Teixeira MC, Carbone C, Sousa MC, et al. 2020. Nanomedicines for the delivery of antimicrobial peptides (AMPs). Nanomaterials, 10(3): 560. doi: 10.3390/nano10030560
[182]	Thapa RK, Diep DB, Tønnesen HH. 2021. Nanomedicine-based antimicrobial peptide delivery for bacterial infections: recent advances and future prospects. Journal of Pharmaceutical Investigation, 51(4): 377−398. doi: 10.1007/s40005-021-00525-z
[183]	Thomas S, Karnik S, Barai RS, et al. 2010. CAMP: a useful resource for research on antimicrobial peptides. Nucleic Acids Research, 38(S1): D774−D780.
[184]	Timmons PB, Hewage CM. 2021a. ENNAACT is a novel tool which employs neural networks for anticancer activity classification for therapeutic peptides. Biomedicine & Pharmacotherapy, 133: 111051.
[185]	Timmons PB, Hewage CM. 2021b. ENNAVIA is a novel method which employs neural networks for antiviral and anti-coronavirus activity prediction for therapeutic peptides. Briefings in Bioinformatics, 22(6): bbab258. doi: 10.1093/bib/bbab258
[186]	Tornesello AL, Borrelli A, Buonaguro L, et al. 2020. Antimicrobial peptides as anticancer agents: functional properties and biological activities. Molecules, 25(12): 2850. doi: 10.3390/molecules25122850
[187]	Travis S, Yap LM, Hawkey C, et al. 2005. Rdp58 is a novel and potentially effective oral therapy for ulcerative colitis. Inflammatory Bowel Diseases, 11(8): 713−719. doi: 10.1097/01.MIB.0000172807.26748.16
[188]	Umedera K, Yoshimori A, Chen HW, et al. 2023. DeepCubist: molecular generator for designing peptidomimetics based on complex three-dimensional scaffolds. Journal of Computer-Aided Molecular Design, 37(2): 107−115. doi: 10.1007/s10822-022-00493-y
[189]	Urnukhsaikhan E, Bold BE, Gunbileg A, et al. 2021. Antibacterial activity and characteristics of silver nanoparticles biosynthesized from Carduus crispus. Scientific Reports, 11(1): 21047.
[190]	Vandekerckhove L, Verhofstede C, Vogelaers D. 2009. Maraviroc: perspectives for use in antiretroviral-naive HIV-1-infected patients. Journal of Antimicrobial Chemotherapy, 63(6): 1087−1096. doi: 10.1093/jac/dkp113
[191]	Veltri D, Kamath U, Shehu A. 2018. Deep learning improves antimicrobial peptide recognition. Bioinformatics, 34(16): 2740−2747. doi: 10.1093/bioinformatics/bty179
[192]	Vernen F, Harvey PJ, Dias SA, et al. 2019. Characterization of tachyplesin peptides and their cyclized analogues to improve antimicrobial and anticancer properties. International Journal of Molecular Sciences, 20(17): 4184. doi: 10.3390/ijms20174184
[193]	Vishnepolsky B, Gabrielian A, Rosenthal A, et al. 2018. Predictive model of linear antimicrobial peptides active against gram-negative bacteria. Journal of Chemical Information and Modeling, 58(5): 1141−1151. doi: 10.1021/acs.jcim.8b00118
[194]	Wach A, Dembowsky K, Dale GE. 2018. Pharmacokinetics and safety of intravenous murepavadin infusion in healthy adult subjects administered single and multiple ascending doses. Antimicrobial Agents and Chemother, 62(4): e02355−17.
[195]	Waghu FH, Barai RS, Gurung P, et al. 2016. CAMP_R3: a database on sequences, structures and signatures of antimicrobial peptides. Nucleic Acids Research, 44(D1): D1094−D1097. doi: 10.1093/nar/gkv1051
[196]	Wang C, Garlick S, Zloh M. 2021a. Deep learning for novel antimicrobial peptide design. Biomolecules, 11(3): 471. doi: 10.3390/biom11030471
[197]	Wang C, Hong TT, Cui PF, et al. 2021b. Antimicrobial peptides towards clinical application: delivery and formulation. Advanced Drug Delivery Reviews, 175: 113818. doi: 10.1016/j.addr.2021.05.028
[198]	Wang GS. 2008. Structures of human host defense cathelicidin LL-37 and its smallest antimicrobial peptide KR-12 in lipid micelles. Journal of Biological Chemistry, 283(47): 32637−32643. doi: 10.1074/jbc.M805533200
[199]	Wang GS, Li X, Wang Z. 2016. APD3: the antimicrobial peptide database as a tool for research and education. Nucleic Acids Research, 44(D1): D1087−D1093. doi: 10.1093/nar/gkv1278
[200]	Wang YP, Hong J, Liu XH, et al. 2008. Snake cathelicidin from Bungarus fasciatus is a potent peptide antibiotics. PLoS One, 3(9): e3217. doi: 10.1371/journal.pone.0003217
[201]	Wang YP, Zhang ZY, Chen LL, et al. 2011. Cathelicidin-BF, a snake cathelicidin-derived antimicrobial peptide, could be an excellent therapeutic agent for acne vulgaris. PLoS One, 6(7): e22120. doi: 10.1371/journal.pone.0022120
[202]	White JK, Muhammad T, Alsheim E, et al. 2022. A stable cyclized antimicrobial peptide derived from LL-37 with host immunomodulatory effects and activity against uropathogens. Cellular and Molecular Life Sciences, 79(8): 411. doi: 10.1007/s00018-022-04440-w
[203]	Whitesides GM, Boncheva M. 2002. Beyond molecules: self-assembly of mesoscopic and macroscopic components. Proceedings of the National Academy of Sciences of the United States of America, 99(8): 4769−4774.
[204]	Won A, Khan M, Gustin S, et al. 2011. Investigating the effects of L- to D-amino acid substitution and deamidation on the activity and membrane interactions of antimicrobial peptide anoplin. Biochimica et Biophysica Acta (BBA) - Biomembranes, 1808(6): 1592−1600. doi: 10.1016/j.bbamem.2010.11.010
[205]	Xiao X, Shao YT, Cheng X, et al. 2021. iAMP-CA2L: a new CNN-BiLSTM-SVM classifier based on cellular automata image for identifying antimicrobial peptides and their functional types. Briefings in Bioinformatics, 22(6): bbab209. doi: 10.1093/bib/bbab209
[206]	Xiao X, Wang P, Lin WZ, et al. 2013. iAMP-2L: a two-level multi-label classifier for identifying antimicrobial peptides and their functional types. Analytical Biochemistry, 436(2): 168−177. doi: 10.1016/j.ab.2013.01.019
[207]	Xie YP, He YP, Irwin PL, et al. 2011. Antibacterial activity and mechanism of action of zinc oxide nanoparticles against Campylobacter jejuni. Applied and Environmental Microbiology, 77(7): 2325–2331.
[208]	Xing MC, Ji MY, Hu JM, et al. 2020. Snake cathelicidin derived peptide inhibits zika virus infection. Frontiers in Microbiology, 11: 1871. doi: 10.3389/fmicb.2020.01871
[209]	Yafout M, Ousaid A, Khayati Y, et al. 2021. Gold nanoparticles as a drug delivery system for standard chemotherapeutics: a new lead for targeted pharmacological cancer treatments. Scientific African, 11: e00685. doi: 10.1016/j.sciaf.2020.e00685
[210]	Yakimov AP, Afanaseva AS, Khodorkovskiy MA, et al. 2016. Design of stable α-helical peptides and thermostable proteins in biotechnology and biomedicine. Acta Naturae, 8(4): 70−81. doi: 10.32607/20758251-2016-8-4-70-81
[211]	Yamashita R, Nishio M, Do RKG, et al. 2018. Convolutional neural networks: an overview and application in radiology. Insights into Imaging, 9(4): 611−629. doi: 10.1007/s13244-018-0639-9
[212]	Yan JL, Cai JX, Zhang B, et al. 2022. Recent progress in the discovery and design of antimicrobial peptides using traditional machine learning and deep learning. Antibiotics, 11(10): 1451. doi: 10.3390/antibiotics11101451
[213]	Yang XW, Lee WH, Zhang Y. 2012. Extremely abundant antimicrobial peptides existed in the skins of nine kinds of Chinese odorous frogs. Journal of Proteome Research, 11(1): 306−319. doi: 10.1021/pr200782u
[214]	Ye Z, Zhu X, Acosta S, et al. 2019. Self-assembly dynamics and antimicrobial activity of all L- and D-amino acid enantiomers of a designer peptide. Nanoscale, 11(1): 266−275. doi: 10.1039/C8NR07334A
[215]	Yin IX, Zhang J, Zhao IS, et al. 2020. The antibacterial mechanism of silver nanoparticles and its application in dentistry. International Journal of Nanomedicine, 15: 2555−2562. doi: 10.2147/IJN.S246764
[216]	Yin LM, Edwards MA, Li J, et al. 2012. Roles of hydrophobicity and charge distribution of cationic antimicrobial peptides in peptide-membrane interactions. Journal of Biological Chemistry, 287(10): 7738−7745. doi: 10.1074/jbc.M111.303602
[217]	Yokoo H, Hirano M, Ohoka N, et al. 2021. Structure-activity relationship study of amphipathic antimicrobial peptides using helix-destabilizing sarcosine. Journal of Peptide Science, 27(12): e3360. doi: 10.1002/psc.3360
[218]	Yu CY, Huang W, Li ZP, et al. 2016. Progress in self-assembling peptide-based nanomaterials for biomedical applications. Current Topics in Medicinal Chemistry, 16(3): 281−290.
[219]	Yuan BQ, Lu XY, Yang M, et al. 2022. A designed antimicrobial peptide with potential ability against methicillin resistant Staphylococcus aureus. Frontiers in Microbiology, 13: 1029366.
[220]	Zeng ZZ, Huang SH, Alezra V, et al. 2021. Antimicrobial peptides: triumphs and challenges. Future Medicinal Chemistry, 13(16): 1313−1315. doi: 10.4155/fmc-2021-0134
[221]	Zhang F, Guo ZL, Chen Y, et al. 2019. Effects of C-terminal amidation and heptapeptide ring on the biological activities and advanced structure of amurin-9KY, a novel antimicrobial peptide identified from the brown frog. Rana kunyuensis. Zoological Research, 40(3): 198−204.
[222]	Zhang QY, Yan ZB, Meng YM, et al. 2021. Antimicrobial peptides: mechanism of action, activity and clinical potential. Military Medical Research, 8(1): 48. doi: 10.1186/s40779-021-00343-2
[223]	Zhang ZY, Mu LX, Tang J, et al. 2013. A small peptide with therapeutic potential for inflammatory acne vulgaris. PLoS One, 8(8): e72923. doi: 10.1371/journal.pone.0072923
[224]	Zhao JS, Ge G, Huang YB, et al. 2022. Butelase 1-mediated enzymatic cyclization of antimicrobial peptides: improvements on stability and bioactivity. Journal of Agricultural and Food Chemistry, 70(50): 15869−15878. doi: 10.1021/acs.jafc.2c06588
[225]	Zhao XW, Wu HY, Lu HR, et al. 2013. LAMP: a database linking antimicrobial peptides. PLoS One, 8(6): e66557. doi: 10.1371/journal.pone.0066557
[226]	Zhao YY, Zhang M, Qiu S, et al. 2016. Antimicrobial activity and stability of the D-amino acid substituted derivatives of antimicrobial peptide polybia-MPI. AMB Express, 6(1): 122. doi: 10.1186/s13568-016-0295-8
[227]	Zhong C, Zhu NY, Zhu YW, et al. 2020. Antimicrobial peptides conjugated with fatty acids on the side chain of D-amino acid promises antimicrobial potency against multidrug-resistant bacteria. European Journal of Pharmaceutical Sciences, 141: 105123. doi: 10.1016/j.ejps.2019.105123
[228]	Zhu X, Ma Z, Wang JJ, et al. 2014. Importance of tryptophan in transforming an amphipathic peptide into a Pseudomonas aeruginosa-targeted antimicrobial peptide. PLoS One, 9(12): e114605. doi: 10.1371/journal.pone.0114605