Peptide

Last updated
Drosomycin, an example of a peptide Drosomycin.svg
Drosomycin, an example of a peptide

Peptides are short chains of amino acids linked by peptide bonds. [1] [2] A polypeptide is a longer, continuous, unbranched peptide chain. [3] Polypeptides that have a molecular mass of 10,000 Da or more are called proteins. [4] Chains of fewer than twenty amino acids are called oligopeptides, and include dipeptides, tripeptides, and tetrapeptides. [5]

Contents

Amino acids comprise peptides as residues. [6] Peptides are usually "linear" with an N-terminal (amine group) and C-terminal (carboxyl group) residue at the ends. Cyclic peptides are a distinct class.

Classification

Peptides have been classified according to their sources and functions. [7] Some groups of peptides include plant peptides, bacterial/antibiotic peptides, fungal peptides, invertebrate peptides, amphibian/skin peptides, venom peptides, cancer/anticancer peptides, vaccine peptides, immune/inflammatory peptides, brain peptides, endocrine peptides, ingestive peptides, gastrointestinal peptides, cardiovascular peptides, renal peptides, respiratory peptides, opioid peptides, neurotrophic peptides, and blood–brain peptides. [8]

Some ribosomal peptides are subject to proteolysis. These function, typically in higher organisms, as hormones and signaling molecules. Some microbes produce peptides as antibiotics, such as microcins and bacteriocins. [9]

Peptides frequently have post-translational modifications such as phosphorylation, hydroxylation, sulfonation, palmitoylation, glycosylation, and disulfide formation. In general, peptides are linear, although lariat structures have been observed. [10] More exotic manipulations do occur, such as racemization of L-amino acids to D-amino acids in platypus venom. [11]

Nonribosomal peptides are assembled by enzymes, not the ribosome. A common non-ribosomal peptide is glutathione, a component of the antioxidant defenses of most aerobic organisms. [12] Other nonribosomal peptides are most common in unicellular organisms, plants, and fungi and are synthesized by modular enzyme complexes called nonribosomal peptide synthetases. [13]

These complexes are often laid out in a similar fashion, and they can contain many different modules to perform a diverse set of chemical manipulations on the developing product. [14] These peptides are often cyclic and can have highly complex cyclic structures, although linear nonribosomal peptides are also common. Since the system is closely related to the machinery for building fatty acids and polyketides, hybrid compounds are often found. The presence of oxazoles or thiazoles often indicates that the compound was synthesized in this fashion. [15]

Peptones are derived from animal milk or meat digested by proteolysis. [16] In addition to containing small peptides, the resulting material includes fats, metals, salts, vitamins, and many other biological compounds. Peptones are used in nutrient media for growing bacteria and fungi. [17]

Peptide fragments refer to fragments of proteins that are used to identify or quantify the source protein. [18] Often these are the products of enzymatic degradation performed in the laboratory on a controlled sample, but can also be forensic or paleontological samples that have been degraded by natural effects. [19] [20]

Chemical synthesis

Solid-phase peptide synthesis on a rink amide resin using Fmoc-a-amine-protected amino acid Peptide Synthesis.svg
Solid-phase peptide synthesis on a rink amide resin using Fmoc-α-amine-protected amino acid

Protein–peptide interactions

Example of a protein (orange) and peptide (green) interaction. Obtained from Propedia: a peptide-protein interactions database. Protein-peptide interaction.png
Example of a protein (orange) and peptide (green) interaction. Obtained from Propedia: a peptide-protein interactions database.

Peptides can perform interactions with proteins and other macromolecules. They are responsible for numerous important functions in human cells, such as cell signaling, and act as immune modulators. [22] Indeed, studies have reported that 15-40% of all protein–protein interactions in human cells are mediated by peptides. [23] Additionally, it is estimated that at least 10% of the pharmaceutical market is based on peptide products. [22]

Applications of machine learning in peptide prediction

Machine learning and deep learning methods are increasingly used to classify, screen and design peptides from sequence- or structure-derived data, particularly when experimental screening is costly, slow or difficult to scale. [24] [25] [26] A typical computational pipeline includes the preparation of benchmark datasets, conversion of peptide sequences or structures into numerical representations, model training, and performance evaluation. [26] Common representations include amino acid composition, dipeptide composition, pseudo-amino acid composition, physicochemical descriptors, substitution matrices, molecular fingerprints and learned embeddings from protein or peptide language models. [26] [27]

These approaches have been applied to several peptide classes, including antimicrobial peptides, cell-penetrating peptides, blood–brain barrier-penetrating peptides, anticancer peptides, antiviral peptides and other functional peptide groups. [26] For example, BrainPepPass uses supervised dimensionality reduction and extreme gradient boosting to predict blood–brain barrier-penetrating peptides from molecular descriptors of natural and chemically modified peptides. [28] For cell-penetrating peptides, ConvBoost-CPP combines a convolutional neural network with XGBoost and uses descriptors such as nitrogen, oxygen and Eisenberg hydrophobicity; in the reported dataset, this descriptor combination increased independent-test accuracy from 82.6% to 91.3%. [29] In antimicrobial peptide research, artificial intelligence methods have expanded from classical machine-learning classifiers to large language models, graph neural networks, diffusion models and structure-guided design strategies. [25] Important limitations include small or biased datasets, inconsistent benchmarking protocols, uncertain negative samples, and limited interpretability of some predictive models. [26] [25]

Molecular properties and chemical space of peptides

The chemical space of peptides can be described as a multidimensional descriptor or fingerprint space in which distances between molecules approximate chemical or functional similarity. [30] [31] Peptide chemical space may be mapped from amino acid sequences, three-dimensional molecular structures, or both. Molecular properties used for this purpose include molecular weight, logP, logD, topological polar surface area, hydrogen-bond donors and acceptors, nitrogen and oxygen atom counts, charge, hydrophobicity, secondary-structure-related features and molecular fingerprints. [28] [31] Dimensionality-reduction methods such as principal component analysis, t-SNE, UMAP and supervised manifold learning, often combined with clustering or similarity networks, are used to visualize peptide libraries and identify groups with related properties or activities. [32] [33] [34] [31]

Peptides differ from many small molecules because their residue sequence, amide backbone, conformational flexibility and chemical modifications jointly influence bioactivity, bioavailability and membrane permeability. [31] Sequence-based notations, including FASTA, HELM and BILN, can encode canonical and modified peptides for computational analysis, whereas atom-based strings and graph representations can capture connectivity, stereochemistry and structural constraints. [31] [27] Chemical modifications such as cyclization, N-methylation, incorporation of non-natural amino acids and site-specific modifications can shift a peptide's position in chemical space and alter properties such as solubility, stability, permeability and target affinity. [31] [27] Because unrelated peptide classes may partially overlap in descriptor space, chemical-space analysis is also used to investigate shared regions of bioactivity and to support virtual screening, repurposing and peptide design. [31]

Example families

The peptide families in this section are ribosomal peptides, usually with hormonal activity. All of these peptides are synthesized by cells as longer "propeptides" or "proproteins" and truncated prior to exiting the cell. They are released into the bloodstream where they perform their signaling functions. [35]

Antimicrobial peptides

Tachykinin peptides

Vasoactive intestinal peptides

Opioid peptides

Calcitonin peptides

Self-assembling peptides

Other peptides

Terminology

Length

Several terms related to peptides have no strict length definitions, and there is often overlap in their usage:[ citation needed ]

Number of amino acids

A tripeptide (example Val-Gly-Ala) with
green marked amino end (L-valine) and
blue marked carboxyl end (L-alanine) Tripeptide Val-Gly-Ala Formula V1.svg
A tripeptide (example Val-Gly-Ala) with
green marked amino end (L-valine) and
blue marked carboxyl end (L-alanine)

Peptides and proteins are often described by the number of amino acids in their chain, e.g. a protein with 158 amino acids may be described as a "158 amino-acid-long protein". Peptides of specific shorter lengths are named using IUPAC numerical multiplier prefixes:

The same words are also used to describe a group of residues in a larger polypeptide (e.g., RGD motif).

Function

See also

References

  1. Hamley, I. W. (September 2020). introduction to Peptide Science. Wiley. ISBN   978-1-119-69817-3.
  2. Nelson, David L.; Cox, Michael M. (2005). Principles of Biochemistry (4th ed.). New York: W. H. Freeman. ISBN   0-7167-4339-6.
  3. Saladin, K. (13 January 2011). Anatomy & physiology: the unity of form and function (6th ed.). McGraw-Hill. p. 67. ISBN   978-0-07-337825-1.
  4. IUPAC , Compendium of Chemical Terminology , 5th ed. (the "Gold Book") (2025). Online version: (2006) " proteins ". doi : 10.1351/goldbook.P04898.
  5. Ardejani, Maziar S.; Orner, Brendan P. (2013-05-03). "Obey the Peptide Assembly Rules". Science. 340 (6132): 561–562. Bibcode:2013Sci...340..561A. doi:10.1126/science.1237708. ISSN   0036-8075. PMID   23641105. S2CID   206548864.
  6. IUPAC , Compendium of Chemical Terminology , 5th ed. (the "Gold Book") (2025). Online version: (2006) " amino-acid residue in a polypeptide ". doi : 10.1351/goldbook.A00279.
  7. Hamley, I. W. (September 2020). introduction to Peptide Science. Wiley. ISBN   978-1-119-69817-3.Hamley, I. W. (September 2020). introduction to Peptide Science. Wiley. ISBN   978-1-119-69817-3.
  8. Abba J. Kastin, ed. (2013). Handbook of Biologically Active Peptides (2nd ed.). Elsevier Science. ISBN   978-0-12-385095-9.
  9. Duquesne S, Destoumieux-Garzón D, Peduzzi J, Rebuffat S (August 2007). "Microcins, gene-encoded antibacterial peptides from enterobacteria". Natural Product Reports. 24 (4): 708–34. doi:10.1039/b516237h. PMID   17653356.
  10. Pons M, Feliz M, Antònia Molins M, Giralt E (May 1991). "Conformational analysis of bacitracin A, a naturally occurring lariat". Biopolymers. 31 (6): 605–12. doi:10.1002/bip.360310604. PMID   1932561. S2CID   10924338.
  11. Torres AM, Menz I, Alewood PF, et al. (July 2002). "D-Amino acid residue in the C-type natriuretic peptide from the venom of the mammal, Ornithorhynchus anatinus, the Australian platypus". FEBS Letters. 524 (1–3): 172–6. Bibcode:2002FEBSL.524..172T. doi:10.1016/S0014-5793(02)03050-8. PMID   12135762. S2CID   3015474.
  12. Meister A, Anderson ME; Anderson (1983). "Glutathione". Annual Review of Biochemistry. 52 (1): 711–60. doi:10.1146/annurev.bi.52.070183.003431. PMID   6137189.
  13. Hahn M, Stachelhaus T; Stachelhaus (November 2004). "Selective interaction between nonribosomal peptide synthetases is facilitated by short communication-mediating domains". Proceedings of the National Academy of Sciences of the United States of America. 101 (44): 15585–90. Bibcode:2004PNAS..10115585H. doi: 10.1073/pnas.0404932101 . PMC   524835 . PMID   15498872.
  14. Finking R, Marahiel MA; Marahiel (2004). "Biosynthesis of nonribosomal peptides1". Annual Review of Microbiology. 58 (1): 453–88. doi:10.1146/annurev.micro.58.030603.123615. PMID   15487945.
  15. Du L, Shen B; Shen (March 2001). "Biosynthesis of hybrid peptide-polyketide natural products". Current Opinion in Drug Discovery & Development. 4 (2): 215–28. PMID   11378961.
  16. "UsvPeptides- USVPeptides is a leading pharmaceutical company in India". USVPeptides.
  17. Payne, J. W.; Rose, Anthony H.; Tempest, D. W. (27 September 1974). "Peptides and micro-organisms". Advances in Microbial Physiology, Volume 13. Vol. 13. Oxford, England: Elsevier Science. pp. 55–160. doi:10.1016/S0065-2911(08)60038-7. ISBN   978-0-08-057971-9. OCLC   1049559483. PMID   775944.{{cite book}}: |journal= ignored (help)
  18. Hummel J, Niemann M, Wienkoop S, Schulze W, Steinhauser D, Selbig J, Walther D, Weckwerth W (2007). "ProMEX: a mass spectral reference database for proteins and protein phosphorylation sites". BMC Bioinformatics. 8 (1) 216. Bibcode:2007BMCBi...8..216H. doi: 10.1186/1471-2105-8-216 . PMC   1920535 . PMID   17587460.
  19. Webster J, Oxley D; Oxley (2005). "Peptide Mass Fingerprinting" . Chemical Genomics. Methods in Molecular Biology. Vol. 310. pp. 227–40. doi:10.1007/978-1-59259-948-6_16. ISBN   978-1-58829-399-2. PMID   16350956.
  20. Marquet P, Lachâtre G; Lachâtre (October 1999). "Liquid chromatography-mass spectrometry: potential in forensic and clinical toxicology". Journal of Chromatography B. 733 (1–2): 93–118. doi:10.1016/S0378-4347(99)00147-4. PMID   10572976.
  21. "Propedia v2.3 - Peptide-Protein Interactions Database". bioinfo.dcc.ufmg.br. Retrieved 2023-03-28.
  22. 1 2 Martins, Pedro M.; Santos, Lucianna H.; Mariano, Diego; Queiroz, Felippe C.; Bastos, Luana L.; Gomes, Isabela de S.; Fischer, Pedro H. C.; Rocha, Rafael E. O.; Silveira, Sabrina A.; de Lima, Leonardo H. F.; de Magalhães, Mariana T. Q.; Oliveira, Maria G. A.; de Melo-Minardi, Raquel C. (December 2021). "Propedia: a database for protein–peptide identification based on a hybrid clustering algorithm". BMC Bioinformatics. 22 (1) 1. doi: 10.1186/s12859-020-03881-z . ISSN   1471-2105. PMC   7776311 . PMID   33388027.
  23. Neduva, Victor; Linding, Rune; Su-Angrand, Isabelle; Stark, Alexander; Masi, Federico de; Gibson, Toby J; Lewis, Joe; Serrano, Luis; Russell, Robert B (2005-11-15). Matthews, Rowena (ed.). "Systematic Discovery of New Recognition Peptides Mediating Protein Interaction Networks". PLOS Biology. 3 (12) e405. doi: 10.1371/journal.pbio.0030405 . ISSN   1545-7885. PMC   1283537 . PMID   16279839.
  24. Wang, Jiaqi; Liu, Zihan; Zhao, Shuang; Xu, Tengyan; Wang, Huaimin; Li, Stan Z.; Li, Wenbin (November 2023). "Deep Learning Empowers the Discovery of Self-Assembling Peptides with Over 10 Trillion Sequences". Advanced Science. 10 (31) 2301544. doi:10.1002/advs.202301544. ISSN   2198-3844. PMC   10625107 . PMID   37749875.
  25. 1 2 3 Brizuela, Carlos A.; Liu, Gary; Stokes, Jonathan M.; de la Fuente-Nunez, Cesar (2025). "AI methods for antimicrobial peptides: progress and challenges". Microbial Biotechnology. 18 (1) e70072. doi:10.1111/1751-7915.70072. PMC   11702388 . PMID   39754551.
  26. 1 2 3 4 5 Asim, Muhammad Nabeel; Asif, Tayyaba; Mehmood, Faiza; Dengel, Andreas (2025). "Peptide classification landscape: an in-depth systematic literature review on peptide types, databases, datasets, predictors architectures and performance". Computers in Biology and Medicine. 188 109821. doi:10.1016/j.compbiomed.2025.109821. PMID   39987697.
  27. 1 2 3 Erckes, Vanessa; Abderrahmane, Massina; Jusot, Maud; Steuer, Christian; Ochoa, Rodrigo (2026). "Peptide cheminformatics tools: making computational tasks accessible in peptide drug discovery". Drug Discovery Today. 31 (2): 104612. doi:10.1016/j.drudis.2026.104612. PMID   41577169.{{cite journal}}: CS1 maint: article number as page number (link)
  28. 1 2 de Oliveira, Ewerton Cristhian Lima; Hirmz, Hannah; Wynendaele, Evelien; Seixas Feio, Juliana Auzier; Moreira, Igor Matheus Souza; da Costa, Kauê Santana; Lima, Anderson H.; De Spiegeleer, Bart; de Souza de Sales Junior, Claudomiro (2024). "BrainPepPass: a framework based on supervised dimensionality reduction for predicting blood-brain barrier-penetrating peptides". Journal of Chemical Information and Modeling. 64 (7): 2368–2382. doi:10.1021/acs.jcim.3c00951. hdl:1854/LU-01HFVTBVPHRM4954PJPGBK3ZHD. PMID   38054399.
  29. Seixas Feio, Juliana Auzier; de Oliveira, Ewerton Cristhian Lima; de Sales Junior, Claudomiro de Souza; da Costa, Kauê Santana; e Lima, Anderson Henrique Lima (2024). "Investigating molecular descriptors in cell-penetrating peptides prediction with deep learning: employing N, O, and hydrophobicity according to the Eisenberg scale". PLOS ONE. 19 (6): e0305253. Bibcode:2024PLoSO..1905253S. doi: 10.1371/journal.pone.0305253 . PMC   11175476 . PMID   38870192.{{cite journal}}: CS1 maint: article number as page number (link)
  30. Orsi, Markus; Reymond, Jean-Louis (January 2025). "Navigating a 1E+60 Chemical Space of Peptide/Peptoid Oligomers". Molecular Informatics. 44 (1) e202400186. doi:10.1002/minf.202400186. ISSN   1868-1743. PMC   11733718 . PMID   39390672.
  31. 1 2 3 4 5 6 7 de Oliveira, Ewerton Cristhian Lima; Feio, Juliana Auzier Seixas; Coelho, Gabriel Pereira; do Nascimento, Lidiane Diniz; De Spiegeleer, Anton; Sales, Claudomiro; Lima, Anderson Henrique; Rodrigues, Caio Marcos Flexa; Wynendaele, Evelien; De Spiegeleer, Bart; Costa, Kauê (2026). "Navigating in the chemical space of peptides: computational strategies and molecular features to unveil their functional and drug-like properties". Physical Chemistry Chemical Physics. doi:10.1039/D5CP04611D.
  32. Romero, Maylin; Marrero-Ponce, Yovani; Martinez-Rios, Felix; Agüero-Chapin, Guillermin; Aguilera-Mendoza, Longendri; Chavez, Edgar; Márquez, Edgar A.; Pérez-Pérez, Noel; Mora, José R.; Contreras-Torres, Ernesto; Barigye, Stephen J. (2025-11-18). "Half-Space Proximal Networks (HSPNs): A Proxy for Multi-Query Similarity Searching Models Predicting Tumor-Homing Peptides". ACS Omega. 10 (45): 54389–54404. doi: 10.1021/acsomega.5c07055 . ISSN   2470-1343. PMC   12631478 . PMID   41280784.
  33. Descamps, Amélie; Hirmz, Hannah; de Oliveira, Ewerton; De Spiegeleer, Anton; Feio, Juliana; da Costa, Kaue; De Spiegeleer, Bart; Wynendaele, Evelien (2025-07-01). "Beyond Molecular Weight: Peptide Characteristics Influencing the Sensitivity of Retention to Changes in Organic Solvent in Reversed-Phase Chromatography". ACS Omega. 10 (25): 27089–27097. doi: 10.1021/acsomega.5c02327 . ISSN   2470-1343. PMC   12223815 . PMID   40621014.
  34. Orsi, Markus; Reymond, Jean-Louis (January 2025). "Navigating a 1E+60 Chemical Space of Peptide/Peptoid Oligomers". Molecular Informatics. 44 (1) e202400186. doi:10.1002/minf.202400186. ISSN   1868-1743. PMC   11733718 . PMID   39390672.
  35. "Protein Synthesis: From Ribosomes to Post-Translational Modifications". BiologyInsights. 2025-01-11. Retrieved 2025-04-04.
  36. Tao, Kai; Makam, Pandeeswar; Aizen, Ruth; Gazit, Ehud (17 Nov 2017). "Self-assembling peptide semiconductors". Science. 358 (6365) eaam9756. doi:10.1126/science.aam9756. PMC   5712217 . PMID   29146781.
  37. Tao, Kai; Levin, Aviad; Adler-Abramovich, Lihi; Gazit, Ehud (26 Apr 2016). "Fmoc-modified amino acids and short peptides: simple bio-inspired building blocks for the fabrication of functional materials". Chem. Soc. Rev. 45 (14): 3935–3953. doi:10.1039/C5CS00889A. PMID   27115033.
  38. Tao, Kai; Wang, Jiqian; Zhou, Peng; Wang, Chengdong; Xu, Hai; Zhao, Xiubo; Lu, Jian R. (February 10, 2011). "Self-Assembly of Short Aβ(16−22) Peptides: Effect of Terminal Capping and the Role of Electrostatic Interaction". Langmuir. 27 (6): 2723–2730. doi:10.1021/la1034273. PMID   21309606.
  39. Ian Hamley (2011). "Self-Assembly of Amphiphilic Peptides" (PDF). Soft Matter. 7 (9): 4122–4138. Bibcode:2011SMat....7.4122H. doi:10.1039/C0SM01218A.
  40. Kai Tao; Guy Jacoby; Luba Burlaka; Roy Beck; Ehud Gazit (July 26, 2016). "Design of Controllable Bio-Inspired Chiroptic Self-Assemblies". Biomacromolecules. 17 (9): 2937–2945. doi:10.1021/acs.biomac.6b00752. PMID   27461453.
  41. Kai Tao; Aviad Levin; Guy Jacoby; Roy Beck; Ehud Gazit (23 August 2016). "Entropic Phase Transitions with Stable Twisted Intermediates of Bio-Inspired Self-Assembly". Chem. Eur. J. 22 (43): 15237–15241. doi:10.1002/chem.201603882. PMID   27550381.
  42. Donghui Jia; Kai Tao; Jiqian Wang; Chengdong Wang; Xiubo Zhao; Mohammed Yaseen; Hai Xu; Guohe Que; John R. P. Webster; Jian R. Lu (June 16, 2011). "Dynamic Adsorption and Structure of Interfacial Bilayers Adsorbed from Lipopeptide Surfactants at the Hydrophilic Silicon/Water Interface: Effect of the Headgroup Length". Langmuir. 27 (14): 8798–8809. doi:10.1021/la105129m. PMID   21675796.
  43. Heitz, Marc; Javor, Sacha; Darbre, Tamis; Reymond, Jean-Louis (2019-08-21). "Stereoselective pH Responsive Peptide Dendrimers for siRNA Transfection". Bioconjugate Chemistry. 30 (8): 2165–2182. doi:10.1021/acs.bioconjchem.9b00403. ISSN   1043-1802. PMID   31398014. S2CID   199519310.
  44. Boelsma E, Kloek J; Kloek (March 2009). "Lactotripeptides and antihypertensive effects: a critical review". The British Journal of Nutrition. 101 (6): 776–86. doi: 10.1017/S0007114508137722 . PMID   19061526.
  45. Xu JY, Qin LQ, Wang PY, Li W, Chang C (October 2008). "Effect of milk tripeptides on blood pressure: a meta-analysis of randomized controlled trials". Nutrition. 24 (10): 933–40. doi:10.1016/j.nut.2008.04.004. PMID   18562172.
  46. Pripp AH (2008). "Effect of peptides derived from food proteins on blood pressure: a meta-analysis of randomized controlled trials". Food & Nutrition Research. 52 10.3402/fnr.v52i0.1641. doi:10.3402/fnr.v52i0.1641. PMC   2596738 . PMID   19109662.
  47. Engberink MF, Schouten EG, Kok FJ, van Mierlo LA, Brouwer IA, Geleijnse JM (February 2008). "Lactotripeptides show no effect on human blood pressure: results from a double-blind randomized controlled trial". Hypertension. 51 (2): 399–405. doi: 10.1161/HYPERTENSIONAHA.107.098988 . PMID   18086944.
  48. Wu, Hongzhong; Ren, Chunyan; Yang, Fang; Qin, Yufeng; Zhang, Yuanxing; Liu, Jianwen (April 2016). "Extraction and identification of collagen-derived peptides with hematopoietic activity from Colla Corii Asini". Journal of Ethnopharmacology. 182: 129–136. doi:10.1016/j.jep.2016.02.019. PMID   26911525.