Classification of Antimicrobial Peptides
There are numerous ways for classifying antimicrobial peptides.
1. Based on the biosynthetic machines
Natural peptides can be classified as gene coded and non-gene coded (i.e. multiple enzyme systems). This database focuses primarily on gene-coded peptides, which in some AMP scientists mind, are true AMPs. It is important to note that some non-ribosome synthesized peptide antibiotics in this database (e.g. gramicidins, colistin and daptomycin) are already in medical use.
2. Based on biological sources
Bacterial AMPs (bacteriocins), plant AMPs, animal AMPs. Animal AMPs are further classified into insect AMPs, amphibian AMPs, fish AMPs, reptile AMPs, mammal AMPs, etc based on source family names. The major and well-studied AMPs families in the animal kingdom are cathelicidins, defensins, and histatins. Bacteriocins are further classified (see Glossary).
3. Based on biological functions
Please refer to the main page of this database.
4. Based on peptide properties
In the absence of three-dimensional (3D) structural information, AMPs can be classified based on peptide properties such as charge, hydrophobicity, and length.
For example, there are cationic, neutral, and anionic peptides based on net charge.
There are hydrophobic, amphipathic, and hydrophilic peptides based on hydrophobicity.
Also, natural AMPs can be classified based on peptide size: ultra-small (2-10 aa), small (10-24 aa), medium (25-50 aa), and large (50-100 aa). AMPs greater than 100 aa are antimicrobial proteins.
5. Based on covalent bonding pattern
This universal classification system (UC) categorizes antimicrobial peptides (or peptide in genenal) into four classes (Wang, G, 2015).
(1) Class I (UCLL): linear one-chain peptides (e.g. LL-37 and magainins) or two linear peptides not connected via a covalent bond (e.g. enterocin L50).
(2) Class II (UCSS): sidechain-sidechain linked peptides (e.g. disulfide-containing defensins or ether bond-containing lantibiotics). A sidechain-sidechain connection can occur within a single peptide chain or between two different peptide chains.
(3) Class III (UCSB): polypeptide chains with a sidechain to backbone connection (e.g. bacterial lassos and fusaricidins).
(4) Class IV (UCBB): circular polypeptides with a peptide bond between the N- and C-termini (i.e., backbone-backbone connection). Circular peptides have been found in bacteria (e.g. AS-48), plants (e.g. cyclotides), and animals (e.g. theta-defensins).
Please refer to the orginal article for further classification of AMPs in each class (Wang G, 2015).
6. Based on 3D structure
In the Wang-edited book, AMPs are classified into four families: α, β, αβ, and non-αβ based on the types of secondary structures. The alpha family consists of AMPs with helical structures (e.g. magainins and LL-37). The beta family is composed of AMPs with beta-strands (e.g. human alpha-defensins). While the alphabeta family comprises both helical and beta-strands in the 3D structure (e.g. beta-defensins), the non-alphabeta family contains neither helical nor beta-strands (e.g. indolicidin). These four families of AMP structures are represented in the main page of this database . They are:
(1) frog magainin 2, alpha-helical (top left, PDB entry 2MAG);
(2) lactoferricin B, beta-sheet (top right, PDB entry 1LFC);
(3) plant defensin Psd1, alpha-beta structure (bottom left, PDB entry 1JKZ);
(4) bovine indolicidin, non-alpha-beta structure (bottom right, PDB entry 1G89).
The numbers of AMPs with such structures are annotated in the APD and listed in the statistics.
7. Based on molecular targets
AMPs can be broadly classified into two families: cell surface targeting peptides (e.g. nisins and temporins) and intracellular targeting peptides (e.g. Pro-rich peptides). Cell surface-targeting peptides, including both membrane-targeting and non-membrane targeting peptides, can be further classified based on specific targets such as cell wall/carbohydrates, lipids/membranes, and proteins/receptors. Likewise, intracellular targeting AMPs can be further classified based on the specific target molecules (e.g. proteins, DNA, and RNA). Further details can be found in the Antimicrobal Peptide book below.
(1) Wang, G. (2015) Improved methods for classification, prediction, and design of antimicrobial peptides. Methods Mol. Biol. 1268, 43-66. PubMed.
(2) Wang, G (2017) "Antimicrobial Peptides: Discovery, Design and Novel Therapeutic Strategies" (2nd version)CABI, England.