Database Commons

a catalog of worldwide biological databases

Natural products offer an important avenue to novel therapeutics against drug-resistant bacteria, viruses, fungi, parasites, and cancer. However, there are numerous hurdles and challenges in discovering such molecules, including antimicrobial peptides (AMPs). While a thorough characterization of AMPs is limited by the amount of material, existing technology, and researcher's expertise, peptide classification is complicated by incomplete information as well as different methods proposed for AMPs from bacteria, plants, and animals. This article describes unified classification schemes for natural AMPs on a common platform: the Antimicrobial Peptide Database (APD; https://aps.unmc.edu). The various criteria for these unified classifications include peptide biological source, biosynthesis machinery, biological activity, amino acid sequence, mechanism of action, and three-dimensional structure. To overcome the problem with a limited number of known 3D structures, a universal peptide classification has also been refined and executed in the APD database. This universal method, based on the spatial connection patterns of polypeptide chains, is independent of peptide source, size, activity, 3D structure, or mechanism of action. It facilitates information registration, naming, exchange, decoding, prediction, and design of novel antimicrobial peptides.

The antimicrobial peptide database (APD, http://aps.unmc.edu/AP/) is an original database initially online in 2003. The APD2 (2009 version) has been regularly updated and further expanded into the APD3. This database currently focuses on natural antimicrobial peptides (AMPs) with defined sequence and activity. It includes a total of 2619 AMPs with 261 bacteriocins from bacteria, 4 AMPs from archaea, 7 from protists, 13 from fungi, 321 from plants and 1972 animal host defense peptides. The APD3 contains 2169 antibacterial, 172 antiviral, 105 anti-HIV, 959 antifungal, 80 antiparasitic and 185 anticancer peptides. Newly annotated are AMPs with antibiofilm, antimalarial, anti-protist, insecticidal, spermicidal, chemotactic, wound healing, antioxidant and protease inhibiting properties. We also describe other searchable annotations, including target pathogens, molecule-binding partners, post-translational modifications and animal models. Amino acid profiles or signatures of natural AMPs are important for peptide classification, prediction and design. Finally, we summarize various database applications in research and education.

The antimicrobial peptide database (APD, http://aps.unmc.edu/AP/main.php) has been updated and expanded. It now hosts 1228 entries with 65 anticancer, 76 antiviral (53 anti-HIV), 327 antifungal and 944 antibacterial peptides. The second version of our database (APD2) allows users to search peptide families (e.g. bacteriocins, cyclotides, or defensins), peptide sources (e.g. fish, frogs or chicken), post-translationally modified peptides (e.g. amidation, oxidation, lipidation, glycosylation or d-amino acids), and peptide binding targets (e.g. membranes, proteins, DNA/RNA, LPS or sugars). Statistical analyses reveal that the frequently used amino acid residues (>10%) are Ala and Gly in bacterial peptides, Cys and Gly in plant peptides, Ala, Gly and Lys in insect peptides, and Leu, Ala, Gly and Lys in amphibian peptides. Using frequently occurring residues, we demonstrate database-aided peptide design in different ways. Among the three peptides designed, GLK-19 showed a higher activity against Escherichia coli than human LL-37.

An antimicrobial peptide database (APD) has been established based on an extensive literature search. It contains detailed information for 525 peptides (498 antibacterial, 155 antifungal, 28 antiviral and 18 antitumor). APD provides interactive interfaces for peptide query, prediction and design. It also provides statistical data for a select group of or all the peptides in the database. Peptide information can be searched using keywords such as peptide name, ID, length, net charge, hydrophobic percentage, key residue, unique sequence motif, structure and activity. APD is a useful tool for studying the structure-function relationship of antimicrobial peptides. The database can be accessed via a web-based browser at the URL: http://aps.unmc.edu/AP/main.html.