TY - CHAP
T1 - Unifying the classification of antimicrobial peptides in the antimicrobial peptide database
AU - Wang, Guangshun
N1 - Funding Information:
This study is supported by the NIH grants GM138552, AI137161, and the University of Nebraska Collaborative Initiation Award 2021.
Publisher Copyright:
© 2022 Elsevier Inc.
PY - 2022/1
Y1 - 2022/1
N2 - 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.
AB - 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.
KW - Antibiotics
KW - Antimicrobial peptides
KW - Classification
KW - Database
KW - Hydrophobic content
KW - Net charge
KW - Peptide discovery
KW - Peptide length
KW - Structure
UR - http://www.scopus.com/inward/record.url?scp=85117145394&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85117145394&partnerID=8YFLogxK
U2 - 10.1016/bs.mie.2021.09.006
DO - 10.1016/bs.mie.2021.09.006
M3 - Chapter
C2 - 35168785
AN - SCOPUS:85117145394
SN - 9780323901581
T3 - Methods in Enzymology
SP - 1
EP - 18
BT - Antimicrobial Peptides
A2 - Hicks, Leslie M.
PB - Academic Press Inc.
ER -