Abstract
Bioactive peptides (BPs) are peptides with hormonal or pharmacological properties. They play a key role in growth, metabolism, disease, aging and death by affecting digestion, endocrine, cardiovascular, immune and nervous systems. They show the potential therapeutic effects on blood pressure-lowering (ACE inhibitory), anticancer, antithrombotic, antibacterial, anti-inflammatory, antioxidant, antiobesity, anti-genotoxic and immunomodulatory. Companied by the fast development and wide applications of DNA sequencing method, a wealth of bioactive peptide sequences accumulated through empirical and bioinformatics approaches or an integrated approach. To store and facilitate the usage of bioactive peptide data, a series of databases have been established that concerned about different aspects of BPs. A variety of information including sequence, source, biological activity, toxicity, physical-chemical property, and structure is stored in these databases. This review summarizes the latest development of BPs databases and briefly introduces the characteristics of different databases, to help readers to retrieve the required information more easily. In addition, it also includes sequence analysis, structural simulation and activity prediction tools, which may be helpful for the design and discovery of new bioactive peptides.
Keywords: Therapeutic peptide, drug discovery, machine learning, database, activity prediction, antithrombotic.
Graphical Abstract
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