dbAMP 2.0: updated resource for antimicrobial peptides with an enhanced scanning method for genomic and proteomic data

Abstract

The last 18 months, or more, have seen a profound shift in our global experience, with many of us navigating a once-in-100-year pandemic. To date, COVID-19 remains a life-threatening pandemic with little to no targeted therapeutic recourse. The discovery of novel antiviral agents, such as vaccines and drugs, can provide therapeutic solutions to save human beings from severe infections; however, there is no specifically effective antiviral treatment confirmed for now. Thus, great attention has been paid to the use of natural or artificial antimicrobial peptides (AMPs) as these compounds are widely regarded as promising solutions for the treatment of harmful microorganisms. Given the biological significance of AMPs, it was obvious that there was a significant need for a single platform for identifying and engaging with AMP data. This led to the creation of the dbAMP platform that provides comprehensive information about AMPs and facilitates their investigation and analysis. To date, the dbAMP has accumulated 26 447 AMPs and 2262 antimicrobial proteins from 3044 organisms using both database integration and manual curation of >4579 articles. In addition, dbAMP facilitates the evaluation of AMP structures using I-TASSER for automated protein structure prediction and structure-based functional annotation, providing predictive structure information for clinical drug development. Next-generation sequencing (NGS) and third-generation sequencing have been applied to generate large-scale sequencing reads from various environments, enabling greatly improved analysis of genome structure. In this update, we launch an efficient online tool that can effectively identify AMPs from genome/metagenome and proteome data of all species in a short period. In conclusion, these improvements promote the dbAMP as one of the most abundant and comprehensively annotated resources for AMPs. The updated dbAMP is now freely accessible at http://awi.cuhk.edu.cn/dbAMP.

Figure 1.

Highlighted improvements in dbAMP 2.0. dbAMP is the most comprehensive resource for AMPs with this update bringing the total values for the AMP sequences and curated articles to >28 000 and >4500, respectively.

Figure 2.

The predicted structure viewer was integrated into the platform during this update. A case study describing the production of AMP, elafin (dbAMP_00487), which is the major antiviral protein in cervicovaginal lavage fluid, using human γδ T cells.

Figure 3.

Main pipeline workflow for AMPfinder. AMPfinder is an efficient online tool, which can accurately identify AMPs within genome/transcriptome and proteome data in a short period of time.

Figure 4.

The schematic framework underlying AMP target prediction. First, the user-input sequences are transformed into one of four different groups of peptide descriptors including amino acid composition (AAC), dipeptide composition (DPC), pseudo-amino acid composition (PAAC) and physiochemical properties (PHYC). These descriptors are then used as the feature vector for processing during the two-stage classification process that relies on GBDT and imbalanced learning. This evaluation will then produce a confidence value (ranging from 0 to 1 as the potency level for targeting different microbes) for each of the predicted AMPs.

Figure 5.

Summary of the properties of the peptides shown to target coronavirus and other viruses. (A) Length distribution of the anticoronavirus peptides (n = 187) and regular AVPs (n = 1664). To distinguish between AMPs and antimicrobial proteins, the entries with sequence length >100 amino acids (n = 1 for anticoronavirus peptides and n = 57 for other regular AVPs, respectively) are not shown in the histogram. (B) Average amino acid composition. Amino acids are categorized according to their physicochemical properties. (C) Dimension reduction of peptide sequences as extracted by tape, which reveals the differences between these peptides and where each point represents a peptide sequence with anticoronavirus (green) or regular antivirus (purple) activity.