A Large-Scale Structural Classification of Antimicrobial Peptides

Lee, Hao-Ting; Lee, Chen-Che; Yang, Je-Ruei; Lai, Jim Z. C.; Chang, Kuan Y.

doi:10.1155/2015/475062

Cited by 131 publications

(126 citation statements)

References 25 publications

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“…The performance of predicting the AMPs of different types of organisms was compared with that of other web tools: iAMPpred [12], iAMP-2L [11], ADAM [19], DBAASP [30], MLAMP [31], and CAMPR3 [2]. It should be noted that DBSSAP can only predict peptides with sequence lengths less than 100; therefore, peptides longer than that were removed from our test set to fulfill the requirement.…”

Section: Comparison With Other Amp Prediction Toolsmentioning

confidence: 99%

“…AMPs are common in nature and have been discovered in almost all forms of life, from single-celled bacteria to multicellular organisms such as animals and plants [17]. In this study, we collected the positive dataset by capturing naturally existing and experimentally validated AMP sequences from different organisms from several databases, CAMP [7], APD [15], ADAM [19], and DRAMP [21]. We collected all the AMPs and deleted the duplicated ones.…”

Section: Data Collection and Preprocessingmentioning

confidence: 99%

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Characterization and Identification of Natural Antimicrobial Peptides on Different Organisms

Chung

Jhong

Wang

et al. 2020

IJMS

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Because of the rapid development of multidrug resistance, conventional antibiotics cannot kill pathogenic bacteria efficiently. New antibiotic treatments such as antimicrobial peptides (AMPs) can provide a possible solution to the antibiotic-resistance crisis. However, the identification of AMPs using experimental methods is expensive and time-consuming. Meanwhile, few studies use amino acid compositions (AACs) and physicochemical properties with different sequence lengths against different organisms to predict AMPs. Therefore, the major purpose of this study is to identify AMPs on seven categories of organisms, including amphibians, humans, fish, insects, plants, bacteria, and mammals. According to the one-rule attribute evaluation, the selected features were used to construct the predictive models based on the random forest algorithm. Compared to the accuracies of iAMP-2L (a web-server for identifying AMPs and their functional types), ADAM (a database of AMP), and MLAMP (a multi-label AMP classifier), the proposed method yielded higher than 92% in predicting AMPs on each category. Additionally, the sensitivities of the proposed models in the prediction of AMPs of seven organisms were higher than that of all other tools. Furthermore, several physicochemical properties (charge, hydrophobicity, polarity, polarizability, secondary structure, normalized van der Waals volume, and solvent accessibility) of AMPs were investigated according to their sequence lengths. As a result, the proposed method is a practical means to complement the existing tools in the characterization and identification of AMPs in different organisms.

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Section: Comparison With Other Amp Prediction Toolsmentioning

confidence: 99%

Section: Data Collection and Preprocessingmentioning

confidence: 99%

Characterization and Identification of Natural Antimicrobial Peptides on Different Organisms

Chung

Jhong

Wang

et al. 2020

IJMS

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show abstract

“…In order to evaluate the potential antimicrobial activity of the reassembled ZaLTP7, we used an array of antimicrobial peptide predictors, including CS-AMPPred (Porto, Pires, & Franco, 2012), CAMP (Waghu, Barai, Gurung, & Idicula-Thomas, 2016), iAMP-2L (Xiao et al, 2013), ADAM (Lee et al, 2015), and AntiBP2 (Lata, Mishra, & Raghava, 2010).…”

Section: Antimicrobial Activity Predictionmentioning

confidence: 99%

Structure‐guided identification of antimicrobial peptides in the spathe transcriptome of the non‐model plant, arum lily (Zantedeschia aethiopica)

et al. 2019

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Antimicrobial peptides (AMPs) are small molecules present in all living beings. Despite their huge sequence variability, AMPs present great structural conservation, mainly in cysteine‐stabilized families. Moreover, in non‐model plants, it is possible to detect cysteine‐stabilized AMPs (cs‐AMPs) with different sequences not covered by conventional searches. Here, we described a threading application for cs‐AMP identification in the non‐model arum lily (Zantedeschia aethiopica) plant, exploring the spathe transcriptome. By using the predicted proteins from the Z. aethiopica transcriptome as our primary source of sequences, we have filtered by using structural alignments of 12 putative cs‐AMP sequences. The two unreported sequences were submitted to PCR validation, and ZaLTP7 gene was confirmed. By using the structure alignments, we classified ZaLTP7 as an LTP type 2‐like. The successful threading application for cs‐AMP identification is an important advance in transcriptomic and proteomic data mining. Besides, the same approach could be applied to the use of NGS public data to discover molecules to combat multidrug‐resistant bacteria.

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“…Antimicrobial peptides (AMPs) serve as potent, broad spectrum antibiotics found in many eukaryotic animal species [1]. They comprise entities of the host defense system present in multiple classes of life forms and constitute a portion of the innate immune response in organisms [2].…”

Section: Introductionmentioning

confidence: 99%

Antimicrobial Peptides and Cancer: Potential Use of Antimicrobial-Like Peptides in Chemotherapy

2019

GJCT

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Antimicrobial peptides (AMPs) constitute host defense peptides found among insects, fish, amphibians, and mammals including man. The targets of AMPs are gram-negative and gram-positive bacteria, fungi, enveloped viruses, and transformed/cancerous cells. The AMPs are broad spectrum antibiotics which display the propensity to serve as therapeutic agents not only in infectious disease, but also in human cancer. AMPs demonstrate unique properties which include cell membrane penetration, destabilization of biological membranes, ability to form and/or interact with membrane channels, and the capability to modulate host immune responses. The three types of AMPs consists a) naturally-occurring; b) artificially synthesized; and c) cleaved peptide fragments from blood and extracellular matrix proteins. The present treatise presents one such example of an AMP-like peptide derived from a naturally-occurring human protein as a potential candidate for future cancer therapy. The biological activities of human AMP-like peptides as cancer therapeutic agents are reviewed and reported in multiple in vitro and in vivo cancer assays. The possibility of using such human protein-derived peptides as primary and adjunct cancer therapeutic agents is addressed.

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A Large-Scale Structural Classification of Antimicrobial Peptides

Cited by 131 publications

References 25 publications

Characterization and Identification of Natural Antimicrobial Peptides on Different Organisms

Characterization and Identification of Natural Antimicrobial Peptides on Different Organisms

Structure‐guided identification of antimicrobial peptides in the spathe transcriptome of the non‐model plant, arum lily (Zantedeschia aethiopica)

Antimicrobial Peptides and Cancer: Potential Use of Antimicrobial-Like Peptides in Chemotherapy

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