Literature DB >> 27966278

Computational resources and tools for antimicrobial peptides.

Shicai Liu1, Linlin Fan1, Jian Sun1, Xingzhen Lao1, Heng Zheng1.   

Abstract

Antimicrobial peptides (AMPs), as evolutionarily conserved components of innate immune system, protect against pathogens including bacteria, fungi, viruses, and parasites. In general, AMPs are relatively small peptides (<10 kDa) with cationic nature and amphipathic structure and have modes of action different from traditional antibiotics. Up to now, there are more than 19 000 AMPs that have been reported, including those isolated from nature sources or by synthesis. They have been considered to be promising substitutes of conventional antibiotics in the quest to address the increasing occurrence of antibiotic resistance. However, most AMPs have modest direct antimicrobial activity, and their mechanisms of action, as well as their structure-activity relationships, are still poorly understood. Computational strategies are invaluable assets to provide insight into the activity of AMPs and thus exploit their potential as a new generation of antimicrobials. This article reviews the advances of AMP databases and computational tools for the prediction and design of new active AMPs.
Copyright © 2016 European Peptide Society and John Wiley & Sons, Ltd. Copyright © 2016 European Peptide Society and John Wiley & Sons, Ltd.

Entities:  

Keywords:  antimicrobial peptides; database screening; databases; design; machine learning methods; prediction

Mesh:

Substances:

Year:  2016        PMID: 27966278     DOI: 10.1002/psc.2947

Source DB:  PubMed          Journal:  J Pept Sci        ISSN: 1075-2617            Impact factor:   1.905


  15 in total

1.  dbAMP: an integrated resource for exploring antimicrobial peptides with functional activities and physicochemical properties on transcriptome and proteome data.

Authors:  Jhih-Hua Jhong; Yu-Hsiang Chi; Wen-Chi Li; Tsai-Hsuan Lin; Kai-Yao Huang; Tzong-Yi Lee
Journal:  Nucleic Acids Res       Date:  2019-01-08       Impact factor: 16.971

Review 2.  Peptides to Tackle Leishmaniasis: Current Status and Future Directions.

Authors:  Alberto A Robles-Loaiza; Edgar A Pinos-Tamayo; Bruno Mendes; Cátia Teixeira; Cláudia Alves; Paula Gomes; José R Almeida
Journal:  Int J Mol Sci       Date:  2021-04-22       Impact factor: 5.923

Review 3.  Promising Approaches to Optimize the Biological Properties of the Antimicrobial Peptide Esculentin-1a(1-21)NH2: Amino Acids Substitution and Conjugation to Nanoparticles.

Authors:  Bruno Casciaro; Floriana Cappiello; Mauro Cacciafesta; Maria Luisa Mangoni
Journal:  Front Chem       Date:  2017-04-25       Impact factor: 5.221

4.  Prediction and Characterization of Cationic Arginine-Rich Plant Antimicrobial Peptide SM-985 From Teosinte (Zea mays ssp. mexicana).

Authors:  Abdelrahman M Qutb; Feng Wei; Wubei Dong
Journal:  Front Microbiol       Date:  2020-06-19       Impact factor: 5.640

5.  Prediction of Antimicrobial Potential of a Chemically Modified Peptide From Its Tertiary Structure.

Authors:  Piyush Agrawal; Gajendra P S Raghava
Journal:  Front Microbiol       Date:  2018-10-26       Impact factor: 5.640

6.  A combined computational and experimental strategy identifies mutations conferring resistance to drugs targeting the BCR-ABL fusion protein.

Authors:  Jinxin Liu; Jianfeng Pei; Luhua Lai
Journal:  Commun Biol       Date:  2020-01-09

7.  Prediction and Activity of a Cationic α-Helix Antimicrobial Peptide ZM-804 from Maize.

Authors:  Mohamed F Hassan; Abdelrahman M Qutb; Wubei Dong
Journal:  Int J Mol Sci       Date:  2021-03-05       Impact factor: 5.923

Review 8.  Plant Antimicrobial Peptides: State of the Art, In Silico Prediction and Perspectives in the Omics Era.

Authors:  Carlos André Dos Santos-Silva; Luisa Zupin; Marx Oliveira-Lima; Lívia Maria Batista Vilela; João Pacifico Bezerra-Neto; José Ribamar Ferreira-Neto; José Diogo Cavalcanti Ferreira; Roberta Lane de Oliveira-Silva; Carolline de Jesús Pires; Flavia Figueira Aburjaile; Marianne Firmino de Oliveira; Ederson Akio Kido; Sergio Crovella; Ana Maria Benko-Iseppon
Journal:  Bioinform Biol Insights       Date:  2020-09-02

9.  Identification of biomarkers for the accurate and sensitive diagnosis of three bacterial pneumonia pathogens using in silico approaches.

Authors:  Olalekan Olanrewaju Bakare; Marshall Keyster; Ashley Pretorius
Journal:  BMC Mol Cell Biol       Date:  2020-11-20

10.  Antimicrobial Activity of Small Synthetic Peptides Based on the Marine Peptide Turgencin A: Prediction of Antimicrobial Peptide Sequences in a Natural Peptide and Strategy for Optimization of Potency.

Authors:  Ida K Ø Hansen; Tomas Lövdahl; Danijela Simonovic; Kine Ø Hansen; Aaron J C Andersen; Hege Devold; Céline S M Richard; Jeanette H Andersen; Morten B Strøm; Tor Haug
Journal:  Int J Mol Sci       Date:  2020-07-30       Impact factor: 5.923

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