Literature DB >> 34165973

Computational Methods and Tools in Antimicrobial Peptide Research.

Pietro G A Aronica1, Lauren M Reid1,2,3, Nirali Desai1,4, Jianguo Li1,5, Stephen J Fox1, Shilpa Yadahalli1, Jonathan W Essex2, Chandra S Verma1,6,7.   

Abstract

The evolution of antibiotic-resistant bacteria is an ongoing and troubling development that has increased the number of diseases and infections that risk going untreated. There is an urgent need to develop alternative strategies and treatments to address this issue. One class of molecules that is attracting significant interest is that of antimicrobial peptides (AMPs). Their design and development has been aided considerably by the applications of molecular models, and we review these here. These methods include the use of tools to explore the relationships between their structures, dynamics, and functions and the increasing application of machine learning and molecular dynamics simulations. This review compiles resources such as AMP databases, AMP-related web servers, and commonly used techniques, together aimed at aiding researchers in the area toward complementing experimental studies with computational approaches.

Entities:  

Keywords:  aggregation; antibiotic resistance; antimicrobial peptides; artificial intelligence; computational chemistry; machine learning; membranes; molecular dynamics; peptide engineering; peptides

Year:  2021        PMID: 34165973     DOI: 10.1021/acs.jcim.1c00175

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  7 in total

1.  Multiple Antimicrobial Effects of Hybrid Peptides Synthesized Based on the Sequence of Ribosomal S1 Protein from Staphylococcus aureus.

Authors:  Sergey V Kravchenko; Pavel A Domnin; Sergei Y Grishin; Alexander V Panfilov; Viacheslav N Azev; Leila G Mustaeva; Elena Y Gorbunova; Margarita I Kobyakova; Alexey K Surin; Anna V Glyakina; Roman S Fadeev; Svetlana A Ermolaeva; Oxana V Galzitskaya
Journal:  Int J Mol Sci       Date:  2022-01-04       Impact factor: 5.923

2.  Application of per-Residue Energy Decomposition to Design Peptide Inhibitors of PSD95 GK Domain.

Authors:  Miao Tian; Hongwei Li; Xiao Yan; Jing Gu; Pengfei Zheng; Sulan Luo; Dongting Zhangsun; Qiong Chen; Qin Ouyang
Journal:  Front Mol Biosci       Date:  2022-03-30

Review 3.  Emerging Computational Approaches for Antimicrobial Peptide Discovery.

Authors:  Guillermin Agüero-Chapin; Deborah Galpert-Cañizares; Dany Domínguez-Pérez; Yovani Marrero-Ponce; Gisselle Pérez-Machado; Marta Teijeira; Agostinho Antunes
Journal:  Antibiotics (Basel)       Date:  2022-07-13

Review 4.  Multidrug-Resistant Microbial Therapy Using Antimicrobial Peptides and the CRISPR/Cas9 System.

Authors:  Yared Abate Getahun; Destaw Asfaw Ali; Bihonegn Wodajnew Taye; Yismaw Alemie Alemayehu
Journal:  Vet Med (Auckl)       Date:  2022-08-11

5.  Antibacterial Peptide NP-6 Affects Staphylococcus aureus by Multiple Modes of Action.

Authors:  Xiaoyan Hou; Jianlong Li; Huaqiao Tang; Qingye Li; Guanghui Shen; Shanshan Li; Anjun Chen; Zixin Peng; Yu Zhang; Chaowei Li; Zhiqing Zhang
Journal:  Int J Mol Sci       Date:  2022-07-15       Impact factor: 6.208

6.  Mining Amphibian and Insect Transcriptomes for Antimicrobial Peptide Sequences with rAMPage.

Authors:  Diana Lin; Darcy Sutherland; Sambina Islam Aninta; Nathan Louie; Ka Ming Nip; Chenkai Li; Anat Yanai; Lauren Coombe; René L Warren; Caren C Helbing; Linda M N Hoang; Inanc Birol
Journal:  Antibiotics (Basel)       Date:  2022-07-15

7.  Machine Learning Guided Discovery of Non-Hemolytic Membrane Disruptive Anticancer Peptides.

Authors:  Elena Zakharova; Markus Orsi; Alice Capecchi; Jean-Louis Reymond
Journal:  ChemMedChem       Date:  2022-08-05       Impact factor: 3.540

  7 in total

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