Computational Approaches in Discovery & Design of Antimicrobial Peptides

• Other Authors: Antunes, Agostinho (Editor), Agüero-Chapin, Guillermin (Editor), Marrero-Ponce, Yovani (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
• Subjects: Research & information: general; Chemistry; cancer; tumor-homing peptide; in silico drug discovery; complex network; chemical space network; centrality measure; similarity searching; group fusion; motif discovery; starPep toolbox software; FOF1-ATP synthase; allosteric inhibition; structure-based drug design; evolutionary and PPI algorithms; peptide design; artificial intelligence; machine learning; AMPs; evolutionary algorithms; molecular descriptors; complex networks; proteogenomics; antimicrobial peptide; AMP discovery; genome mining; antimicrobial resistance; Streptomyces; secondary metabolites; genome; biosynthetic gene clusters; high-performance liquid chromatography (HPLC); mass spectrometry; amphipathic peptides; multifunctional; design; penetratins; antimicrobial; antiviral; anticancer; anti-inflammatory; cell-penetrating; non-toxic; cathelicidins; antimicrobial peptides; LL-37; biofilms; abscess model; skin model; reptiles; Apicomplexan; bioactive peptides; toxoplasmosis; cryptosporidiosis; malaria; antibacterial peptide; AMPs database; StarPep; Gram staining-based target; peptide library screening; human peptidome; redox system; Cryptococcus neoformans; ROS metabolism; ergosterol; synthetic antimicrobial peptides; n/a
• Online Access: DOAB: download the publication; DOAB: description of the publication

Antimicrobial resistance remains a major concern in medicine, especially during the COVID-19 pandemic, where microbial infections were frequent complications. To combat drug-resistant pathogens, there has been a renewed interest in the use of antimicrobial peptides (AMPs). This reprint focuses on the in-silico approaches used for the rational discovery and design of AMPs. Such computational methodologies range from classical homology-based and machine-learning prediction algorithms to complex similarity networks and evolutionary algorithms that use models of sequence evolution. Furthermore, the reprint explores the improvement of high-throughput screening techniques in the discovery of AMPs from biological samples, which has also led to the evolution of computational approaches that aid in this biodiscovery process. The reprint contains original research and review papers, which serve as valuable references for researchers dedicated to peptide drug development.