Current Pharmacology Reports, Год журнала: 2023, Номер 9(6), С. 433 - 454
Опубликована: Сен. 23, 2023
Язык: Английский
European Journal of Medicinal Chemistry, Год журнала: 2023, Номер 255, С. 115377 - 115377
Опубликована: Апрель 20, 2023
Язык: Английский
Процитировано
121
Antibiotics, Год журнала: 2022, Номер 11(10), С. 1451 - 1451
Опубликована: Окт. 21, 2022
Antimicrobial resistance has become a critical global health problem due to the abuse of conventional antibiotics and rise multi-drug-resistant microbes. peptides (AMPs) are group natural that show promise as next-generation their low toxicity host, broad spectrum biological activity, including antibacterial, antifungal, antiviral, anti-parasitic activities, great therapeutic potential, such anticancer, anti-inflammatory, etc. Most importantly, AMPs kill bacteria by damaging cell membranes using multiple mechanisms action rather than targeting single molecule or pathway, making it difficult for bacterial drug develop. However, experimental approaches used discover design new very expensive time-consuming. In recent years, there been considerable interest in silico methods, traditional machine learning (ML) deep (DL) approaches, discovery. While few papers summarizing computational AMP prediction none them focused on DL methods. this review, we aim survey latest methods achieved approaches. First, biology background is introduced, then various feature encoding represent features peptide sequences presented. We explain most popular techniques highlight works based classify novel sequences. Finally, discuss limitations challenges prediction.
Язык: Английский
Процитировано
73
International Journal of Molecular Sciences, Год журнала: 2023, Номер 24(6), С. 5753 - 5753
Опубликована: Март 17, 2023
Antimicrobial peptides (AMPs) are short, mainly positively charged, amphipathic molecules. AMPs important effectors of the immune response in insects with a broad spectrum antibacterial, antifungal, and antiparasitic activity. In addition to these well-known roles, exhibit many other, often unobvious, functions host. They support elimination viral infections. participate regulation brain-controlled processes, e.g., sleep non-associative learning. By influencing neuronal health, communication, activity, they can affect functioning insect nervous system. Expansion AMP repertoire loss their specificity is connected aging process lifespan insects. Moreover, take part maintaining gut homeostasis, regulating number endosymbionts as well reducing foreign microbiota. turn, presence venom prevents spread infection social insects, where prey may be source pathogens.
Язык: Английский
Процитировано
65
Microbiological Research, Год журнала: 2024, Номер 286, С. 127822 - 127822
Опубликована: Июнь 26, 2024
Antibiotic resistance represents a global health threat, challenging the efficacy of traditional antimicrobial agents and necessitating innovative approaches to combat infectious diseases. Among these alternatives, peptides have emerged as promising candidates against resistant pathogens. Unlike antibiotics with only one target, can use different mechanisms destroy bacteria, low toxicity mammalian cells compared many conventional antibiotics. Antimicrobial (AMPs) encouraging antibacterial properties are currently employed in clinical treatment pathogen infection, cancer, wound healing, cosmetics, or biotechnology. This review summarizes discusses drug resistance, limitations challenges AMPs peptide applications for combating drug-resistant bacterial infections, strategies enhance their capabilities.
Язык: Английский
Процитировано
53
Journal of Pharmaceutical Analysis, Год журнала: 2024, Номер 15(1), С. 101046 - 101046
Опубликована: Июль 18, 2024
Natural antimicrobial peptides (AMPs) are promising candidates for the development of a new generation antimicrobials to combat antibiotic-resistant pathogens. They have found extensive applications in fields medicine, food, and agriculture. However, efficiently screening AMPs from natural sources poses several challenges, including low efficiency high antibiotic resistance. This review focuses on action mechanisms AMPs, both through membrane non-membrane routes. We thoroughly examine various highly efficient AMP methods, whole-bacterial adsorption binding, cell chromatography (CMC), phospholipid membrane-mediated capillary electrophoresis (CE), colorimetric assays, thin layer (TLC), fluorescence-based screening, genetic sequencing-based analysis, computational mining databases, virtual methods. Additionally, we discuss potential developmental enhancing discovery. provides comprehensive framework identifying within complex product systems.
Язык: Английский
Процитировано
53
Journal of Chemical Theory and Computation, Год журнала: 2023, Номер 19(8), С. 2161 - 2185
Опубликована: Апрель 4, 2023
Molecular dynamics simulations of membranes and membrane proteins serve as computational microscopes, revealing coordinated events at the interface. As G protein-coupled receptors, ion channels, transporters, membrane-bound enzymes are important drug targets, understanding their binding action mechanisms in a realistic becomes critical. Advances materials science physical chemistry further demand an atomistic lipid domains interactions between membranes. Despite wide range simulation studies, generating complex assembly remains challenging. Here, we review capability CHARMM-GUI
Язык: Английский
Процитировано
49
Bioorganic Chemistry, Год журнала: 2024, Номер 145, С. 107151 - 107151
Опубликована: Янв. 27, 2024
Язык: Английский
Процитировано
27
Science Advances, Год журнала: 2025, Номер 11(6)
Опубликована: Фев. 5, 2025
Artificial intelligence holds great promise for the design of antimicrobial peptides (AMPs); however, current models face limitations in generating AMPs with sufficient novelty and diversity, they are rarely applied to generation antifungal peptides. Here, we develop an alternative pipeline grounded a diffusion model molecular dynamics de novo AMPs. The generated by our have lower similarity identity than those other reported methodologies. Among 40 synthesized experimental validation, 25 exhibit either antibacterial or activity. AMP-29 shows selective activity against Candida glabrata vivo efficacy murine skin infection model. AMP-24 exhibits potent vitro Gram-negative bacteria both lung Acinetobacter baumannii models. proposed approach offers designing diverse counteract threat antibiotic resistance.
Язык: Английский
Процитировано
8
Microbial Biotechnology, Год журнала: 2025, Номер 18(1)
Опубликована: Янв. 1, 2025
ABSTRACT Antimicrobial peptides (AMPs) are promising candidates to combat multidrug‐resistant pathogens. However, the high cost of extensive wet‐lab screening has made AI methods for identifying and designing AMPs increasingly important, with machine learning (ML) techniques playing a crucial role. approaches have recently revolutionised this field by accelerating discovery new anti‐infective activity, particularly in preclinical mouse models. Initially, classical ML dominated field, but there been shift towards deep (DL) Despite significant contributions, existing reviews not thoroughly explored potential large language models (LLMs), graph neural networks (GNNs) structure‐guided AMP design. This review aims fill that gap providing comprehensive overview latest advancements, challenges opportunities using methods, particular emphasis on LLMs, GNNs We discuss limitations current highlight most relevant topics address coming years
Язык: Английский
Процитировано
5
Advanced Biology, Год журнала: 2025, Номер unknown
Опубликована: Фев. 6, 2025
Abstract The increasing morbidity and mortality caused by multidrug‐resistant bacteria alerts human beings to the fact that conventional antibiotics are no longer reliable effective alternatives imperatively needed. Owing wide range of sources, diverse structures, unique mode action, antimicrobial peptides have been highly anticipated extensively studied in recent years. Besides, integration artificial intelligence helps researchers gain access vast unexplored chemical space, which opens more opportunities for optimization design novel structures. Moreover, Due advances chemistry synthetic biology, also begun focus on potential mimetics peptides. In this review, a comprehensive discussion about natural synthesized as well their is made, so provide summary field inspire follow‐up research.
Язык: Английский
Процитировано
3