Membrane Interactions of Latarcins: Antimicrobial Peptides from Spider Venom

Contrastive learning for enhancing feature extraction in anticancer peptides

Cancer, recognized as a primary cause of death worldwide, has profound health implications and incurs a substantial social burden. Numerous efforts have been made to develop cancer treatments, among which anticancer peptides (ACPs) are garnering recognition for their potential applications. While ACP screening is time-consuming and costly, in silico prediction tools provide a way to overcome these challenges. Herein, we present a deep learning model designed to screen ACPs using peptide sequences only. A contrastive learning technique was applied to enhance model performance, yielding better results than a model trained solely on binary classification loss. Furthermore, two independent encoders were employed as a replacement for data augmentation, a technique commonly used in contrastive learning. Our model achieved superior performance on five of six benchmark datasets against previous state-of-the-art models. As prediction tools advance, the potential in peptide-based cancer therapeutics increases, promising a brighter future for oncology research and patient care.

Spider-Venom Peptides: Structure, Bioactivity, Strategy, and Research Applications

Spiders (Araneae), having thrived for over 300 million years, exhibit remarkable diversity, with 47,000 described species and an estimated 150,000 species in existence. Evolving with intricate venom, spiders are nature's skilled predators. While only a small fraction of spiders pose a threat to humans, their venoms contain complex compounds, holding promise as drug leads. Spider venoms primarily serve to immobilize prey, achieved through neurotoxins targeting ion channels. Peptides constitute a major part of these venoms, displaying diverse pharmacological activities, and making them appealing for drug development. Moreover, spider-venom peptides have emerged as valuable tools for exploring human disease mechanisms. This review focuses on the roles of spider-venom peptides in spider survival strategies and their dual significance as pharmaceutical research tools. By integrating recent discoveries, it provides a comprehensive overview of these peptides, their targets, bioactivities, and their relevance in spider survival and medical research.

Antimicrobial Peptides Mediate Apoptosis by Changing Mitochondrial Membrane Permeability

Changes in mitochondrial membrane permeability are closely associated with mitochondria-mediated apoptosis. Antimicrobial peptides (AMPs), which have been found to enter cells to exert physiological effects, cause damage to the mitochondria. This paper reviews the molecular mechanisms of AMP-mediated apoptosis by changing the permeability of the mitochondrial membrane through three pathways: the outer mitochondrial membrane (OMM), inner mitochondrial membrane (IMM), and mitochondrial permeability transition pore (MPTP). The roles of AMPs in inducing changes in membrane permeability and apoptosis are also discussed. Combined with recent research results, the possible application prospects of AMPs are proposed to provide a theoretical reference for the development of AMPs as therapeutic agents for human diseases.

Prevention of hospital pathogen biofilm formation by antimicrobial peptide KWI18

This study investigated the antimicrobial and antibiofilm activity of KWI18, a new synthetic peptide. KWI18 was tested against planktonic cells and Pseudomonas aeruginosa and Candida parapsilosis biofilms. Time-kill and synergism assays were performed. Sorbitol, ergosterol, lipid peroxidation, and protein oxidation assays were used to gain insight into the mechanism of action of the peptide. Toxicity was evaluated against erythrocytes and Galleria mellonella. KWI18 showed antimicrobial activity, with minimum inhibitory concentration (MIC) values ranging from 0.5 to 10 μM. KWI18 at 10 × MIC reduced P. aeruginosa and C. parapsilosis biofilm formation and cell viability. Time-kill assays revealed that KWI18 inhibited the growth of P. aeruginosa in 4 h and that of C. parapsilosis in 6 h. The mechanism of action was related to ergosterol as well as induction of oxidative damage in cells and biofilms. Furthermore, KWI18 demonstrated low toxicity to erythrocytes and G. mellonella. KWI18 proved to be an effective antibiofilm agent, opening opportunities for the development of new antimicrobials.

Identifying novel antimicrobial peptides from venom gland of spider Pardosa astrigera by deep multi-task learning

Antimicrobial peptides (AMPs) show promises as valuable compounds for developing therapeutic agents to control the worldwide health threat posed by the increasing prevalence of antibiotic-resistant bacteria. Animal venom can be a useful source for screening AMPs due to its various bioactive components. Here, the deep learning model was developed to predict species-specific antimicrobial activity. To overcome the data deficiency, a multi-task learning method was implemented, achieving F1 scores of 0.818, 0.696, 0.814, 0.787, and 0.719 for Bacillus subtilis, Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, and Staphylococcus epidermidis, respectively. Peptides PA-Full and PA-Win were identified from the model using different inputs of full and partial sequences, broadening the application of transcriptome data of the spider Pardosa astrigera. Two peptides exhibited strong antimicrobial activity against all five strains along with cytocompatibility. Our approach enables excavating AMPs with high potency, which can be expanded into the fields of biology to address data insufficiency.

Antimicrobial Mechanisms and Clinical Application Prospects of Antimicrobial Peptides

Antimicrobial peptides are a type of small-molecule peptide that widely exist in nature and are components of the innate immunity of almost all living things. They play an important role in resisting foreign invading microorganisms. Antimicrobial peptides have a wide range of antibacterial activities against bacteria, fungi, viruses and other microorganisms. They are active against traditional antibiotic-resistant strains and do not easily induce the development of drug resistance. Therefore, they have become a hot spot of medical research and are expected to become a new substitute for fighting microbial infection and represent a new method for treating drug-resistant bacteria. This review briefly introduces the source and structural characteristics of antimicrobial peptides and describes those that have been used against common clinical microorganisms (bacteria, fungi, viruses, and especially coronaviruses), focusing on their antimicrobial mechanism of action and clinical application prospects.

Synthetic molecular evolution of antimicrobial peptides

As we learn more about how peptide structure and activity are related, we anticipate that antimicrobial peptides will be engineered to have strong potency and distinct functions and that synthetic peptides will have new biomedical applications, such as treatments for emerging infectious diseases. As a result of the enormous number of possible amino acid sequences and the low-throughput nature of antimicrobial peptide assays, computational tools for peptide design and optimization are needed for direct experimentation toward obtaining functional sequences. Recent developments in computational tools have improved peptide design, saving labor, reagents, costs, and time. At the same time, improvements in peptide synthesis and experimental platforms continue to reduce the cost and increase the throughput of peptide-drug screening. In this review, we discuss the current methods of peptide design and engineering, including in silico methods and peptide synthesis and screening, and highlight areas of potential improvement.