Design Of Antimicrobial Peptides Research Articles

De Novo Antimicrobial Peptide Design with Feedback Generative Adversarial Networks.

Antimicrobial peptides (AMPs) are promising candidates for new antibiotics due to their broad-spectrum activity against pathogens and reduced susceptibility to resistance development. Deep-learning techniques, such as deep generative models, offer a promising avenue to expedite the discovery and optimization of AMPs. A remarkable example is the Feedback Generative Adversarial Network (FBGAN), a deep generative model that incorporates a classifier during its training phase. Our study aims to explore the impact of enhanced classifiers on the generative capabilities of FBGAN. To this end, we introduce two alternative classifiers for the FBGAN framework, both surpassing the accuracy of the original classifier. The first classifier utilizes the k-mers technique, while the second applies transfer learning from the large protein language model Evolutionary Scale Modeling 2 (ESM2). Integrating these classifiers into FBGAN not only yields notable performance enhancements compared to the original FBGAN but also enables the proposed generative models to achieve comparable or even superior performance to established methods such as AMPGAN and HydrAMP. This achievement underscores the effectiveness of leveraging advanced classifiers within the FBGAN framework, enhancing its computational robustness for AMP de novo design and making it comparable to existing literature.

A novel family of defensin-like peptides from Hermetia illucens with antibacterial properties.

The world faces a major infectious disease challenge. Interest in the discovery, design, or development of antimicrobial peptides (AMPs) as an alternative approach for the treatment of bacterial infections has increased. Insects are a good source of AMPs which are the main effector molecules of their innate immune system. Black Soldier Fly Larvae (BSFL) are being developed for large-scale rearing for food sustainability, waste reduction and as sustainable animal and fish feed. Bioinformatic studies have suggested that BSFL have the largest number of AMPs identified in insects. However, most AMPs identified in BSF have not yet undergone antimicrobial evaluation but are promising leads to treat critical infections. Jg7197.t1, Jg7902.t1 and Jg7904.t1 were expressed into the haemolymph of larvae following infection with Salmonella enterica serovar Typhimurium and were predicted to be AMPs using the computational tool ampir. The genes encoding these proteins were within 2 distinct clusters in chromosome 1 of the BSF genome. Following removal of signal peptides, predicted structures of the mature proteins were superimposed, highlighting a high degree of structural conservation. The 3 AMPs share primary sequences with proteins that contain a Kunitz-binding domain; characterised for inhibitory action against proteases, and antimicrobial activities. An in vitro antimicrobial screen indicated that heterologously expressed SUMO-Jg7197.t1 and SUMO-Jg7902.t1 did not show activity against 12 bacterial strains. While recombinant SUMO-Jg7904.t1 had antimicrobial activity against a range of Gram-negative and Gram-positive bacteria, including the serious pathogen Pseudomonas aeruginosa. We have cloned and purified putative AMPs from BSFL and performed initial in vitro experiments to evaluate their antimicrobial activity. In doing so, we have identified a putative novel defensin-like AMP, Jg7904.t1, encoded in a paralogous gene cluster, with antimicrobial activity against P. aeruginosa.

A Systematic Review of the Design and Applications of Antimicrobial Peptides in Wound Healing.

The sources of antimicrobial peptides (AMPs), also known as peptide-based antibiotics, are diverse, such as plants, animals, microorganisms including human leukocytes, saliva, human defense peptides, and human sweat. These natural sources provide a rich variety of AMPs with unique characteristics and potential therapeutic applications, including wound-healing and antimicrobial properties. AMPs derived from these sources have shown promise in combating a wide range of pathogens, making them valuable targets for further research and potential clinical applications. The design of AMPs for wound healing involves a meticulous process of structurally optimizing peptides to possess a unique combination of antibacterial and wound-healing characteristics. This systematic review was produced to show the design and applications of AMPs in wound healing. The terms "antimicrobial peptides AND wound healing" were used to search for articles published between September 2023 and January 2010. In the search, we found a total of 12958 articles, of which 12898 were excluded, and the remaining 60 articles were chosen for further study. This systematic review underscores the potential of AMPs as valuable tools in infection control and wound healing, showcasing their versatility and effectiveness in combating a wide range of pathogens. Overall, AMPs in wound healing display a diverse mechanism of action, influencing the inflammatory response, encouraging tissue regeneration, and aiding tissue remodeling, along with strong antibacterial activity. Furthermore, this systematic review addresses AMP toxicity studies, which include rigorous in vitro and in vivo examinations to determine potential cytotoxic effects, systemic toxicity, and any adverse responses connected with its usage in wound-healing applications.

Novel design of simplified β-hairpin antimicrobial peptide as a potential food preservative based on Trp-pocket backbone

Food contamination from microbial deterioration requires the development of potent antimicrobial peptides (AMPs). The deployment of approved AMPs as dietary preservatives is limited due to barriers such as instability, toxicity, and high synthetic costs. This exploration utilizes the primary structural elements of the Trp-pocket backbone to engineer a series of β-hairpin AMPs (XWRWRPGXKXXR-NH2, X representing I, V, F, and/or L). Peptides WpLF, with Phe as X and Leu arranged at the 11th position, demonstrated exceptional selectivity index (SI = 123.08) and sterilization effects both in vitro and in vivo. WpLF consistently exhibited stable bacteriostasis, regardless of physiological salts, serum, and extreme pH. Mechanistic analysis indicated that the peptide penetrates microbial cell membranes, inducing membrane disruption, thereby impeding drug resistance evolution. Conclusively, AMPs engineered by the Trp-pocket skeleton hold substantial potential as innovative biological preservatives in food preservation, providing valuable insights for sustainable and safe peptide-based food preservatives.

Abstract 2231 Revisiting the Translation Initiation in Bacterial Protein Biosynthesis for Rational Design of Antimicrobial Peptides

Abstract 2231 Revisiting the Translation Initiation in Bacterial Protein Biosynthesis for Rational Design of Antimicrobial Peptides

Machine Learning Accelerates De Novo Design of Antimicrobial Peptides.

Efficient and precise design of antimicrobial peptides (AMPs) is of great importance in the field of AMP development. Computing provides opportunities for peptide de novo design. In the present investigation, a new machine learning-based AMP prediction model, AP_Sin, was trained using 1160 AMP sequences and 1160 non-AMP sequences. The results showed that AP_Sin correctly classified 94.61% of AMPs on a comprehensive dataset, outperforming the mainstream and open-source models (Antimicrobial Peptide Scanner vr.2, iAMPpred and AMPlify) and being effective in identifying AMPs. In addition, a peptide sequence generator, AP_Gen, was devised based on the concept of recombining dominant amino acids and dipeptide compositions. After inputting the parameters of the 71 tridecapeptides from antimicrobial peptides database (APD3) into AP_Gen, a tridecapeptide bank consisting of de novo designed 17,496 tridecapeptide sequences were randomly generated, from which 2675 candidate AMP sequences were identified by AP_Sin. Chemical synthesis was performed on 180 randomly selected candidate AMP sequences, of which 18 showed high antimicrobial activities against a wide range of the tested pathogenic microorganisms, and 16 of which had a minimal inhibitory concentration of less than 10μg/mL against at least one of the tested pathogenic microorganisms. The method established in this research accelerates the discovery of valuable candidate AMPs and provides a novel approach for de novo design of antimicrobial peptides.

Rational Design of Amphipathic Antimicrobial Peptides with Alternating L-/D-Amino Acids That Form Helical Structures.

Antimicrobial peptides (AMPs) are promising therapeutic agents against bacteria. We have previously reported an amphipathic AMP Stripe composed of cationic L-Lys and hydrophobic L-Leu/L-Ala residues, and Stripe exhibited potent antimicrobial activity against Gram-positive and Gram-negative bacteria. Gramicidin A (GA), composed of repeating sequences of L- and D-amino acids, has a unique β6.3-helix structure and exhibits broad antimicrobial activity. Inspired by the structural properties and antimicrobial activities of LD-alternating peptides such as GA, in this study, we designed Stripe derivatives with LD-alternating sequences. We found that simply alternating L- and D-amino acids in the Stripe sequence to give StripeLD caused a reduction in antimicrobial activity. In contrast, AltStripeLD, with cationic and hydrophobic amino acids rearranged to yield an amphipathic distribution when the peptide adopts a β6.3-helix, displayed higher antimicrobial activity than AltStripe. These results suggest that alternating L-/D-cationic and L-/D-hydrophobic amino acids in accordance with the helical structure of an AMP may be a useful way to improve antimicrobial activity and develop new AMP drugs.

Design, biological characteristics, and antibacterial mechanism of high therapeutic index antimicrobial peptides with PRRP as central axis.

As the important components of biological innate immunity, antimicrobial peptides (AMPs) were found in a variety of organisms including insects, plants, animals, bacteria, fungi, etc. However, high hemolytic activity, high toxicity, and poor stability of natural AMPs hinder serious their application as therapeutic agents. To overcome these problems, in this study we use PRRP as a central axis, and peptides were designed based on the sequence template XRRXXRXPRRPXRXXRRX-NH2, where X represents a hydrophobic amino acid like Phe (F), Ile (I), Val (V), and Leu (L). The designed peptides LR18, FR18, and IR18 showed effective antimicrobial activity against some Gram-positive bacteria and Gram-negative bacteria, low cytotoxicity to mammalian cells, and had a tendency to form α-helical structures in membrane-mimetic environments. Among them, peptide LR18 (X: L) showed the highest geometric mean average treatment index (GMTI = 42.7) against Gram-negative bacteria, and FR18 (X: L) showed the highest GMTI (22.86) against Gram-positive bacteria. LR18 and FR18 also showed better salt, temperature, pH, and trypsin stability. LR18 and FR18 exert their antimicrobial effects mainly through destroying bacteria cell membrane. Briefly, peptide LR18 and FR18 have the potential to serve as a therapeutic agent to reduce antibiotic resistance owing to its high therapeutic index and great stability.

Machine learning assisted rational design of antimicrobial peptides based on human endogenous proteins and their applications for cosmetic preservative system optimization

Preservatives are essential components in cosmetic products, but their safety issues have attracted widespread attention. There is an urgent need for safe and effective alternatives. Antimicrobial peptides (AMPs) are part of the innate immune system and have potent antimicrobial properties. Using machine learning-assisted rational design, we obtained a novel antibacterial peptide, IK-16-1, with significant antibacterial activity and maintaining safety based on β-defensins. IK-16-1 has broad-spectrum antimicrobial properties against Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, and Candida albicans, and has no haemolytic activity. The use of IK-16-1 holds promise in the cosmetics industry, since it can serve as a preservative synergist to reduce the amount of other preservatives in cosmetics. This study verified the feasibility of combining computational design with artificial intelligence prediction to design AMPs, achieving rapid screening and reducing development costs.

An in silico approach to de novo design of anti-microbial peptide from inspirited Komodo dragon's original VK6 peptide

An in silico approach to de novo design of anti-microbial peptide from inspirited Komodo dragon's original VK6 peptide

Rational design of antimicrobial peptides: an optimization approach

Discovery of new antimicrobial peptide sequences using a computer-aided inverse design framework.

Progress and future of the computational design of antimicrobial peptides (AMPs): bio-inspired functional molecules

The effectiveness of antibiotics is greatly enhanced by their ability to target invasive organisms involved in the ancient evolutionary battle between hosts and pathogens.

An in silico approach to de novo design of Anti-Microbial peptide from inspirited Komodo dragon's original VK6 peptide

An in silico approach to de novo design of Anti-Microbial peptide from inspirited Komodo dragon's original VK6 peptide

Multi-CGAN: Deep Generative Model-Based Multiproperty Antimicrobial Peptide Design.

Antimicrobial peptides are peptides that are effective against bacteria and viruses, and the discovery of new antimicrobial peptides is of great importance to human life and health. Although the design of antimicrobial peptides using machine learning methods has achieved good results in recent years, it remains a challenge to learn and design novel antimicrobial peptides with multiple properties of interest from peptide data with certain property labels. To this end, we propose Multi-CGAN, a deep generative model-based architecture that can learn from single-attribute peptide data and generate antimicrobial peptide sequences with multiple attributes that we need, which may have a potentially wide range of uses in drug discovery. In particular, we verified that our Multi-CGAN generated peptides with the desired properties have good performance in terms of generation rate. Moreover, a comprehensive statistical analysis demonstrated that our generated peptides are diverse and have a low probability of being homologous to the training data. Interestingly, we found that the performance of many popular deep learning methods on the antimicrobial peptide prediction task can be improved by using Multi-CGAN to expand the data on the training set of the original task, indicating the high quality of our generated peptides and the robust ability of our method. In addition, we also investigated whether it is possible to directionally generate peptide sequences with specified properties by controlling the input noise sampling for our model.

Antimicrobial activities and mechanisms of truncated and amino-acid-substituted peptides derived from bacteriocin PZJ5

Truncation and amino acid residue substitution are common methods to optimise the design of antimicrobial peptides (AMPs). In the present work, seven truncated and residue-substituted derivatives of Plantaricin ZJ5 (PZJ5) were designed and synthesised. PZJ5-5 was a truncation that simultaneously contained three substituted amino-acid residues, with enhanced antimicrobial activity and low haemolytic activity. The effects of PZJ5-5 on Escherichia coli microstructure were investigated using scanning and transmission electron microscopy, which indicated that its antibacterial mechanism was similar to PZJ5. C-terminal amidation of PZJ5-5 (PZJ5-7) was deleterious, and resulted in a dramatic reduction in potency against E. coli and Listeria monocytogenes, with no potency against the other three indicator bacteria. Truncation and residue substitution of bacteriocin PZJ5 changed its antimicrobial activities and specificities, which provided a rationale for bacteriocin design.

Structural Analysis and Activity Correlation of Amphiphilic Cyclic Antimicrobial Peptides Derived from the [W4R4] Scaffold.

In our ongoing quest to design effective antimicrobial peptides (AMPs), this study aimed to elucidate the mechanisms governing cyclic amphiphilic AMPs and their interactions with membranes. The objective was to discern the nature of these interactions and understand how peptide sequence and structure influence antimicrobial activity. We introduced modifications into the established cyclic AMP peptide, [W4R4], incorporating an extra aromatic hydrophobic residue (W), a positively charged residue (R), or the unique 2,5-diketopiperazine (DKP). This study systematically explored the structure-activity relationships (SARs) of a series of cyclic peptides derived from the [W4R4] scaffold, including the first synthesis and evaluation of [W4R4(DKP)]. Structural, dynamic, hydrophobic, and membrane-binding properties of four cyclic peptides ([W4R4], [W5R4], [W4R5], [W4R4(DKP)]) were explored using molecular dynamics simulations within a DOPC/DOPG lipid bilayer that mimics the bacterial membrane. The results revealed distinct SARs linking antimicrobial activity to parameters such as conformational plasticity, immersion depth in the bilayer, and population of the membrane binding mode. Notably, [W4R5] exhibited an optimal "activity/binding to the bacterial membrane" pattern. This multidisciplinary approach efficiently decoded finely regulated SAR profiles, laying a foundation for the rational design of novel antimicrobial peptides.

Design and evaluation of tadpole-like conformational antimicrobial peptides

Antimicrobial peptides are promising alternatives to conventional antibiotics. Herein, we report a class of “tadpole-like” peptides consisting of an amphipathic α-helical head and an aromatic tail. A structure-activity relationship (SAR) study of “tadpole-like” temporin-SHf and its analogs revealed that increasing the number of aromatic residues in the tail, introducing Arg to the α-helical head and rearranging the peptide topology dramatically increased antimicrobial activity. Through progressive structural optimization, we obtained two peptides, HT2 and RI-HT2, which exhibited potent antimicrobial activity, no hemolytic activity and cytotoxicity, and no propensity to induce resistance. NMR and molecular dynamics simulations revealed that both peptides indeed adopted “tadpole-like” conformations. Fluorescence experiments and electron microscopy confirmed the membrane targeting mechanisms of the peptides. Our studies not only lead to the discovery of a series of ultrashort peptides with potent broad-spectrum antimicrobial activities, but also provide a new strategy for rational design of novel “tadpole-like” antimicrobial peptides.

Design and In-silico Screening of Short Antimicrobial Peptides (AMPs) as Anti-Tubercular Agents Targeting INHA

Introduction: Tuberculosis has been studied as a potentially serious bacterial infection affecting the lung caused by Mycobacterium tuberculosis. In addition to its severe impact on health, resistance to existing drugs has also been seen as a rising concern in the space of medicinal solutions. Therapeutic peptides have the potential to complement existing drug designs to provide effective outcomes against Mycobacterium tuberculosis-resistant strains. Methods: This study illustrated a computational approach to design and test peptides against NADHdependent enoyl-acyl carrier protein reductase of Mycobacterium tuberculosis. A human antimicrobial peptide LL-37 was used as a template, and a further 6 peptides were designed, and their binding and interactions against NADH-dependent enoyl-acyl carrier protein reductase were examined. Further, toxicity, immunogenicity, and a broad spectrum of physicochemical properties were calculated to evaluate the therapeutic and safety profile of these peptides. Results: These peptides were structurally modelled and docked with the protein to determine their binding poses and affinity. The molecular interaction of LL-37 with protein was treated as a reference to evaluate the effectiveness of designed peptides. Solvent accessible surface area (SASA) and ΔG binding free energy of docked complexes assisted in the ranking of these peptides. Eventually, peptides P1: LLGDFFRKSKEK, P3: LLFGDRFLLKEK and P7: LLGDFFRLLKEK were selected for 100 ns molecular dynamic simulation as they showed predicted dissociation constants of 8.7×10-4 M, 3.3×10-4 M and 1.2×10-4 M, respectively. These peptides showed direct hydrogen bond formation with ILE21 and LYS165, which are critical active site residues of the protein. The structural variation pattern collected from the MD simulation suggested a strong and stable binding of P3 and P1 with the protein with RMSD 4-5 Å with the starting conformation under the non-fluctuating state. These two peptides showed relatively similar binding results compared with the control peptide LL-37. Comprehensive structural analysis was performed for the middle structures of the most populated cluster generated from 100 ns MD simulation trajectory. Conclusion: Later, MMPBSA binding energies of these structures were computed, where the average binding free energies of P1, P3, and P7 peptides were -146.93 kcal/mole, -161.16 kcal/mole, and - 151.44 kcal/mole, respectively. These energies suggested that P3 is strongly bound to the active site of NADH-dependent enoyl-acyl carrier protein reductase. Overall, this study proposed the application of these peptides as a possible therapeutic solution to inhibit the growth of Mycobacterium tuberculosis.

Multi-label classification and features investigation of antimicrobial peptides with various functional classes

The challenge of drug-resistant bacteria to global public health has led to increased attention on antimicrobial peptides (AMPs) as a targeted therapeutic alternative with a lower risk of resistance. However, high production costs and limitations in functional class prediction have hindered progress in this field. In this study, we used multi-label classifiers with binary relevance and algorithm adaptation techniques to predict different functions of AMPs across a wide range of pathogen categories, including bacteria, mammalian cells, fungi, viruses, and cancer cells. Our classifiers attained promising AUC scores varying from 0.8492 to 0.9126 on independent testing data. Forward feature selection identified sequence order and charge as critical, with specific amino acids (C and E) as discriminative. These findings provide valuable insights for the design of antimicrobial peptides (AMPs) with multiple functionalities, thus contributing to the broader effort to combat drug-resistant pathogens.

Rational design and characterization of cell-selective antimicrobial peptides based on a bioactive peptide from Crocodylus siamensis hemoglobin

Antimicrobial resistance is a growing health concern. Antimicrobial peptides are a potential solution because they bypass conventional drug resistance mechanisms. Previously, we isolated a peptide from Crocodylus siamensis hemoglobin hydrolysate, which has antimicrobial activity and identified the main peptide from this mixture (QL17). The objective of this work was to evaluate and rationally modify QL17 in order to: (1) control its mechanism of action through bacterial membrane disruption; (2) improve its antimicrobial activity; and (3) ensure it has low cytotoxicity against normal eukaryotic cells. QL17 was rationally designed using physicochemical and template-based methods. These new peptide variants were assessed for: (1) their in vitro inhibition of microbial growth, (2) their cytotoxicity against normal cells, (3) their selectivity for microbes, and (4) the mode of action against bacteria using scanning electron microscopy (SEM), transmission electron microscopy (TEM) and confocal microscopy. The results indicate that all designed peptides have more potent antimicrobial efficacy than QL17 and IL15 peptides. However, only the most rationally modified peptides showed strong antimicrobial activity and minimal toxicity against normal cells. In particular, IL15.3 (hydrophobicity of 47% and net charge of + 6) was a potent antimicrobial agent (MIC = 4–12 μg/mL; MBC = 6–25 μg/mL) and displayed excellent selectivity for microbes (cf. human cells) via FACS assays. Microscopy confirmed that IL15.3 acts against bacteria by disrupting the cell membrane integrity and penetrating into the membrane. This causes the release of intracellular content into the outer environment leading to the death of bacteria. Moreover, IL15.3 can also interact with DNA suggesting it could have dual mode of action. Overall, a novel variant of QL17 is described that increases antimicrobial activity by over 1000-fold (~ 5 μg/mL MIC) and has minimal cytotoxicity. It may have applications in clinical use to treat and safeguard against bacteria.