Antimicrobial Peptide Database Research Articles

Influence of Enzymatic Hydrolysis Conditions on Antimicrobial Activities and Peptide Profiles of Milk Protein-Derived Hydrolysates from White Wastewater

The focus of our investigation lies in the hydrolysis of milk proteins found in the substantial wastewater generated by the dairy industry, particularly in the white and cleaning wastewater resulting from rinsing and cleaning-in-place processes in order to enhance the value of dairy constituents by producing a diverse population of peptides, including potential antimicrobial peptides generated by 4 different enzymes: pepsin, trypsin, pronase E, and thermolysin. The protein/peptide content was influenced by the degree of hydrolysis values ranging from 2% to 13%, and UPLC-MS/MS characterization reveals distinct peptide sequences in enzymatic hydrolysates. The impact of hydrolysis time was also examined, revealing significant differences between 30minutes and 240minutes, with 555 peptides identified at 30minutes, increasing to 693 at 240minutes. After 4hours, grouping showed variations: 181 peptides (thermolysin), 153 (pepsin), 126 (trypsin), and 83 (pronase E). A comparative analysis of the characterized sequences with antimicrobial peptides databases identified 17 antimicrobial peptides after 240minutes pronase E and thermolysin hydrolysis, though they were insufficient to inhibit strains like Clostridium tyrobutyricum and Pseudomonas aeruginosa. Antimicrobial assays also revealed that peptides from Pronase T30, Pronase T240, and Thermolysine T240 exhibited antifungal activity against Mucor racemosus (MIC 2.5mg/ml), but none against Penicillium commune. The effet of enzymatic hydrolysis demonstrated in this study highlights for the first time the potential for valorizing dairy white wastewater within the context of a circular economy framework.

Novel antimicrobial peptides based on Protegrin-1: In silico and in vitro assessments

The development of antibiotic resistance has caused significant health problems. Antimicrobial peptides (AMPs) are considered next-generation antibiotics. Protegrin-1 (PG-1) is a β-hairpin AMP with a membrane-binding capacity. This study used twelve PG-1 analogs with different amino acid substitutions. Coarse-grained molecular dynamics (MD) simulations were used to assess these analogs, and their physicochemical properties were computed using the Antimicrobial Peptide Database. Three AMPs, PEP-D, PEP-C, and PEP-H, were chosen and synthesized for antibacterial testing. The microbroth dilution technique and hemolytic assays evaluated the antimicrobial efficacy and cellular toxicity. The checkerboard method was used to test the combined activity of AMP and standard antibiotics. Cell membrane permeability and electron microscopy were used to evaluate the mode of action. The chemical stability of the selective AMP, PEP-D, was assessed by a validated HPLC method. PEP-D consists of 16–18 amino acid residues and has a charge of +7 and a hydrophobicity of 44 %, similar to PG-1. It can efficiently inactivate bacteria by disrupting cell membranes and significantly reducing hemolytic activity. Chemical stability studies indicated that AMP was stable at 40 °C for six months under autoclave conditions. This study could introduce the potential therapeutic application of selective AMP as an anti-infective agent.

A novel antimicrobial peptide MP-4: Insights into its antimicrobial properties and intestinal regulation on E. coli-infected mice

The quest for novel, potent antimicrobial agents with low resistance potential poses a significant challenge for the advancement of the food and medical sectors. This study aimed to elucidate the antibacterial potency of antimicrobial peptides derived from koumiss in a murine model. Leveraging an antimicrobial peptide database, six peptides (MP-1 to MP-6) were meticulously predicted and screened for their antibacterial properties. These peptides were subsequently synthesized using chemical solid-phase methods and their antibacterial activities were rigorously validated. Remarkably, among the six peptides, MP-4 demonstrated a profound antibacterial effect against E. coli, achieving rapid bacterial eradication within 240 min. Flow cytometry analysis further corroborated its significant bactericidal activity. In vivo experiments conducted on mice infected with E. coli revealed that oral administration of MP-4 significantly ameliorated symptoms such as lethargy, anorexia, and weight loss. Additionally, it effectively reduced the colonic E. coli burden, attenuated inflammatory responses, and favorably modulated the intestinal microbiota composition. This study not only validates the robust antibacterial activity of the koumiss-derived antimicrobial peptide MP-4, but also underscores its potential therapeutic application in mitigating E. coli infections and promoting intestinal health.

Relationship Between Biophysical Properties of Antimicrobial Peptides (AMPs) and their Associated Drug Efficacies

Antibiotic resistance is a growing global health threat. One consequence is that patients with cystic fibrosis (CF) are prone to developing antibiotic resistant lung infections caused by multiple strains of bacteria, including Pseudomonas aeruginosa. Due to the limited number of treatment options for patients with chronic antibiotic resistant infections, there is a need for finding new antibiotics that allow for effective eradication of bacterial infections, such as those in the CF lung. Many antimicrobial peptides (AMPs) have been annotated in databases and are considered as potential alternatives for current antibiotics. However, in many instances, the suitability of AMPs as drug molecules has not been extensively explored. Here, we propose that certain molecular properties of AMPs favor high antibiotic efficacy. Using information from AMP databases, we combined statistical analyses and machine learning techniques to identify relationships between various biophysical properties of AMPs and their drug efficacies. Analyses from classification and regression trees (CART) and random forests suggest that net charge and maximum average hydrophobic moment are the most important properties in determining if a peptide is useful against P. aeruginosa infections in CF patients. Maximum average hydrophobic residue, average alpha helix propensity score, hydrophobic proportion, and peptide length still contribute to this determination but to lesser degrees. Cation-pi interactions, on the other hand, do not appear to factor into this decision at all. Based on these properties, our current work is focused on designing and experimentally testing new peptides that may have activity against P. aeruginosa infections.

Prediction of enzyme action for extraction of antimicrobial substances from <i>Sus scrofa</i> and <i>Bos taurus</i>

The study of antimicrobial compounds of animal origin, particularly antimicrobial peptides (AMPs), is a current research topic. However, extracting endogenous AMPs is a challenging process and requires the application of targeted enzymatic processing principles based on knowledge of the structure of prepropeptide molecules — precursors of AMPs. In this study, a search was conducted for antimicrobial peptides present in Sus scrofa and Bos taurus organisms, as well as their precursors, using The Antimicrobial Peptide Database and UniProtKB databases. In the amino acid sequences of prepropeptides, the sequences of the mature peptides were found, and cleavage sites for trypsin, bacterial collagenase (type I), and neutrophil elastase were determined. As a result of the search for antimicrobial compounds in The Antimicrobial Peptide Database, 18 antimicrobial peptides from Sus scrofa and 40 antimicrobial peptides from Bos taurus were identified. Based on the results of determining cleavage sites in AMP precursors, enzymes were ranked from less preferred to more preferred for AMP release as follows: bacterial collagenase (type I) ≤ trypsin < neutrophil elastase. This order is justified not only by the number of suitable cleavage sites and their accuracy but also by the action of enzymes within mature AMPs: it is important to consider that enzymes can “cut” the peptides themselves, thereby reducing their antimicrobial activity. The bioinformatics analysis conducted is applicable for both primary screening of raw material potential and determining of suitable enzymes for extracting antimicrobial compounds from Sus scrofa and Bos taurus organisms.

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.

Computational Study of Antimicrobial Peptides for Promising Therapeutic Applications Against Methicillin-resistant Staphylococcus Aureus.

Methicillin-resistant Staphylococcus aureus (MRSA) is a causative agent for multiple drug-resistant diseases and is a prime health concern. Currently, antibiotics like vancomycin, daptomycin, fluoroquinolones, linezolid, fifth-generation cephalosporin and others are available in the market for the treatment of MRSA infection. With the increasing prevalence of drug-resistant cases, researchers are actively investigating alternative strategies to combat MRSA, including the exploration of peptide therapeutics. This study employed computational methods to prospect for potential Antimicrobial Peptides (AMPs). A total of One hundred and fifty antimicrobial peptides were explored based on physicochemical properties. The results showed that Clavanin B was the most appropriate candidate. Molecular Docking and Molecular Dynamics Simulation results showed the protein-peptide interaction of the MRSA target proteins, Penicillin Binding Protein 2a and Panton-Valentine Leukocidin Toxin, with the Antimicrobial Peptide Clavanin B. Currently, the antimicrobial peptide database highlights Clavanin B's role as an anti-HIV peptide. Moreover, this investigation proposes Clavanin B as a viable repurposed drug for treating MRSA, underscoring its potential deployment in the management of MRSA infections.

ПРИРОДНЫЙ И СИНТЕЗИРОВАННЫЙ ПЕПТИДЫ: СРАВНИТЕЛЬНАЯ АНТИМИКРОБНАЯ АКТИВНОСТЬ

A study of the comparative biological activity of a natural antimicrobial peptide isolated from trypsin hydrolysate of cow colostrum and its synthetic analogue was carried out. It was found that the isolated peptide consists of five amino acids and has a molecular weight of 407 Da. According to a search conducted on the Antimicrobial Peptide Database, the isolated peptide has 100 % similarity to the peptide AP01406 obtained from Eisenia foetida and has antiviral, antimicrobial and antitumor effects. The analysis of the chemical and physical properties of the peptide, screening of the results obtained by the Protein NCBI and Antimicrobial Peptide Database databases suggests that the isolated peptide has antimicrobial properties. A threephase synthesis of a natural analog peptide was carried out. It is proved that synthesized and natural peptides have antimicrobial and antifungal activity. The biological activity of the synthesized peptide is slightly higher than the natural one.

Design and Evaluation of a Novel Anti-microbial Peptide from Cathelicidin-2: Selectively Active Against Acinetobacter baumannii.

Infections caused by pathogenic microorganisms have increased the need for hospital care and have thus represented a public health problem and a significant financial burden. Classical treatments consisting of traditional antibiotics face several challenges today. Anti-microbial peptides (AMPs) are a conserved characteristic of the innate immune response among different animal species to defend against pathogenic microorganisms. In this study, a new peptide sequence (mCHTL131-140) was designed using the in silico approach. Cathelicidin-2 (UniprotID: Q2IAL7) was used as a potential antimicrobial protein, and a novel 10 - 12 amino acids sequence AMP was designed using bioinformatics tools and the AMP databases. Then, the anti-bacterial, anti-biofilm, and anti-fungal properties of the peptide, as well as its hemolytic activity and cytotoxicity towards human fibroblast (HDF) cells, were investigated in vitro. Online bioinformatics tools indicated that the peptide sequence could have anti-bacterial, anti-viral, anti-fungal, and anti-biofilm properties with little hemolytic properties. The experimental tests confirmed that mCHTL131-140 exhibited the best anti-bacterial properties against Acinetobacter baumannii and had fair anti-fungal properties. Besides, it did not cause red blood cell lysis and showed no cytotoxicity towards HDF cells. In general, the designed peptide can be considered a promising AMP to control hospital-acquired infections by A. baumannii.

A novel endogenous antimicrobial peptide MP-4 derived from koumiss of Inner Mongolia by peptidomics, and effects on Staphylococcus aureus

Koumiss is known as a traditional milk-based beverage with high nutritional value and antimicrobial potential. In this study, we investigated the antibacterial effects of koumiss-derived antimicrobial peptides against Staphylococcus aureus. Then, we used peptidomics to analyze and identify 2381 peptides from mare's milk and koumiss, of which 53.25% were significantly different before and after fermentation, and these peptides were mainly derived from caseins. Among the identified peptides, five new antimicrobial peptides with high antimicrobial potential, as measured by the scores of predicted peptide sequences in the antimicrobial peptide database, and validation of their antimicrobial activity and stability. MP-4 was found to have antimicrobial activity, and it exerted significant and stable antibacterial effects. The antimicrobial peptide MP-4 could inhibit Staphylococcus aureus by changing its morphology and killing it via the induction of protein leakage. Therefore, it can be concluded that MP-4 is a novel antimicrobial peptide derived from koumiss that has good antibacterial properties against Staphylococcus aureus. Our study provides a theoretical basis for the application of koumiss-derived peptides.

Developing anti-microbial peptide database version 1 to provide comprehensive and exhaustive resource of manually curated AMPs

Anti-Microbial Peptide Database version 1 (AMPDB v1) is a meticulously curated resource that aims to address the limitations of existing databases in the field of antimicrobial research. We have utilized the latest technology and put our best efforts into adding all relevant tools to cater to the needs of our users. AMPDB v1 is a derived database, built upon information gathered from the available resources and boasts a significant size of 59,122 entries which are classified into 88 classes. All the information in this resource was curated manually. Sequence alignment and protein feature calculation tools were integrated into the database in the form of web applications, to make them easy to use, quick, and responsive in real-time. We have included multiple types of browsing and searching options to enhance the user experience, from simple text search to a completely customizable advanced search page with intuitive options that let the user combine multiple options together to make a powerful search query. The database is accessible by a web browser at https://bblserver.org.in/ampdb/.

The antimicrobial peptide database is 20 years old: Recent developments and future directions.

In 2023, the Antimicrobial Peptide Database (currently available at https://aps.unmc.edu) is 20-years-old. The timeline for the APD expansion in peptide entries, classification methods, search functions, post-translational modifications, binding targets, and mechanisms of action of antimicrobial peptides (AMPs) has been summarized in our previous Protein Science paper. This article highlights new database additions and findings. To facilitate antimicrobial development to combat drug-resistant pathogens, the APD has been re-annotating the data for antibacterial activity (active, inactive, and uncertain), toxicity (hemolytic and nonhemolytic AMPs), and salt tolerance (salt sensitive and insensitive). Comparison of the respective desired and undesired AMP groups produces new knowledge for peptide design. Our unification of AMPs from the six life kingdoms into "natural AMPs" enabled the first comparison with globular or transmembrane proteins. Due to the dominance of amphipathic helical and disulfide-linked peptides, cysteine, glycine, and lysine in natural AMPs are much more abundant than those in globular proteins. To include peptides predicted by machine learning, a new "predicted" group has been created. Remarkably, the averaged amino acid composition of predicted peptides is located between the lower bound of natural AMPs and the upper bound of synthetic peptides. Synthetic peptides in the current APD, with the highest cationic and hydrophobic amino acid percentages, are mostly designed with varying degrees of optimization. Hence, natural AMPs accumulated in the APD over 20 years have laid the foundation for machine learning prediction. We discuss future directions for peptide discovery. It is anticipated that the APD will continue to play a role in research and education.

Apoptin NLS2 homodimerization strategy for improved antibacterial activity and bio-stability.

The emergence of antibiotic resistance prompts exploration of viable antimicrobial peptides (AMPs) designs. The present study explores the antimicrobial prospects of Apoptin nuclear localization sequence (NLS2)-derived peptide ANLP (PRPRTAKRRIRL). Further, we examined the utility of the NLS dimerization strategy for improvement in antimicrobial activity and sustained bio-stability of AMPs. Initially, the antimicrobial potential of ANLP using antimicrobial peptide databases was analyzed. Then, ANLP along with its two homodimer variants namely ANLP-K1 and ANLP-K2 were synthesized and evaluated for antimicrobial activity against Escherichia coli and Salmonella. Among three AMPs, ANLP-K2 showed efficient antibacterial activity with 12µM minimum inhibitory concentration (MIC). Slow degradation of ANLP-K1 (26.48%) and ANLP-K2 (13.21%) compared with linear ANLP (52.33%) at 480min in serum stability assay indicates improved bio-stability of dimeric peptides. The AMPs presented no cytotoxicity in Vero cells. Dye penetration assays confirmed the membrane interacting nature of AMPs. The zeta potential analysis reveals effective charge neutralization of both lipopolysaccharide (LPS) and bacterial cells by dimeric AMPs. The dimeric AMPs on scanning electron microscopy studies showed multiple pore formations on the bacterial surface. Collectively, proposed Lysine scaffold dimerization of Apoptin NLS2 strategy resulted in enhancing antibacterial activity, bio-stability, and could be effective in neutralizing the off-target effect of LPS. In conclusion, these results suggest that nuclear localization sequence with a modified dimeric approach could represent a rich source of template for designing future antimicrobial peptides.

Characterization and Engineering Studies of a New Endolysin from the Propionibacterium acnes Bacteriophage PAC1 for the Development of a Broad-Spectrum Artilysin with Altered Specificity.

The emergence of multidrug-resistant (MDR) bacteria has risen rapidly, leading to a great threat to global public health. A promising solution to this problem is the exploitation of phage endolysins. In the present study, a putative N-acetylmuramoyl-L-alanine type-2 amidase (NALAA-2, EC 3.5.1.28) from Propionibacterium bacteriophage PAC1 was characterized. The enzyme (PaAmi1) was cloned into a T7 expression vector and expressed in E. coli BL21 cells. Kinetics analysis using turbidity reduction assays allowed the determination of the optimal conditions for lytic activity against a range of Gram-positive and negative human pathogens. The peptidoglycan degradation activity of PaAmi1 was confirmed using isolated peptidoglycan from P. acnes. The antibacterial activity of PaAmi1 was investigated using live P. acnes cells growing on agar plates. Two engineered variants of PaAmi1 were designed by fusion to its N-terminus two short antimicrobial peptides (AMPs). One AMP was selected by searching the genomes of Propionibacterium bacteriophages using bioinformatics tools, whereas the other AMP sequence was selected from the antimicrobial peptide databases. Both engineered variants exhibited improved lytic activity towards P. acnes and the enterococci species Enterococcus faecalis and Enterococcus faecium. The results of the present study suggest that PaAmi1 is a new antimicrobial agent and provide proof of concept that bacteriophage genomes are a rich source of AMP sequences that can be further exploited for designing novel or improved endolysins.

CH vs. HC-Promiscuous Metal Sponges in Antimicrobial Peptides and Metallophores.

Histidine and cysteine residues, with their imidazole and thiol moieties that deprotonate at approximately physiological pH values, are primary binding sites for Zn(II), Ni(II) and Fe(II) ions and are thus ubiquitous both in peptidic metallophores and in antimicrobial peptides that may use nutritional immunity as a way to limit pathogenicity during infection. We focus on metal complex solution equilibria of model sequences encompassing Cys-His and His-Cys motifs, showing that the position of histidine and cysteine residues in the sequence has a crucial impact on its coordination properties. CH and HC motifs occur as many as 411 times in the antimicrobial peptide database, while similar CC and HH regions are found 348 and 94 times, respectively. Complex stabilities increase in the series Fe(II) < Ni(II) < Zn(II), with Zn(II) complexes dominating at physiological pH, and Ni(II) ones-above pH 9. The stabilities of Zn(II) complexes with Ac-ACHA-NH2 and Ac-AHCA-NH2 are comparable, and a similar tendency is observed for Fe(II), while in the case of Ni(II), the order of Cys and His does matter-complexes in which the metal is anchored on the third Cys (Ac-AHCA-NH2) are thermodynamically stronger than those where Cys is in position two (Ac-ACHA-NH2) at basic pH, at which point amides start to take part in the binding. Cysteine residues are much better Zn(II)-anchoring sites than histidines; Zn(II) clearly prefers the Cys-Cys type of ligands to Cys-His and His-Cys ones. In the case of His- and Cys-containing peptides, non-binding residues may have an impact on the stability of Ni(II) complexes, most likely protecting the central Ni(II) atom from interacting with solvent molecules.

Optimisation and identification of anchovy antimicrobial peptides by enzymolysis and untargeted proteomic profiling

Natural antimicrobial peptides are promising antibiotics without inducing high bacteria resistance and have wide applications in the medical health and food industry. Herein, we prepared and optimised anchovy antimicrobial peptides (AAMPs) by degreasing and enzymolysis of anchovy extracts under different conditions. The enzymolysis mixtures at optimised preparation conditions exhibited concentration-dependent inhibitory activity against Staphylococcus aureus. Then, we applied the mass spectrometry-based proteomics analysis to globally profile the peptide constitutes within the active peptide mixture and finally, 4 unique peptides coming from 68 proteins were confidently identified. We compared the peptide sequences with the antimicrobial peptides (AMPs) database and synthesised 4 potential AAMPs. As a result, peptide GTEDELDKY exhibited inhibitory activity against Escherichia coli, and peptides DREGESGPS, YIGRPIPQ and YEDEINKR exhibited inhibitory activity against SA. Our work established a useful workflow for discovering novel AMPs from fish proteins, which may play important role in the development of effective antibiotics.

Prediction and bioactivity of small-molecule antimicrobial peptides from Protaetia brevitarsis Lewis larvae.

Antimicrobial peptides (AMPs) are widely recognized as promising natural antimicrobial agents. Insects, as the group of animals with the largest population, have great potential as a source of AMPs. Thus, it is worthwhile to investigate potential novel AMPs from Protaetia brevitarsis Lewis larvae, which is a saprophagous pest prevalent in China. In this study, comparing the whole-genome sequence of Protaetia brevitarsis Lewis larvae with the Antimicrobial Peptide Database (APD3) led to the identification of nine peptide templates that were potentially AMPs. Next, based on the peptide templates, 16 truncated sequences were predicted to the AMPs by bioinformatics software and then underwent structural and physicochemical property analysis. Thereafter, candidate small-molecule AMPs were artificially synthesized and their minimal inhibitory concentration (MIC) values were assessed. A candidate peptide, designated FD10, exhibited strong antimicrobial activity against both bacteria and fungi comprising Escherichia coli (MIC: 8 μg/mL), Pseudomonas aeruginosa (MIC: 8 μg/mL), Bacillus thuringiensis (MIC: 8 μg/mL), Staphylococcus aureus (MIC: 16 μg/mL), and Candida albicans (MIC: 16 μg/mL). Additionally, two other candidate peptides, designated FD12 and FD15, exhibited antimicrobial activity against both E. coli (MIC: both 32 μg/mL) and S. aureus (MIC: both 16 μg/mL). Moreover, FD10, FD12, and FD15 killed almost all E. coli and S. aureus cells within 1 h, and the hemolytic effect of FD10 (0.31%) and FD12 (0.40%) was lower than that of ampicillin (0.52%). These findings indicate that FD12, FD15, and especially FD10 are promising AMPs for therapeutic application. This study promoted the development of antibacterial drugs and provided a theoretical basis for promoting the practical application of antimicrobial peptides in the Protaetia brevitarsis Lewis larvae.

Thinking on the Construction of Antimicrobial Peptide Databases: Powerful Tools for the Molecular Design and Screening.

With the accelerating growth of antimicrobial resistance (AMR), there is an urgent need for new antimicrobial agents with low or no AMR. Antimicrobial peptides (AMPs) have been extensively studied as alternatives to antibiotics (ATAs). Coupled with the new generation of high-throughput technology for AMP mining, the number of derivatives has increased dramatically, but manual running is time-consuming and laborious. Therefore, it is necessary to establish databases that combine computer algorithms to summarize, analyze, and design new AMPs. A number of AMP databases have already been established, such as the Antimicrobial Peptides Database (APD), the Collection of Antimicrobial Peptides (CAMP), the Database of Antimicrobial Activity and Structure of Peptides (DBAASP), and the Database of Antimicrobial Peptides (dbAMPs). These four AMP databases are comprehensive and are widely used. This review aims to cover the construction, evolution, characteristic function, prediction, and design of these four AMP databases. It also offers ideas for the improvement and application of these databases based on merging the various advantages of these four peptide libraries. This review promotes research and development into new AMPs and lays their foundation in the fields of druggability and clinical precision treatment.

Deep Learning-Based Bioactive Therapeutic Peptide Generation and Screening.

Many bioactive peptides demonstrated therapeutic effects over complicated diseases, such as antiviral, antibacterial, anticancer, etc. It is possible to generate a large number of potentially bioactive peptides using deep learning in a manner analogous to the generation of de novo chemical compounds using the acquired bioactive peptides as a training set. Such generative techniques would be significant for drug development since peptides are much easier and cheaper to synthesize than compounds. Despite the limited availability of deep learning-based peptide-generating models, we have built an LSTM model (called LSTM_Pep) to generate de novo peptides and fine-tuned the model to generate de novo peptides with specific prospective therapeutic benefits. Remarkably, the Antimicrobial Peptide Database has been effectively utilized to generate various kinds of potential active de novo peptides. We proposed a pipeline for screening those generated peptides for a given target and used the main protease of SARS-COV-2 as a proof-of-concept. Moreover, we have developed a deep learning-based protein-peptide prediction model (DeepPep) for rapid screening of the generated peptides for the given targets. Together with the generating model, we have demonstrated that iteratively fine-tuning training, generating, and screening peptides for higher-predicted binding affinity peptides can be achieved. Our work sheds light on developing deep learning-based methods and pipelines to effectively generate and obtain bioactive peptides with a specific therapeutic effect and showcases how artificial intelligence can help discover de novo bioactive peptides that can bind to a particular target.

Promising antimicrobial protein from &lt;em&gt;Klebsiella&lt;/em&gt;

Increasing antibody resistance necessitates the use of new antimicrobial products. Antimicrobial peptides (AMP`s) And Proteins are a promising alternative to antibiotics currently being used due to their high degree of specificity & wide range of action Here we report a novel antimicrobial protein from iron reducing bacteria isolated from the coffee estate soils of Coorg district, Karnataka, India. Iron reducing bacteria are known to be antagonistic to others due to the presence of Pseuderophores. It makes them a good source of antimicrobial active principles. Fifteen isolates were obtained by selectively screening for iron reduction. These isolates were tested for antimicrobial activity against Gram positive [Staphylococcus aureus (MTCC3160), Bacillus cereus (MTCC6620)] & Gram negative [Escherichia coli (MTCC1650), Salmonella typhi (MTCC3224) and Pseudomonas aeruginosa (MTCC2453)] bacteria. Of the 15 isolates, one isolate, CBI-8, which showed good antimicrobial activity, was selected for further studies. The isolate was identified by MALDI-TOF & 16S rDNA sequencing as Klebsiella variicola/quasipneumonae (strain IS93) (genebank - MN814029). To induce and augment the production of antimicrobial molecules, CBI-8 was grown in the presence of Salmonella typhi and the spent medium was subjected to ammonium sulphate precipitation. The fractions which showed promising activity were further subjected to preparatory HPLC. The distinct bands obtained in the SDS-PAGE corresponding to the HPLC peak that showed antimicrobial activity from the induced sample was analyzed by Mass Spectrometry. Antimicrobial Peptide Database (APD3) calculator, Collection of Anti-Microbial Peptides (CAMPR3) software used to predict AMPs in the proteins identified from MS data.