Toxic Determination of Cry11 Mutated Proteins Obtained Using Rational Design and Its Computational Analysis.

Cry11 proteins are toxic to Aedes aegypti, the vector of dengue, chikungunya, and Zika viruses. Cry11Aa and Cry11Bb are protoxins, which when activated present their active-toxin form in two fragments between 30 and 35 kDa respectively. Previous studies conducted with Cry11Aa and Cry11Bb genes using DNA shuffling generated variant 8, which presented a deletion in the first 73 amino acids and one at position 572 and 9 substitutions including L553F and L556W. In this study, variant 8 mutants were constructed using site-directed mutagenesis, resulting in conversion of phenylalanine (F) and tryptophan (W) to leucine (L) at positions 553 and 556, respectively, producing the mutants 8F553L, 8W556L, and 8F553L/8W556L. Additionally, two mutants, A92D and C157R, derived from Cry11Bb were also generated. The proteins were expressed in the non-crystal strain BMB171 of Bacillus thuringiensis and subjected to median-lethal concentration (LC50) tests on first-instar larvae of A. aegypti. LC50 analysis showed that the 8F553L, 8W556L, 8F553L/8W556L, and C157R variants lost their toxic activity (>500 ng·mL-1), whereas the A92D protein presented a loss of toxicity of 11.4 times that of Cry11Bb. Cytotoxicity assays performed using variant 8, 8W556L and the controls Cry11Aa, Cry11Bb, and Cry-negative BMB171 on the colorectal cancer cell line SW480 reported 30-50% of cellular viability except for BMB171. Molecular dynamic simulations performed to identify whether the mutations at positions 553 and 556 were related to the stability and rigidity of the functional tertiary structure (domain III) of the Cry11Aa protein and variant 8 showed the importance of these mutations in specific regions for the toxic activity of Cry11 against A. aegypti. This generates pertinent knowledge for the design of Cry11 proteins and their biotechnological applications in vector-borne disease control and cancer cell lines.

Comparative Virucidal Activities of Essential Oils and Alcohol-Based Solutions against Enveloped Virus Surrogates: In Vitro and In Silico Analyses.

The large-scale use of alcohol (OH)-based disinfectants to control pathogenic viruses is of great concern because of their side effects on humans and harmful impact on the environment. There is an urgent need to develop safe and environmentally friendly disinfectants. Essential oils (EOs) are generally recognized as safe (GRAS) by the FDA, and many exhibit strong antiviral efficacy against pathogenic human enveloped viruses. The present study investigated the virucidal disinfectant activity of solutions containing EO and OH against DENV-2 and CHIKV, which were used as surrogate viruses for human pathogenic enveloped viruses. The quantitative suspension test was used. A solution containing 12% EO + 10% OH reduced > 4.0 log10 TCID50 (100% reduction) of both viruses within 1 min of exposure. In addition, solutions containing 12% EO and 3% EO without OH reduced > 4.0 log10 TCID50 of both viruses after 10 min and 30 min of exposure, respectively. The binding affinities of 42 EO compounds and viral envelope proteins were investigated through docking analyses. Sesquiterpene showed the highest binding affinities (from -6.7 to -8.0 kcal/mol) with DENV-2 E and CHIKV E1-E2-E3 proteins. The data provide a first step toward defining the potential of EOs as disinfectants.

Site-Directed Mutants of Parasporin PS2Aa1 with Enhanced Cytotoxic Activity in Colorectal Cancer Cell Lines.

Parasporin 2 has cytotoxic effects against numerous colon cancer cell lines, making it a viable alternative to traditional treatments. However, its mechanism of action and receptors remain unknown. In this study, site-directed mutagenesis was used to obtain PS2Aa1 mutants with variation in domain I at positions 256 and 257. Variants 015, 002, 3-3, 3-35, and 3-45 presented G256A, G256E, G257A, G257V, and G257E substitutions, respectively. Cytotoxicity tests were performed for the cell viability of cell lines SW480, SW620, and CaCo-2. Mutants 3-3, 3-35, and 3-45 efficiently killed the cell lines. It was found that the activated forms of caspase-3 and PARP were in higher abundance as well as increased production of γH2AX when 3-35 was used to treat CaCo-2 and SW480. To assess possible membrane-binding receptors involved in the interaction, an APN receptor blocking assay showed reduced activity of some parasporins. Hence, we performed molecular docking and molecular dynamics simulations to analyze the stability of possible interactions and identify the residues that could be involved in the protein-protein interaction of PS2Aa1 and APN. We found that residues 256 and 257 facilitate the interaction. Parasporin 3-35 is promising because it has higher cytotoxicity than PS2Aa1.

New PEPTIR-2.0 Peptide Designed for Use as Recognition Element in Electrochemical Biosensors with Improved Specificity towards E. coli O157:H7.

The detection of pathogens through alternative methodologies based on electrochemical biosensors is being studied. These devices exhibit remarkable properties, such as simplicity, specificity, and high sensitivity in monitoring pathogens. However, it is necessary to continue conducting studies that adequately improve these characteristics, especially the recognition molecule. This work aims to design and evaluate a new peptide, named PEPTIR-2.0, as a recognition molecule in electrochemical biosensors to detect E. coli O157:H7 in water. PEPTIR-2.0 was obtained from modifications of the PEPTIR-1.0 peptide sequence, which was previously reported and exhibited excellent properties for detecting and quantifying this pathogenic microorganism. PEPTIR-1.0 is a peptide analogous to the TIR (Translocated Intimin Receptor) protein capable of interacting with the Intimin outer membrane. The basis of this study was to obtain, by using bioinformatics tools, a molecule analogous to PEPTIR-1.0 that maintains its three-dimensional structure but increases the hydrophobic interactions between it and Intimin, since these intermolecular forces are the predominant ones. The designed PEPTIR-2.0 peptide was immobilized on screen-printed electrodes modified with gold nanoparticles. The detection capacity of E. coli O157:H7 in water was evaluated using electrochemical impedance spectroscopy in the presence of other microorganisms, such as P. aeruginosa, S. aureus, and non-pathogenic E. coli. The results showed that PEPTIR-2.0 confers remarkable specificity to the biosensor towards detecting E. coli, even higher than PEPTIR-1.0.

Essential Oils from Colombian Plants: Antiviral Potential against Dengue Virus Based on Chemical Composition, In Vitro and In Silico Analyses.

Currently, there are no therapies to prevent severe dengue disease. Essential oils (EOs) can serve as primary sources for research and the discovery of phytomedicines for alternative therapy. Fourteen EOs samples were obtained by distillation from six plants used in Colombian folk medicine. GC/MS analysis identified 125 terpenes. Cytopathic effect (CPE) reduction assays revealed differences in antiviral activity. EOs of Lippia alba, citral chemotype and carvone-rich fraction; Lippia origanoides, phellandrene chemotype; and Turnera diffusa, exhibited strong antiviral activity (IC50: 29 to 82 µg/mL; SI: 5.5 to 14.3). EOs of Piper aduncum, Ocimum basilicum, and L. origanoides, carvacrol, and thymol chemotypes, exhibited weak antiviral activity (32 to 53% DENV-CPE reduction at 100 µg/mL; SI > 5.0). Cluster and one-way ANOVA analyses suggest that the strong antiviral activity of EOs could be attributed to increased amounts of non-phenolic oxygenated monoterpenes and sesquiterpene hydrocarbons. Docking analyses (AutoDock Vina) predicted binding affinity between the DENV-2 E protein and terpenes: twenty sesquiterpene hydrocarbons (−8.73 to −6.91 kcal/mol), eight oxygenated monoterpenes (−7.52 to −6.98 kcal/mol), and seven monoterpene hydrocarbons (−7.60 to −6.99 kcal/mol). This study reports for the first time differences in the antiviral activity of EOs against DENV, corresponding to their composition of monoterpenes and sesquiterpenes.

A Bioinspired Peptide in TIR Protein as Recognition Molecule on Electrochemical Biosensors for the Detection of E. coli O157:H7 in an Aqueous Matrix.

Currently, the detection of pathogens such as Escherichia coli through instrumental alternatives with fast response and excellent sensitivity and selectivity are being studied. Biosensors are systems consisting of nanomaterials and biomolecules that exhibit remarkable properties such as simplicity, portable, affordable, user­friendly, and deliverable to end­users. For this, in this work we report for the first time, to our knowledge, the bioinformatic design of a new peptide based on TIR protein, a receptor of Intimin membrane protein which is characteristic of E. coli. This peptide (named PEPTIR­1.0) was used as recognition element in a biosensor based on AuNPs­modified screen­printed electrodes for the detection of E. coli. The morphological and electrochemical characteristics of the biosensor obtained were studied. Results show that the biosensor can detect the bacteria with limits of detection and quantification of 2 and 6 CFU/mL, respectively. Moreover, the selectivity of the system is statistically significant towards the detection of the pathogen in the presence of other microorganisms such as P. aeruginosa and S. aureus. This makes this new PEPTIR­1.0 based biosensor can be used in the rapid, sensitive, and selective detection of E. coli in aqueous matrices.

Genetic Modification Approaches for Parasporins Bacillus thuringiensis Proteins with Anticancer Activity.

Bacillus thuringiensis (Bt) is a bacterium capable of producing Cry toxins, which are recognized for their bio-controlling actions against insects. However, a few Bt strains encode proteins lacking insecticidal activity but showing cytotoxic activity against different cancer cell lines and low or no cytotoxicity toward normal human cells. A subset of Cry anticancer proteins, termed parasporins (PSs), has recently arisen as a potential alternative for cancer treatment. However, the molecular receptors that allow the binding of PSs to cells and their cytotoxic mechanisms of action have not been well established. Nonetheless, their selective cytotoxic activity against different types of cancer cell lines places PSs as a promising alternative treatment modality. In this review, we provide an overview of the classification, structures, mechanisms of action, and insights obtained from genetic modification approaches for PS proteins.

Comprehensive Analysis of Kisspeptin Signaling: Effects on Cellular Dynamics in Cervical Cancer.

Kisspeptin, a key neuropeptide derived from the KISS1R gene, is renowned for its critical role in regulating the hypothalamic-pituitary-gonadal axis and reproductive hormone secretion. Beyond its primary function in reproductive biology, emerging research has illuminated its influence in various cancers, mediating significant effects through its interaction with the G protein-coupled receptor, kisspeptin receptor. This interaction has been implicated in modulating cellular processes such as proliferation and metastasis, making it a potential target for therapeutic intervention. Our study initially screened ten kisspeptin-10 analogs through cytotoxic effects of kisspeptin-10 (KP10) and its analogs in several cancer types, including cervical, prostate, breast, and gastric cancers, with a particular focus on cervical cancer, where the most profound effects were observed. Further exploration using kinase array assays revealed that these analogs specifically alter key kinases involved in cancer progression. Migration assays demonstrated a substantial decrease in cell motility, and Bioluminescence Resonance Energy Transfer assays confirmed these analogs' strong interactions with the kisspeptin receptor. Overall, our results indicate that these KP10 analogs not only hinder cervical cancer cell proliferation but also curtail migration through targeted modulation of kinase signaling, suggesting their potential as therapeutic agents in managing cervical cancer progression. This comprehensive approach underscores the therapeutic promise of exploiting kisspeptin signaling in cancer treatment strategies.

Enhancing the Cytotoxicity and Apoptotic Efficacy of Parasporin-2-Derived Variants (Mpp46Aa1) on Cancer Cell Lines.

Parasporin PS2Aa1, recently renamed Mpp46Aa1, is an anti-cancer protein known for its selectivity against various human cancer cell lines. We genetically modified native PS2Aa1 to create a library of approximately 100 mutants. From this library, we selected promising mutants based on their half-maximal inhibitory concentration (IC50) and sequence variations. In this study, Variant 3-35, with the G257V substitution, demonstrated increased cytotoxicity and selectivity against the colon cancer cell line SW480. Conversely, Variant N65, featuring substitutions N92D, K175R, and S218G, yielded the most favorable results against the cancer cell lines SW-620, MOLT-4, and Jurkat. The caspase 3/7 and 9, Annexin V-Cy3 and 6-GFDA activities, and, most notably, mitochondrial membrane permeabilization assays confirmed the apoptotic marker elevation. These findings indicate that residues 92, 175, 218, and 257 may play a critical role in the cytotoxic activity and selectivity. We successfully obtained genetically improved variants with substitutions at these key amino acid positions. Additionally, we conducted molecular dynamic simulations to explore the potential interactions between PS2Aa1 and the CD59 GPI-anchored protein. The simulation results revealed that residues 57, 92, and 101 were consistently present, suggesting their possible significance in the interactions between parasporin and the CD59 protein.

Artificial Intelligence and Quantum Computing as the Next Pharma Disruptors.

Artificial intelligence (AI) consists of a synergistic assembly of enhanced optimization strategies with wide application in drug discovery and development, providing advanced tools for promoting cost-effectiveness throughout drug life cycle. Specifically, AI brings together the potential to improve drug approval rates, reduce development costs, get medications to patients faster, and help patients complying with their treatments. Accelerated pharmaceutical development and drug product approval rates can further benefit from the quantum computing (QC) technology, which will ultimately enable larger profits from patent-protected market exclusivity.Key pharma stakeholders are endorsing cutting-edge technologies based on AI and QC , covering drug discovery, preclinical and clinical development, and postapproval activities. Indeed, AI-QC applications are expected to become standard in the pharma operating model over the next 5-10 years. Generalizing scalability to larger pharmaceutical problems instead of specialization is now the main principle for transforming pharmaceutical tasks on multiple fronts, for which systematic and cost-effective solutions have benefited in areas such as molecular screening, synthetic pathway design, and drug discovery and development.The information generated by coupling the life cycle of drugs and AI and/or QC through data-driven analysis, neural network prediction, and chemical system monitoring will enable (1) better understanding of the complexity of process data, (2) streamlining the design of experiments, (3) discovering new molecular targets and materials, and also (4) planning or rethinking upcoming pharmaceutical challenges The power of AI-QC makes accessible a range of different pharmaceutical problems and their rationalization that have not been previously addressed due to a lack of appropriate analytical tools, demonstrating the breadth of potential applications of these emerging multidimensional approaches. In this context, creating the right AI-QC strategy often involves a steep learning path, especially given the embryonic stage of the industry development and the relative lack of case studies documenting success. As such, a comprehensive knowledge of the underlying pillars is imperative to extend the landscape of applications across the drug life cycle.The topics enclosed in this chapter will focus on AI-QC methods applied to drug discovery and development, with emphasis on the most recent advances in this field.

Chemoinformatics and artificial intelligence colloquium: progress and challenges in developing bioactive compounds.

We report the main conclusions of the first Chemoinformatics and Artificial Intelligence Colloquium, Mexico City, June 15-17, 2022. Fifteen lectures were presented during a virtual public event with speakers from industry, academia, and non-for-profit organizations. Twelve hundred and ninety students and academics from more than 60 countries. During the meeting, applications, challenges, and opportunities in drug discovery, de novo drug design, ADME-Tox (absorption, distribution, metabolism, excretion and toxicity) property predictions, organic chemistry, peptides, and antibiotic resistance were discussed. The program along with the recordings of all sessions are freely available at https://www.difacquim.com/english/events/2022-colloquium/ .

Computational study, synthesis and evaluation of active peptides derived from Parasporin-2 and spike protein from Alphacoronavirus against colorectal cancer cells.

Parasporin-2Aa1 (PS2Aa1) is a toxic protein of 37 KDa (30 kDa, activated form produced by proteolysis) that was shown to be cytotoxic against specific human cancer cells, although its mechanism of action has not been elucidated yet. In order to study the role of some native peptide fragments of proteins on anticancer activity, here we investigated the cytotoxic effect of peptide fragments from domain-1 of PS2Aa1 and one of the loops present in the binding region of the virus spike protein from Alphacoronavirus (HCoV-229E), the latter according to scientific reports, who showed interaction with the human APN (h-APN) receptor, evidence corroborated through computational simulations, and thus being possible active against colon cancer cells. Peptides namely P264-G274, Loop1-PS2Aa, and Loop2-PS2Aa were synthesized using the Fmoc solid-phase synthesis and characterized by mass spectrometry (MS). Additionally, one region from loop 1 of HCoV-229E, Loop1-HCoV-229E, was also synthesized and characterized. The A4W-GGN5 anticancer peptide and 5-fluorouracil (5-FU) were taken as a control in all experiments. Circular dichroism revealed an α-helix structure for the peptides derived from PS2Aa1 (P264-G274, Loop1-PS2Aa, and Loop2-PS2Aa) and ß-laminar structure for the peptide derived from Alphacoronavirus spike protein Loop1-HCoV-229E. Peptides showed a hemolysis percentage of less than 20% at 100 µM concentration. Besides, peptides exhibited stronger anticancer activity against SW480 and SW620 cells after exposure for 48 h. Likewise, these compounds showed significantly lower toxicity against normal cells CHO-K1. The results suggest that native peptide fragments from Ps2Aa1 may be optimized as a novel potential cancer-therapeutic agents.

Identification of potential natural neuroprotective molecules for Parkinson's disease by using chemoinformatics and molecular docking.

Parkinson's disease is a progressive nervous system disorder characterized by motor, cognitive, sensory, psychiatric, and autonomic disturbances. While there is currently no cure for Parkinson's Disease, medication can offer relief from its symptoms for many years. Although these medications are considered safe, they can present acute or chronic side effects and can become less effective over time. Thus, new medications are highly needed. In this regard, α-synuclein is a protein of great interest to Parkinson's researchers because it is a major constituent of Lewy bodies, which are protein clumps being the pathological hallmark of Parkinson's disease. However, current medications are not focused on the inhibition of α-synuclein oligomerization, and therefore, therapeutics preventing the formation of these bodies through the inhibition of α-synuclein oligomerization may play a role in the fight against this and other synucleinopathies. In this study, we used chemoinformatics tools and molecular docking simulations to analyze molecules that have been experimentally tested and bound to α-synuclein, causing neuroprotective or neurotoxic activity, and whose results have been used to select potential natural neuroprotective molecules. We identified 6 potential natural neuroprotective molecules that are similar in their chemical structure to neuroprotective molecules and have a high number of hydrogen bonds with α-synuclein. We expect that these molecules may lead to the design or discovery of new effective treatments for Parkinson's disease.

Softepigen: Primers Design Web-Based Tool for MS-HRM Technique.

Polymerase Chain Reaction (PCR) based techniques for DNA methylation techniques includes the MS-HRM technique. Methylation Sensitive High-Resolution Melting (MS-HRM) primer-design requires a set of necessary recommendations for such DNA methylation assessment. However, there were not any available software that allows an automatic design of this kind primers. We present Softepigen, the first complete MS-HRM primer design software. Softepigen allows to search for primers in a genomic region following Wojdacz's recommendations and targets primer binding regions with high linguistic complexity sequences that increase the specificity of the converted sequence of the human genome. We performed in-silico PCR analysis through BiSearch ePCR tool to validate the specificity of the of the primers designed using Softepigen. Softepigen for MS-HRM performance in our genomic regions of interest show satisfactory specificity measurements, and we implemented it for freely available use in the web-based interface at www.soft-epigen.com.

Computer Aided Design of Non-toxic Antibacterial Peptides.

Antimicrobial resistance is increasing at an alarming rate and the number of new antibiotics developed and approved has decreased in the last decades, basically for economic and regulatory obstacles. Pathogenic bacteria that are resistant to multiple or all available antibiotics are isolated frequently. Hence, new antibacterial agents are urgently needed and antimicrobial peptides are being considered as a potential solution to this important threat. These molecules are small host defense proteins that are part of the immune systems of most living organisms such as plants, bacteria, invertebrates, vertebrates, and mammals. These peptides are found in those parts of organisms that are exposed to pathogens and they are active against multiple organisms such as virus, bacteria, and parasites, among others. This review shows different strategies in the computational design of new antibacterial peptides, the physicochemical properties that are considered as the most relevant for the antibacterial activity and toxicity, and it suggests guidelines in order to help in the finding of new non-toxic antibacterial peptides through the development of computational models.

Essential oil of Cordia curassavica (Jacq) Roem. & Schult: in vitro and in silico evaluation of effects on dengue virus replication and cytokines production / Aceite esencial de Cordia curassavica (Jacq) Roem. & Schult: evaluación in vitro e in silico del efecto sobre la replicación del virus dengue y la producción de citoquinas

The lack of effective conventional therapie s against dengue has created an interest in herbal preparations as alternative therapies. In the present study, in vitro effects of Cordia curassavica essential oil (EO) on both dengue virus replication and cytokine production were examined. Predictions of molecular interactions between EO compounds and virus and cell proteins were performed with AutoDock Vina. The EO inhibited replication of dengue virus serotypes at IC 50 < 30 µg/mL, and it reduced 87% TNF - α, 67% IL - 8 and 46% IFN - α in LPS - stimulated PBMCs. The main EO compounds were trans - ß - caryophyllene (21.4%), germacrene D (17.8%), α - copaene (16.5%), trans - ß - guaiene (8.2%), and α - pinene (6.0%). The first two compounds, δ - cadinene, α - muurolene, α - cubebene and ß - burbonene were coupled to proteins involved in the TLR - 4 cytokine effector pathway. 3,7 - Guaiadiene was coupled to the viral E and C proteins. This study demonstrates the potential of C. curassavica EO as a starting point for discovering novel therapeutic for dengue.

La falta de terapias eficaces para el dengue ha suscitado interés por preparados herbales como terapias alternativas. En el presente estudio se examinaron efectos in vitro del aceite e sencial (AE) de Cordia curassavica sobre la replicación del virus dengue y producción de citoquinas. Se realizaron predicciones de interacciones moleculares entre los compuestos del AE y proteínas virales y celulares con AutoDock Vina. El AE inhibió la rep licación de serotipos del virus a CI 50 < 30 µg/mL y redujo 87% TNF - α, 67% IL - 8 y 46% IFN - α en MNCP. Los principales compuestos del AE fueron trans - ß - cariofileno, germacreno D, α - copaeno, trans - ß - guaieno y α - pineno. Los dos primeros compuestos, el δ - cadineno, el α - muuroleno, el α - cubebeno y el ß - burboneno se acoplaron a proteínas implicadas en la vía efectora de citoquinas TLR - 4. El 3,7 - guaiadiene se acopló a las proteínas virales E y C. Este estudio demuestra el potencial del AE de C. curassavica como punto de partida para descubrir nuevas tera pias para el dengue.

Design of Bactericidal Peptides Against Escherichia coli O157:H7, Pseudomonas aeruginosa and methicillin-resistant Staphylococcus aureus.

BACKGROUND: Antimicrobial peptides are on the first line of defense against pathogenic microorganisms of many living beings. These compounds are considered natural antibiotics that can overcome bacterial resistance to conventional antibiotics. Due to this characteristic, new peptides with improved properties are quite appealing for designing new strategies for fighting pathogenic bacteria. METHODS: Sixteen designed peptides were synthesized using Fmoc chemistry; five of them are new cationic antimicrobial peptides (CAMPs) designed using a genetic algorithm that optimizes the antibacterial activity based on selected physicochemical descriptors and 11 analog peptides derived from these five peptides were designed and constructed by single amino acid substitutions. These 16 peptides were structurally characterized and their biological activity was determined against Escherichia coli O157:H7 (E. coli O157:H7), and methicillin-resistant strains of Staphylococcus aureus (MRSA) and Pseudomonas aeruginosa (P. aeruginosa) were determined. RESULTS: These 16 peptides were folded into an α-helix structure in membrane-mimicking environment. Among these 16 peptides, GIBIM-P5S9K (ATKKCGLFKILKGVGKI) showed the highest antimicrobial activity against E. coli O157:H7 (MIC=10µM), methicillin-resistant Staphylococcus aureus (MRSA) (MIC=25µM) and Pseudomonas aeruginosa (MIC=10 µM). Peptide GIBIM-P5S9K caused permeabilization of the bacterial membrane at 25 µM as determined by the Sytox Green uptake assay and the labelling of these bacteria by using the fluoresceinated peptide. GIBIM-P5S9K seems to be specific for these bacteria because at 50 µM, it provoked lower than 40% of erythrocyte hemolysis. CONCLUSION: New CAMPs have been designed using a genetic algorithm based on selected physicochemical descriptors and single amino acid substitution. These CAMPs interacted quite specifically with the bacterial cell membrane, GIBIM-P5S9K exhibiting high antibacterial activity on Escherichia coli O157:H7, methicillin-resistant strains of Staphylococcus aureus and P. aeruginosa.

Machine learning in the rational design of antimicrobial peptides.

One of the most important public health issues is the microbial and bacterial resistance to conventional antibiotics by pathogen microorganisms. In recent years, many researches have been focused on the development of new antibiotics. Among these, antimicrobial peptides (AMPs) have raised as a promising alternative to combat antibioticresistant microorganisms. For this reason, many theoretical efforts have been done in the development of new computational tools for the rational design of both better and effective AMPs. In this review, we present an overview of the rational design of AMPs using machine learning techniques and new research fields.