CancerGram: An Effective Classifier for Differentiating Anticancer from Antimicrobial Peptides

Expanding the cryoprotectant toolbox in biomedicine by multifunctional antifreeze peptides

The global cryopreservation market size rises exponentially due to increased demand for cell therapy-based products, assisted reproductive technology, and organ transplantation. Cryoprotectants (CPAs) are required to reduce ice-related damage, osmotic cell injury, and protein denaturation. Antioxidants are needed to hamper membrane lipid peroxidation under freezing stress, and antibiotics are added to the cryo-solutions to prevent contamination. The vitrification process for sized organs requires a high concentration of CPA, which is hardly achievable using conventional penetrating toxic CPAs like DMSO. Antifreeze peptides (AFpeps) are biocompatible CPAs leveraging inspiration from nature, such as freeze-tolerant and freeze-avoidant organisms, to circumvent logistic limitations in cryogenic conditions. This study aims to introduce the advances of AFpeps with cell-penetrating, antioxidant, and antimicrobial characteristics. We herein revisit the placement of AFpeps in the biobanking of cancer cells, immune cells, stem cells, blood cells, germ cells (sperms and oocytes), and probiotics. Implementing low-immunogenic AFpeps for allograft cryopreservation minimizes HLA mismatching risk after organ transplantation. Applying AFpeps to formulate bioinks with optimal rheology in extrusion-based 3D cryobiopriners expedites the bench-to-beside transition of bioprinted scaffolds. This study advocates that the fine-tuned synthetic or insect-derived AFpeps, forming round blunt-shape crystals, are biomedically broad-spectrum, and cell-permeable AFpeps from marine and plant sources, which result in sharp ice crystals, are appropriate for cryosurgery. Perspectives of the available room for developing peptide mimetics in favor of higher activity and stability and peptide-functionalized nanoparticles for enhanced delivery are delineated. Finally, antitumor immune activation by cryoimmunotherapy as an autologous in-vivo tumor lysate vaccine has been illustrated.

Topology-Enhanced Machine Learning Model (Top-ML) for Anticancer Peptide Prediction

Recently, therapeutic peptides have demonstrated great promise for cancer treatment. To explore powerful anticancer peptides, artificial intelligence (AI)-based approaches have been developed to systematically screen potential candidates. However, the lack of efficient featurization of peptides has become a bottleneck for these machine-learning models. In this paper, we propose a topology-enhanced machine learning model (Top-ML) for anticancer peptide prediction. Our Top-ML employs peptide topological features derived from its sequence "connection" information characterized by spectral descriptors. Our Top-ML model, employing an Extra-Trees classifier, has been validated on the AntiCP 2.0 and mACPpred 2.0 benchmark data sets, achieving state-of-the-art performance or results comparable to existing deep learning models, while providing greater interpretability. Our results highlight the potential of leveraging novel topology-based featurization to accelerate the identification of anticancer peptides.

Structural information in therapeutic peptides: Emerging applications in biomedicine

Peptides are attracting a growing interest as therapeutic agents. This trend stems from their cost-effectiveness and reduced immunogenicity, compared to antibodies or recombinant proteins, but also from their ability to dock and interfere with large protein-protein interaction surfaces, and their higher specificity and better biocompatibility relative to organic molecules. Many tools have been developed to understand, predict, and engineer peptide function. However, most state-of-the-art approaches treat peptides only as linear entities and disregard their structural arrangement. Yet, structural details are critical for peptide properties such as solubility, stability, or binding affinities. Recent advances in peptide structure prediction have successfully addressed the scarcity of confidently determined peptide structures. This review will explore different therapeutic and biotechnological applications of peptides and their assemblies, emphasizing the importance of integrating structural information to advance these endeavors effectively.

Glioblastoma Multiforme: Sensitivity to Antimicrobial Peptides LL-37 and PG-1, and Their Combination with Chemotherapy for Predicting the Overall Survival of Patients

Background/Objectives: Glioblastomas (GBMs) are the most malignant and intractable of all cancers, with an unfavorable clinical prognosis for affected patients. The objective was to analyze the sensitivity of GBM cells to the antimicrobial peptides (AMPs) cathelicidin (LL-37) and protegrin-1 (PG-1), both alone and in combination with chemotherapy, to predict overall survival (OS) in the patients. Methods: The study was conducted on 27 GBM patients treated in the neurosurgical department of the Almazov Medical Research Centre (Saint Petersburg, Russia) from 2021 to 2024. The cytotoxic effects of chemotherapy, AMPs, and their combinations on brain tumor cells were assessed by an MTT assay using a 50% inhibitory concentration (IC50). Results: In GBM cells from the patients, LL-37 and PG-1 exhibited strong anticancer effects, surpassing those of chemotherapy drugs. These LL-37 and PG-1 anticancer effects were associated with a statistically significant increase in life expectancy and OS in GBM patients. These findings were confirmed by experiments on rats with C6 glioma, where the intranasal administration of LL-37 (300 μM) and PG-1 (600 μM) increased the life expectancy of the animals to 69 and 55 days, respectively, compared to 24 days in the control group (HR = 4.139, p = 0.0005; HR = 2.542, p = 0.0759). Conclusions: Additionally, the combination of LL-37 and PG-1 with chemotherapy drugs showed that a high IC50 of LL-37 with cisplatin (cutoff > 800 μM) in GBM cells was associated with increased life expectancy (19 vs. 5 months, HR = 4.708, p = 0.0101) and OS in GBM patients. These combinations could be used in future GBM treatments.

mACPpred 2.0: Stacked Deep Learning for Anticancer Peptide Prediction with Integrated Spatial and Probabilistic Feature Representations

Anticancer peptides (ACPs), naturally occurring molecules with remarkable potential to target and kill cancer cells. However, identifying ACPs based solely from their primary amino acid sequences remains a major hurdle in immunoinformatics. In the past, several web-based machine learning (ML) tools have been proposed to assist researchers in identifying potential ACPs for further testing. Notably, our meta-approach method, mACPpred, introduced in 2019, has significantly advanced the field of ACP research. Given the exponential growth in the number of characterized ACPs, there is now a pressing need to create an updated version of mACPpred. To develop mACPpred 2.0, we constructed an up-to-date benchmarking dataset by integrating all publicly available ACP datasets. We employed a large-scale of feature descriptors, encompassing both conventional feature descriptors and advanced pre-trained natural language processing (NLP)-based embeddings. We evaluated their ability to discriminate between ACPs and non-ACPs using eleven different classifiers. Subsequently, we employed a stacked deep learning (SDL) approach, incorporating 1D convolutional neural network (1D CNN) blocks and hybrid features. These features included the top seven performing NLP-based features and 90 probabilistic features, allowing us to identify hidden patterns within these diverse features and improve the accuracy of our ACP prediction model. This is the first study to integrate spatial and probabilistic feature representations for predicting ACPs. Rigorous cross-validation and independent tests conclusively demonstrated that mACPpred 2.0 not only surpassed its predecessor (mACPpred) but also outperformed the existing state-of-the-art predictors, highlighting the importance of advanced feature representation capabilities attained through SDL. To facilitate widespread use and accessibility, we have developed a user-friendly for mACPpred 2.0, available at https://balalab-skku.org/mACPpred2/.

Jackfruit Leaf Protein Hydrolysates Obtained by Enzymatic Hydrolysis of Leaf Protein Concentrate with Pepsin and Pancreatin: Molecular Weight, Cytotoxicity, Antiproliferative Activity, and Oxidative Stress

Jackfruit leaf protein hydrolysates obtained from the enzymatic hydrolysis of leaf protein concentrate with gastrointestinal enzymes have shown good techno-functional properties and high antioxidant capacity. However, molecular weight, antiproliferative activity, cytotoxicity and the ability to reduce reactive oxygen species (ROS) are still unknown. Therefore, this study aimed to evaluate the effect of jackfruit leaf protein hydrolysates obtained by enzymatic hydrolysis with pepsin and pancreatin at different hydrolysis times (30-240 min) on molecular weights, cytotoxicity, antiproliferation of cancer cells, and the reduction of reactive oxygen species in H2O2-induced HaCaT cells. The electrophoretic profile indicated that H-Pep contains peptides with molecular weights between 25 - 20 kDa. Meanwhile, H-Pan is composed of molecular weight products between 25 - 20 kDa and < 20 kDa. H-Pan and H-Pep (125-500 µg/mL) did not show significant cytotoxicity on HaCaT (human keratinocytes) and J774A.1 (murine macrophage cells). Antiproliferative activity was achieved in human cervical, ovarian, and liver cancer cells. H-Pan-240 min (1000 µg/mL) reduced the cell viability of cervical cancer cells by 23% while H-Pan-60 min significantly reduced cell viability of ovarian and liver cancer cells by 14.5 (500 µg/mL) and 17% (1000 µg/mL), respectively (P < 0.05). The protective effect against oxidative stress on H2O2-stressed HaCaT cells was obtained with H-Pep-60 min, which reduced 25% of ROS at 250 µg/mL (P < 0.05). The findings demonstrate the safe use of green biomass as a source of plant protein hydrolysates.

Peptidome Profiling of Bubalus bubalis Urine and Assessment of Its Antimicrobial Activity against Mastitis-Causing Pathogens

Urinary proteins have been studied quite exhaustively in the past, however, the small sized peptides have remained neglected for a long time in dairy cattle. These peptides are the products of systemic protein turnover, which are excreted out of the body and hence can serve as an important biomarker for various pathophysiologies. These peptides in other species of bovine have been reported to possess several bioactive properties. To investigate the urinary peptides in buffalo and simultaneously their bioactivities, we generated a peptidome profile from the urine of Murrah Buffaloes (n = 10). Urine samples were processed using <10 kDa MWCO filter and filtrate obtained was used for peptide extraction using Solid Phase Extraction (SPE). The nLC-MS/MS of the aqueous phase from ten animals resulted in the identification of 8165 peptides originating from 6041 parent proteins. We further analyzed these peptide sequences to identify bioactive peptides and classify them into anti-cancerous, anti-hypertensive, anti-microbial, and anti-inflammatory groups with a special emphasis on antimicrobial properties. With this in mind, we simultaneously conducted experiments to evaluate the antimicrobial properties of urinary aqueous extract on three pathogenic bacterial strains: S. aureus, E. coli, and S. agalactiae. The urinary peptides observed in the study are the result of the activity of possibly 76 proteases. The GO of these proteases showed the significant enrichment of the antibacterial peptide production. The total urinary peptide showed antimicrobial activity against the aforementioned pathogenic bacterial strains with no significant inhibitory effects against a buffalo mammary epithelial cell line. Just like our previous study in cows, the present study suggests the prime role of the antimicrobial peptides in the maintenance of the sterility of the urinary tract in buffalo by virtue of their amino acid composition.

Immunomodulatory Peptides as Vaccine Adjuvants and Antimicrobial Agents

The underdevelopment of adjuvant discovery and diversity, compared to core vaccine technology, is evident. On the other hand, antibiotic resistance is on the list of the top ten threats to global health. Immunomodulatory peptides that target a pathogen and modulate the immune system simultaneously are promising for the development of preventive and therapeutic molecules. Since investigating innate immunity in insects has led to prominent achievements in human immunology, such as toll-like receptor (TLR) discovery, we used the capacity of the immunomodulatory peptides of arthropods with concomitant antimicrobial or antitumor activity. An SVM-based machine learning classifier identified short immunomodulatory sequences encrypted in 643 antimicrobial peptides from 55 foe-to-friend arthropods. The critical features involved in efficacy and safety were calculated. Finally, 76 safe immunomodulators were identified. Then, molecular docking and simulation studies defined the target of the most optimal peptide ligands among all human cell-surface TLRs. SPalf2-453 from a crab is a cell-penetrating immunoadjuvant with antiviral properties. The peptide interacts with the TLR1/2 heterodimer. SBsib-711 from a blackfly is a TLR4/MD2 ligand used as a cancer vaccine immunoadjuvant. In addition, SBsib-711 binds CD47 and PD-L1 on tumor cells, which is applicable in cancer immunotherapy as a checkpoint inhibitor. MRh4-679 from a shrimp is a broad-spectrum or universal immunoadjuvant with a putative Th1/Th2-balanced response. We also implemented a pathway enrichment analysis to define fingerprints or immunological signatures for further in vitro and in vivo immunogenicity and reactogenicity measurements. Conclusively, combinatorial machine learning, molecular docking, and simulation studies, as well as systems biology, open a new opportunity for the discovery and development of multifunctional prophylactic and therapeutic lead peptides.

Lactoferricin B Combined with Antibiotics Exhibits Leukemic Selectivity and Antimicrobial Activity

The fusion of penetrating peptides (PPs), e.g., cell penetration peptides (CPPs) or antimicrobial peptides (AMPs), together with antimicrobial agents is an expanding research field. Specific AMPs, such as lactoferricin B (LfcinB), have demonstrated strong antibacterial, antifungal, and antiparasitic activity, as well as valuable anticancer activity, proving beneficial in the development of anticancer conjugates. The resulting conjugates offer potential dual functionality, acting as both an anticancer and an antimicrobial agent. This is especially necessary in cancer treatment, where microbial infections pose a critical risk. Leukemic cells frequently exhibit altered outer lipid membranes compared to healthy cells, making them more sensitive to compounds that interfere with their membrane. In this study, we revisited and reanalyzed our earlier research on LfcinB and its conjugates. Furthermore, we carried out new experiments with a specific focus on cell proliferation, changes in membrane asymmetric phosphatidylserine location, intracellular reactive oxygen species (ROS) generation, mitochondrial functions, and in vitro bacterial topoisomerase inhibition.

Short Fragmented Peptides from Pardachirus Marmoratus Exhibit Stronger Anticancer Activities in In Silico Residue Replacement and Analyses

BACKGROUND

Cancer is a worldwide issue. It has been observed that conventional therapies face many problems, such as side effects and drug resistance. Recent research reportedly used marine-derived products to treat various diseases and explored their potential in treating cancers.

OBJECTIVE

This study aims to discover short-length anticancer peptides derived from pardaxin 6 through an in silico approach.

METHODS

Fragmented peptides ranging from 5 to 15 amino acids were derived from the pardaxin 6 parental peptide. These peptides were further replaced with one residue and, along with the original fragmented peptides, were predicted for their SVM scores and physicochemical properties. The top 5 derivative peptides were further examined for their toxicity, hemolytic probability, peptide structures, docking models, and energy scores using various web servers. The trend of in silico analysis outputs across 5 to 15 amino acid fragments was further analyzed.

RESULTS

Results showed that when the amino acids were increased, SVM scores of the original fragmented peptides were also increased. Designed peptides had increased SVM scores, which was aligned with previous studies where the single residue replacement transformed the non-anticancer peptide into an anticancer agent. Moreover, in vitro studies validated that the designed peptides retained or enhanced anticancer effects against different cancer cell lines. Interestingly, a decreasing trend was observed in those fragmented derivative peptides.

CONCLUSION

Single residue replacement in fragmented pardaxin 6 was found to produce stronger anticancer agents through in silico predictions. Through bioinformatics tools, fragmented peptides improved the efficiency of marine-derived drugs with higher efficacy and lower hemolytic effects in treating cancers.

Dual-Activity Fluoroquinolone-Transportan 10 Conjugates Offer Alternative Leukemia Therapy during Hematopoietic Cell Transplantation

Hematopoietic cell transplantation (HCT) is often considered a last resort leukemia treatment, fraught with limited success due to microbial infections, a leading cause of mortality in leukemia patients. To address this critical issue, we explored a novel approach by synthesizing antileukemic agents containing antibacterial substances. This innovative strategy involves conjugating fluoroquinolone antibiotics, such as ciprofloxacin (CIP) or levofloxacin (LVX), with the cell-penetrating peptide transportan 10 (TP10). Here, we demonstrate that the resultant compounds display promising biologic activities in preclinical studies. These novel conjugates not only exhibit potent antimicrobial effects but are also selective against leukemia cells. The cytotoxic mechanism involves rapid disruption of cell membrane asymmetry leading to membrane damage. Importantly, these conjugates penetrated mammalian cells, accumulating within the nuclear membrane without significant effect on cellular architecture or mitochondrial function. Molecular simulations elucidated the aggregation tendencies of TP10 conjugates within lipid bilayers, resulting in membrane disruption and permeabilization. Moreover, mass spectrometry analysis confirmed efficient reduction of disulfide bonds within TP10 conjugates, facilitating release and activation of the fluoroquinolone derivatives. Intriguingly, these compounds inhibited human topoisomerases, setting them apart from traditional fluoroquinolones. Remarkably, TP10 conjugates generated lower intracellular levels of reactive oxygen species compared with CIP and LVX. The combination of antibacterial and antileukemic properties, coupled with selective cytostatic effects and minimal toxicity toward healthy cells, positions TP10 derivatives as promising candidates for innovative therapeutic approaches in the context of antileukemic HCT. This study highlights their potential in search of more effective leukemia treatments. SIGNIFICANCE STATEMENT: Fluoroquinolones are commonly used antibiotics, while transportan 10 (TP10) is a cell-penetrating peptide (CPP) with anticancer properties. In HCT, microbial infections are the primary cause of illness and death. Combining TP10 with fluoroquinolones enhanced their effects on different cell types. The dual pharmacological action of these conjugates offers a promising proof-of-concept solution for leukemic patients undergoing HCT. Strategically designed therapeutics, incorporating CPPs with antibacterial properties, have the potential to reduce microbial infections in the treatment of malignancies.

Dual-action potential of cationic cryptides against infections and cancers

Cryptides are a subfamily of bioactive peptides embedded latently in their parent proteins and have multiple biological functions. Cationic cryptides could be used as modern drugs in both infectious diseases and cancers because their mechanism of action is less likely to be affected by genetic mutations in the treated cells, therefore addressing a current unmet need in these two areas of medicine. In this review, we present the current understanding of cryptides, methods to mine them sustainably using available online databases and prediction tools, with a particular focus on their antimicrobial and anticancer potential, and their potential applicability in a clinical setting.

A novel L-phenylalanine dipeptide inhibits prostate cancer cell proliferation by targeting TNFSF9

In the present study, a series of novel L-phenylalanine dipeptides were designed and synthesized by a multi-step sequence of reactions, including carbodiimide-mediated condensation, hydrolysis, mixed anhydride condensation, and nucleophilic substitution. Among them, compound 7c exhibited potent antitumor activity against prostate cancer cell PC3 in vitro and in vivo via inducing apoptosis. We investigated the significantly differentially expressed proteins in the cells caused by the compound 7c to unravel the molecular mechanisms underlying the regulation of PCa cell growth, which indicated that 7c mainly regulated the protein expression of apoptosis-related transcription factors, including c-Jun, IL6, LAMB3, OSMR, STC1, OLR1, SDC4 and PLAU; and 7c also regulated the protein expression of inflammatory cytokines including IL6, CXCL8, TNFSF9, TNFRSF12A and OSMR, and the phosphorylation levels of RelA. The action target confirmed that TNFSF9 protein is the critical binding target of 7c. These findings suggested that 7c could regulate the apoptosis and inflammatory response related signaling pathways for the inhibition of the proliferation of PC3 cells, implying that 7c could be considered a promising therapeutic candidate for PCa therapy.

HBx downregulated decorin and decorin-derived peptides inhibit the proliferation and tumorigenicity of hepatocellular carcinoma cells

Hepatitis B virus (HBV) is one of the important risk factors in inducing the occurrence and development of liver cancer, while the mechanism has not been fully clarified. In this study, we found decorin (DCN) was significantly reduced in HBV transgenic cell line HepG2-4D14 compared to HepG2. The data from hepatocellular carcinoma (HCC) patients indicated that the level of DCN mRNA was significantly lower in tumor tissues than healthy control and positively correlated with the survival of HCC patients. We revealed that HBV HBx can inhibit the transcription of DCN by blocking p53 activity. Functional analysis demonstrated that overexpression of DCN substantially inhibits the proliferation of HCC cells, while knockdown of DCN enhances the proliferation of HCC cells. It is known that DCN could competitively bind to c-Met to inhibit HGF/c-Met signaling pathway to inhibit the development of HCC. Therefore, we screened the novel antitumor peptides derived from DCN based on the sequence of DCN and the complex structure of HGF/c-Met with virtual screening and identified a set of DCN-derived peptides (DCN-Ps) which may competitively bind to c-Met. We found that 5 of peptides can reduce the proliferation and migration of HepG2 cells significantly. Among them, DCN-P#3 can inhibit the growth of HCC cells both in vitro and in vivo. In conclusion, we discovered that HBV HBx downregulates the expression of DCN, which in turn promotes the proliferation of hepatocytes and the development of HCC. We identified DCN-derived antitumor peptides which provides the candidates for developing novel drugs against HCC.

ALA-A2 Is a Novel Anticancer Peptide Inspired by Alpha-Lactalbumin: A Discovery from a Computational Peptide Library, In Silico Anticancer Peptide Screening and In Vitro Experimental Validation

Anticancer peptides (ACPs) are rising as a new strategy for cancer therapy. However, traditional laboratory screening to find and identify novel ACPs from hundreds to thousands of peptides is costly and time consuming. Here, a sequential procedure is applied to identify candidate ACPs from a computer-generated peptide library inspired by alpha-lactalbumin, a milk protein with known anticancer properties. A total of 2688 distinct peptides, 5-25 amino acids in length, are generated from alpha-lactalbumin. In silico ACP screening using the physicochemical and structural filters and three machine learning models lead to the top candidate peptides ALA-A1 and ALA-A2. In vitro screening against five human cancer cell lines supports ALA-A2 as the positive hit. ALA-A2 selectively kills A549 lung cancer cells in a dose-dependent manner, with no hemolytic side effects, and acts as a cell penetrating peptide without membranolytic effects. Sequential window acquisition of all theorical fragment ions-proteomics and functional validation reveal that ALA-A2 induces autophagy to mediate lung cancer cell death. This approach to identify ALA-A2 is time and cost-effective. Further investigations are warranted to elucidate the exact intracellular targets of ALA-A2. Moreover, these findings support the use of larger computational peptide libraries built upon multiple proteins to further advance ACP research and development.

Piceatannol-3'-O-β-D-glucopyranoside attenuates colistin-induced neurotoxicity by suppressing oxidative stress via the NRF2/HO-1 pathway

BACKGROUND

Multidrug-resistant Gram-negative bacteria are the most pressing problem in treating infectious diseases. As one of the primary drugs for multidrug-resistant Gram-negative bacteria, the neurotoxicity of colistin has become a significant challenge in clinical practice.

PURPOSE

This study aimed to investigate the potential effect of piceatannol-3'-O-β-D glucopyranoside (PG) on colistin-induced neurotoxicity and the underlying mechanism.

METHODS

In vitro, nerve cell damage models were established by exposing N2a cells to 400 μM colistin for 24 h. The effects of PG on cell viability, apoptosis level, and oxidative stress level were analyzed. A western blot experiment was performed to determine the NRF2 pathway, apoptosis, and autophagy-related proteins. Mitochondrial morphology and mitochondrial membrane potential were detected after staining using laser confocal microscopy. In vivo, nerve injury mouse model was established by intracerebroventricular colistin administration. Morphological changes in brain tissues were observed using HE and Nissl staining.

RESULTS

PG significantly reduced colistin-induced neuronal apoptosis levels. The apoptosis-related protein expressions were suppressed after PG intervention. Mechanistically, PG increased the levels of antioxidant factors and decreased the levels of oxidative factors, which might be related to the activation of the NRF2 pathway. In addition, PG treatment reversed the deviations in mitochondrial morphology and membrane potential. PG suppressed autophagy levels in N2a cells, possibly because PG inhibited colistin-induced apoptosis, thus reducing the level of spontaneous protective autophagy in cells. Nrf2 knockdown N2a cell models were applied to confirm that the activation of the NRF2 pathway played a vital role in PG alleviating the nerve damage caused by colistin.

CONCLUSION

PG is a potential treatment option for colistin-induced neurotoxicity. It mitigated colistin-induced oxidative stress-associated injury and mitochondrial damage by activating the NRF2/HO-1 pathway, thus reducing nerve cell apoptosis.

Plasma metabolites-based design of long-acting peptides and their anticancer evaluation

Antimicrobial peptides (AMPs) are generally small cationic amphipathic peptides, which are thought to be ideal antineoplastic agents, owing to their favorable selectivity to cancer cells and the ability to overcome drug-resistance. In this study, an anticancer AMP (Mastoparan (INLKALAALAKKIL-NH2)) was selected as the lead compound and a series of Mastoparan derivatives were designed. Preliminary studies verified that an analogue of Mastoparan, KM8 (KLLKINLKALAALAKKIL-NH2), exhibited prominent selective antitumor effects. Instead, it presents a significant defect of metabolic instability, with a half-life in plasma of only about 0.5 h. Metabolite profiling of KM8 was performed and indicated the structure ₉AL₁₀ in peptide sequence could be the fragile site for KM8. Thus, the Aib (unnatural amnio acid) was employed to substitute the ₉Ala residue in KM8, and generating a long-acting KM8 derivative, namely KM8-Aib. Further investigations revealed KM8-Aib possessed higher metabolic stability, more potent anticancer activity in vitro & in vivo, and lower toxicity. Therefore, KM8-Aib is suggested be a potential antimalignant agent that worthy of more in-depth study.

Polypharmacological Cell-Penetrating Peptides from Venomous Marine Animals Based on Immunomodulating, Antimicrobial, and Anticancer Properties

Complex pathological diseases, such as cancer, infection, and Alzheimer's, need to be targeted by multipronged curative. Various omics technologies, with a high rate of data generation, demand artificial intelligence to translate these data into druggable targets. In this study, 82 marine venomous animal species were retrieved, and 3505 cryptic cell-penetrating peptides (CPPs) were identified in their toxins. A total of 279 safe peptides were further analyzed for antimicrobial, anticancer, and immunomodulatory characteristics. Protease-resistant CPPs with endosomal-escape ability in Hydrophis hardwickii, nuclear-localizing peptides in Scorpaena plumieri, and mitochondrial-targeting peptides from Synanceia horrida were suitable for compartmental drug delivery. A broad-spectrum S. horrida-derived antimicrobial peptide with a high binding-affinity to bacterial membranes was an antigen-presenting cell (APC) stimulator that primes cytokine release and naïve T-cell maturation simultaneously. While antibiofilm and wound-healing peptides were detected in Synanceia verrucosa, APC epitopes as universal adjuvants for antiviral vaccination were in Pterois volitans and Conus monile. Conus pennaceus-derived anticancer peptides showed antiangiogenic and IL-2-inducing properties with moderate BBB-permeation and were defined to be a tumor-homing peptide (THP) with the ability to inhibit programmed death ligand-1 (PDL-1). Isoforms of RGD-containing peptides with innate antiangiogenic characteristics were in Conus tessulatus for tumor targeting. Inhibitors of neuropilin-1 in C. pennaceus are proposed for imaging probes or therapeutic delivery. A Conus betulinus cryptic peptide, with BBB-permeation, mitochondrial-targeting, and antioxidant capacity, was a stimulator of anti-inflammatory cytokines and non-inducer of proinflammation proposed for Alzheimer's. Conclusively, we have considered the dynamic interaction of cells, their microenvironment, and proportional-orchestrating-host- immune pathways by multi-target-directed CPPs resembling single-molecule polypharmacology. This strategy might fill the therapeutic gap in complex resistant disorders and increase the candidates' clinical-translation chance.

Role of Anti-Cancer Peptides as Immunomodulatory Agents: Potential and Design Strategy

The usage of peptide-based drugs to combat cancer is gaining significance in the pharmaceutical industry. The collateral damage caused to normal cells due to the use of chemotherapy, radiotherapy, etc. has given an impetus to the search for alternative methods of cancer treatment. For a long time, antimicrobial peptides (AMPs) have been shown to display anticancer activity. However, the immunomodulatory activity of anti-cancer peptides has not been researched very extensively. The interconnection of cancer and immune responses is well-known. Hence, a search and design of molecules that can show anti-cancer and immunomodulatory activity can be lead molecules in this field. A large number of anti-cancer peptides show good immunomodulatory activity by inhibiting the pro-inflammatory responses that assist cancer progression. Here, we thoroughly review both the naturally occurring and synthetic anti-cancer peptides that are reported to possess both anti-cancer and immunomodulatory activity. We also assess the structural and biophysical parameters that can be utilized to improve the activity. Both activities are mostly reported by different groups, however, we discuss them together to highlight their interconnection, which can be used in the future to design peptide drugs in the field of cancer therapeutics.

Anti-cancer peptides: their current trends in the development of peptide-based therapy and anti-tumor drugs

Human cancer remains a cause of high mortality throughout the world. The conventional methods and therapies currently employed for treatment are followed by moderate-to-severe side effects. They have not generated curative results due to the ineffectiveness of treatments. Besides, the associated high costs, technical requirements, and cytotoxicity further characterize their limitations. Due to relatively higher presidencies, bioactive peptides with anti-cancer attributes have recently become treatment choices within the therapeutic arsenal. The peptides act as potential anti-cancer agents explicitly targeting tumor cells while being less toxic to normal cells. The anti-cancer peptides are isolated from various natural sources, exhibit high selectivity and high penetration efficiency, and could be quickly restructured. The therapeutic benefits of compatible anti-cancer peptides have contributed to the significant expansion of cancer treatment; albeit, the mechanisms by which bioactive peptides inhibit the proliferation of tumor cells remain unclear. This review will provide a framework for assessing anti-cancer peptides' structural and functional aspects. It shall provide appropriate information on their mode of action to support and strengthen efforts to improve cancer prevention. The article will mention the therapeutic health benefits of anti-cancer peptides. Their importance in clinical studies is elaborated for reducing cancer incidences and developing sustainable treatment models.

Overview of Host Defense Peptides with Promising Anti-Breast Cancer Activity

Breast cancer is the leading cause of death among women worldwide. The main limitations of conventional anti-cancer therapy, including breast cancer treatment, are side effects and the development of resistance to chemotherapeutics. Host defense peptides (HDPs) are bioactive compounds of innate immunity isolated from almost all living organisms, which exhibit wide range of biological activities. This review focuses on the anti-cancer effects of HDPs and their therapeutic potential against breast cancer. Numerous HDPs from different sources, including mammalian and amphibian origin, and their chemically modified analogues, exert the spectrum of anti-cancer activities. These effects include direct disruption of cancer cell membrane, induction of apoptosis, inhibition of angiogenesis and cancer cell proliferation, but also the modulation of anti-cancer immune response. Selected examples of HDPs of different origin and their anti-breast cancer capacities have been reviewed. Conclusively, due to their anti-cancer effects accompanied by substantial selectivity for cancer cells and low toxicity for normal cells, HDPs have been widely recognized as possible therapeutic agents.

Mitochondria-Targeted Drug Delivery

Mitochondria, organelles surrounded by a double membrane and with their own small genome, are the cells' energy centres [...].

Antimicrobial Peptides: An Update on Classifications and Databases

Antimicrobial peptides (AMPs) are distributed across all kingdoms of life and are an indispensable component of host defenses. They consist of predominantly short cationic peptides with a wide variety of structures and targets. Given the ever-emerging resistance of various pathogens to existing antimicrobial therapies, AMPs have recently attracted extensive interest as potential therapeutic agents. As the discovery of new AMPs has increased, many databases specializing in AMPs have been developed to collect both fundamental and pharmacological information. In this review, we summarize the sources, structures, modes of action, and classifications of AMPs. Additionally, we examine current AMP databases, compare valuable computational tools used to predict antimicrobial activity and mechanisms of action, and highlight new machine learning approaches that can be employed to improve AMP activity to combat global antimicrobial resistance.

Prediction of Anticancer Peptides with High Efficacy and Low Toxicity by Hybrid Model Based on 3D Structure of Peptides

Recently, anticancer peptides (ACPs) have emerged as unique and promising therapeutic agents for cancer treatment compared with antibody and small molecule drugs. In addition to experimental methods of ACPs discovery, it is also necessary to develop accurate machine learning models for ACP prediction. In this study, features were extracted from the three-dimensional (3D) structure of peptides to develop the model, compared to most of the previous computational models, which are based on sequence information. In order to develop ACPs with more potency, more selectivity and less toxicity, the model for predicting ACPs, hemolytic peptides and toxic peptides were established by peptides 3D structure separately. Multiple datasets were collected according to whether the peptide sequence was chemically modified. After feature extraction and screening, diverse algorithms were used to build the model. Twelve models with excellent performance (Acc > 90%) in the ACPs mixed datasets were used to form a hybrid model to predict the candidate ACPs, and then the optimal model of hemolytic peptides (Acc = 73.68%) and toxic peptides (Acc = 85.5%) was used for safety prediction. Novel ACPs were found by using those models, and five peptides were randomly selected to determine their anticancer activity and toxic side effects in vitro experiments.