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

Diverse roles of aldolase enzymes in cancer development, drug resistance and therapeutic approaches as moonlighting enzymes

Aldolase enzymes, particularly ALDOA, ALDOB, and ALDOC, play a crucial role in the development and progression of cancer. While the aldolase family is mainly known for its involvement in the glycolysis pathway, these enzymes also have various pathological and physiological functions through distinct signaling pathways such as Wnt/β-catenin, EGFR/MAPK, Akt, and HIF-1α. This has garnered increased attention in recent years and shed light on other sides of this enzyme. Potential therapeutic strategies targeting aldolases include using siRNA, inhibitors like naphthol AS-E phosphate and TX-2098, and natural compounds such as HDPS-4II and L-carnosine. Additionally, anticancer peptides derived from ALDOA, like P04, can potentially increase cancer cells' sensitivity to chemotherapy. Aldolases also affect cancer drug resistance by different approaches, making them good therapeutic targets. In this review, we extensively explore the role of aldolase enzymes in various types of cancers in proliferation, invasion, migration, and drug resistance; we also significantly explore the possible treatment considering aldolase function.

Rational design of a new short anticancer peptide with good potential for cancer treatment

Anticancer peptides (ACPs) have regarded as a new generation of promising antitumor drugs due to the unique mode of action. The main challenge is to develop potential anticancer peptides with satisfied antitumor activity and low toxicity. Here, a series of new α-helical anticancer peptides were designed and synthesized based on the regular repeat motif KLLK. The optimal peptides 14E and 14Aad were successfully derived from the new short α-helical peptide KL-8. Our results demonstrated that 14E and 14Aad had good antitumor activity and low toxicity, exhibiting excellent selectivity index. This result highlighted that the desirable modification position and appropriate hydrophobic side-chain structure of acidic amino acids played critical roles in regulating the antitumor activity/toxicity of new peptides. Further studies indicated that they could induce tumor cell death via the multiple actions of efficient membrane disruption and intracellular mechanisms, displaying apparent superiority in combination with PTX. In addition, the new peptides 14E and 14Aad showed excellent antitumor efficacy in vivo and low toxicity in mice compared to KL-8 and PTX. Particularly, 14Aad with the longer side chain at the 14th site exhibited the best therapeutic performance. In conclusion, our work provided a new avenue to develop promising anticancer peptides with good selectivity for tumor therapy.

ACP-PDAFF: Pretrained model and dual-channel attentional feature fusion for anticancer peptides prediction

Anticancer peptides(ACPs) have attracted significant interest as a novel method of treating cancer due to their ability to selectively kill cancer cells without damaging normal cells. Many artificial intelligence-based methods have demonstrated impressive performance in predicting ACPs. Nevertheless, the limitations of existing methods in feature engineering include handcrafted features driven by prior knowledge, insufficient feature extraction, and inefficient feature fusion. In this study, we propose a model based on a pretrained model, and dual-channel attentional feature fusion(DAFF), called ACP-PDAFF. Firstly, to reduce the heavy dependence on expert knowledge-based handcrafted features, binary profile features (BPF) and physicochemical properties features(PCPF) are used as inputs to the transformer model. Secondly, aimed at learning more diverse feature informations of ACPs, a pretrained model ProtBert is utilized. Thirdly, for better fusion of different feature channels, DAFF is employed. Finally, to evaluate the performance of the model, we compare it with other methods on five benchmark datasets, including ACP-Mixed-80 dataset, Main and Alternate datasets of AntiCP 2.0, LEE and Independet dataset, and ACPred-Fuse dataset. And the accuracies obtained by ACP-PDAFF are 0.86, 0.80, 0.94, 0.97 and 0.95 on five datasets, respectively, higher than existing methods by 1% to 12%. Therefore, by learning rich feature informations and effectively fusing different feature channels, ACD-PDAFF achieves outstanding performance. Our code and the datasets are available at https://github.com/wongsing/ACP-PDAFF.

MMDB: Multimodal dual-branch model for multi-functional bioactive peptide prediction

Bioactive peptides can hinder oxidative processes and microbial spoilage in foodstuffs and play important roles in treating diverse diseases and disorders. While most of the methods focus on single-functional bioactive peptides and have obtained promising prediction performance, it is still a significant challenge to accurately detect complex and diverse functions simultaneously with the quick increase of multi-functional bioactive peptides. In contrast to previous research on multi-functional bioactive peptide prediction based solely on sequence, we propose a novel multimodal dual-branch (MMDB) lightweight deep learning model that designs two different branches to effectively capture the complementary information of peptide sequence and structural properties. Specifically, a multi-scale dilated convolution with Bi-LSTM branch is presented to effectively model the different scales sequence properties of peptides while a multi-layer convolution branch is proposed to capture structural information. To the best of our knowledge, this is the first effective extraction of peptide sequence features using multi-scale dilated convolution without parameter increase. Multimodal features from both branches are integrated via a fully connected layer for multi-label classification. Compared to state-of-the-art methods, our MMDB model exhibits competitive results across metrics, with a 9.1% Coverage increase and 5.3% and 3.5% improvements in Precision and Accuracy, respectively.

pDNA-tachyplesin treatment stimulates the immune system and increases the probability of apoptosis in MC4-L2 tumor cells

Breast cancer is the most common cancer among women worldwide, and marine creatures are the most abundant reservoir of anticancer medicines. Tachyplesin peptides have shown antibacterial capabilities, but their potential to inhibit cancer growth and trigger cancer cell death has not been investigated. A synthetic tachyplesin nucleotide sequence was generated and inserted into the pcDNA3.1( +) Mammalian Expression Vector. PCR analysis and enzyme digesting procedures were used to evaluate the vectors' accuracy. The transfection efficiency of MCF-7 and MCF10-A cells was 57% and 65%, respectively. The proliferation of MCF-7 cancer cells was markedly suppressed. Administration of plasmid DNA (pDNA) combined with tachyplesin to mice with tumors did not cause any discernible morbidity or mortality throughout treatment. The final body weight curves revealed a significant reduction in weight among mice treated with pDNA/tachyplesin and tachyplesin at a dose of 100 µg/ml (18.4 ± 0.24 gr, P < 0.05; 11.4 ± 0.24 gr P < 0.01) compared to the control group treated with PBS (22 ± 0.31 gr). Animals treated with pDNA/tachyplesin and tachyplesin exhibited a higher percentage of CD4 + Foxp3 + Tregs, CD8 + Foxp3 + Tregs, and CD4 + and CD8 + T cell populations expressing CTLA-4 in their lymph nodes and spleen compared to the PBS group. The groups that received pDNA/tachyplesin exhibited a substantial upregulation in the expression levels of caspase-3, caspase-8, BAX, PI3K, STAT3, and JAK genes. The results offer new possibilities for treating cancer by targeting malignancies using pDNA/tachyplesin and activating the mTOR and NFκB signaling pathways.

Package delivered: folate receptor-mediated transporters in cancer therapy and diagnosis

Neoplasias pose a significant threat to aging society, underscoring the urgent need to overcome the limitations of traditional chemotherapy through pioneering strategies. Targeted drug delivery is an evolving frontier in cancer therapy, aiming to enhance treatment efficacy while mitigating undesirable side effects. One promising avenue utilizes cell membrane receptors like the folate receptor to guide drug transporters precisely to malignant cells. Based on the cellular folate receptor as a cancer cell hallmark, targeted nanocarriers and small molecule-drug conjugates have been developed that comprise different (bio) chemistries and/or mechanical properties with individual advantages and challenges. Such modern folic acid-conjugated stimuli-responsive drug transporters provide systemic drug delivery and controlled release, enabling reduced dosages, circumvention of drug resistance, and diminished adverse effects. Since the drug transporters' structure-based de novo design is increasingly relevant for precision cancer remediation and diagnosis, this review seeks to collect and debate the recent approaches to deliver therapeutics or diagnostics based on folic acid conjugated Trojan Horses and to facilitate the understanding of the relevant chemistry and biochemical pathways. Focusing exemplarily on brain and breast cancer, recent advances spanning 2017 to 2023 in conjugated nanocarriers and small molecule drug conjugates were considered, evaluating the chemical and biological aspects in order to improve accessibility to the field and to bridge chemical and biomedical points of view ultimately guiding future research in FR-targeted cancer therapy and diagnosis.

Anticancer activities of natural antimicrobial peptides from animals

Cancer is the most common cause of human death worldwide, posing a serious threat to human health and having a negative impact on the economy. In the past few decades, significant progress has been made in anticancer therapies, but traditional anticancer therapies, including radiation therapy, surgery, chemotherapy, molecular targeted therapy, immunotherapy and antibody-drug conjugates (ADCs), have serious side effects, low specificity, and the emergence of drug resistance. Therefore, there is an urgent need to develop new treatment methods to improve efficacy and reduce side effects. Antimicrobial peptides (AMPs) exist in the innate immune system of various organisms. As the most promising alternatives to traditional drugs for treating cancers, some AMPs also have been proven to possess anticancer activities, which are defined as anticancer peptides (ACPs). These peptides have the advantages of being able to specifically target cancer cells and have less toxicity to normal tissues. More and more studies have found that marine and terrestrial animals contain a large amount of ACPs. In this article, we introduced the animal derived AMPs with anti-cancer activity, and summarized the types of tumor cells inhibited by ACPs, the mechanisms by which they exert anti-tumor effects and clinical applications of ACPs.

Jelleine, a Family of Peptides Isolated from the Royal Jelly of the Honey Bees (Apis mellifera), as a Promising Prototype for New Medicines: A Narrative Review

The jelleine family is a group of four peptides (jelleines I-IV) originally isolated from the royal jelly of honey bee (Apis mellifera), but later detected in some honey samples. These oligopeptides are composed of 8-9 amino acid residues, positively charged (+2 to +3 at pH 7.2), including 38-50% of hydrophobic residues and a carboxamide C-terminus. Jelleines, generated by processing of the C-terminal region of major royal jelly proteins 1 (MRJP-1), play an important biological role in royal jelly conservation as well as in protecting bee larvae from potential pathogens. Therefore, these molecules present numerous benefits for human health, including therapeutic purposes as shown in preclinical studies. In this review, we aimed to evaluate the biological effects of jelleines in addition to characterising their toxicities and stabilities. Jelleines I-III have promising antimicrobial activity and low toxicity (LD50 > 1000 mg/Kg). However, jelleine-IV has not shown relevant biological potential. Jelleine-I, but not the other analogues, also has antiparasitic, healing, and pro-coagulant activities in addition to indirectly modulating tumor cell growth and controlling the inflammatory process. Although it is sensitive to hydrolysis by proteases, the addition of halogens increases the chemical stability of these molecules. Thus, these results suggest that jelleines, especially jelleine-I, are a potential target for the development of new, effective and safe therapeutic molecules for clinical use.

Plant-based proteins: advanced extraction technologies, interactions, physicochemical and functional properties, food and related applications, and health benefits

Even though plant proteins are more plentiful and affordable than animal proteins in comparison, direct usage of plant-based proteins (PBPs) is still limited because PBPs are fed to animals as feed to produce animal-based proteins. Thus, this work has comprehensively reviewed the effects of various factors such as pH, temperature, pressure, and ionic strength on PBP properties, as well as describes the protein interactions, and extraction methods to know the optimal conditions for preparing PBP-based products with high functional properties and health benefits. According to the cited studies in the current work, the environmental factors, particularly pH and ionic strength significantly affected on physicochemical and functional properties of PBPs, especially solubility was 76.0% to 83.9% at pH = 2, while at pH = 5.0 reduced from 5.3% to 9.6%, emulsifying ability was the lowest at pH = 5.8 and the highest at pH 8.0, and foaming capacity was lowest at pH 5.0 and the highest at pH = 7.0. Electrostatic interactions are the main way for protein interactions, which can be used to create protein/polysaccharide complexes for food industrial purposes. The extraction yield of proteins can be reached up to 86-95% with high functional properties using sustainable and efficient routes, including enzymatic, ultrasound-, microwave-, pulsed electric field-, and high-pressure-assisted extraction. Nondairy alternative products, especially yogurt, 3D food printing and meat analogs, synthesis of nanoparticles, and bioplastics and packaging films are the best available PBPs-based products. Moreover, PBPs particularly those that contain pigments and their products showed good bioactivities, especially antioxidants, antidiabetic, and antimicrobial.

Evaluation of glycyl-arginine and lysyl-aspartic acid dipeptides for their antimicrobial, antibiofilm, and anticancer potentials

Antibacterial resistance and cancer are worldwide challenges and have been defined as major threats by international health organizations. Peptides are produced naturally by all organisms and have a variety of immunomodulatory, physiological, and wound-healing properties. They can also provide protection against microorganisms and tumor cells. Therefore, we aimed to determine the antimicrobial, antibiofilm, and anticancer potentials of Glycyl-Arginine and Lysyl-Aspartic acid dipeptides. The Broth Dilution and Crystal Violet Binding assays assessed the antimicrobial tests and biofilm inhibitory effects. The MTT assay was used to measure the cytotoxic effects of dipeptides on HeLa cell viability. According to our results, Candida tropicalis T26 and Proteus mirabilis U15 strains were determined as more resistant to Staphylococcus epidermidis W17 against Glycyl-Arginine and Lysyl-Aspartic acid dipeptides with MICs higher than 2 mM (1 mg/mL). Sub-MICs of Glycyl-Arginine caused inhibitions against biofilm formation of all the tested clinical isolates, with the highest inhibition observed against S. epidermidisW17. Lysyl-Aspartic acid exhibited zero to no effect against biofilm formation of P. mirabilisU15, and S. epidermidisW17, whereas it exhibited 52% inhibition of biofilm formation of C. tropicalisT26. Cell viability results revealed that HeLa cell viability decreases with increasing concentration of both dipeptides. Also, parallel to antimicrobial tests, Glycyl-Arginine has a greater cytotoxic effect compared to Lysyl-Aspartic acid. The findings from this study will contribute to the advancement of novel strategies involving dipeptide-based synthesizable molecules and drug development studies. However, it is essential to note that there are still challenges, including the need for extensive experimental and clinical trials.

Recent advances in anticancer peptoids

Since most tumors become resistant to drugs in a gradual and irreversible manner, making treatment less effective over time, anticancer drugs require continuous development. Peptoids are a class of peptidomimetics that can be easily synthesized and optimized. They exhibit a number of unique characteristics, including protease resistance, non-immunogenicity, do not interfere with peptide functionality and skeleton polarity, and can adopt different conformations. They have been studied for their efficacy in different cancer therapies, and can be considered as a promising alternative molecular category for the development of anticancer drugs. Herein, we discuss the extensive recent advances in peptoids and peptoid hybrids in the treatment of cancers such as prostate, breast, lung, and other ones, in the hope of providing a reference for the further development of peptoid anticancer drugs.

An Augmented Sample Selection Framework for Prediction of Anticancer Peptides

Anticancer peptides (ACPs) have promising prospects for cancer treatment. Traditional ACP identification experiments have the limitations of low efficiency and high cost. In recent years, data-driven deep learning techniques have shown significant potential for ACP prediction. However, data-driven prediction models rely heavily on extensive training data. Furthermore, the current publicly accessible ACP dataset is limited in size, leading to inadequate model generalization. While data augmentation effectively expands dataset size, existing techniques for augmenting ACP data often generate noisy samples, adversely affecting prediction performance. Therefore, this paper proposes a novel augmented sample selection framework for the prediction of anticancer peptides (ACPs-ASSF). First, the prediction model is trained using raw data. Then, the augmented samples generated using the data augmentation technique are fed into the trained model to compute pseudo-labels and estimate the uncertainty of the model prediction. Finally, samples with low uncertainty, high confidence, and pseudo-labels consistent with the original labels are selected and incorporated into the training set to retrain the model. The evaluation results for the ACP240 and ACP740 datasets show that ACPs-ASSF achieved accuracy improvements of up to 5.41% and 5.68%, respectively, compared to the traditional data augmentation method.

Marine Cyanobacterial Peptides in Neuroblastoma: Search for Better Therapeutic Options

Neuroblastoma is the most prevalent extracranial solid tumor in pediatric patients, originating from sympathetic nervous system cells. Metastasis can be observed in approximately 70% of individuals after diagnosis, and the prognosis is poor. The current care methods used, which include surgical removal as well as radio and chemotherapy, are largely unsuccessful, with high mortality and relapse rates. Therefore, attempts have been made to incorporate natural compounds as new alternative treatments. Marine cyanobacteria are a key source of physiologically active metabolites, which have recently received attention owing to their anticancer potential. This review addresses cyanobacterial peptides' anticancer efficacy against neuroblastoma. Numerous prospective studies have been carried out with marine peptides for pharmaceutical development including in research for anticancer potential. Marine peptides possess several advantages over proteins or antibodies, including small size, simple manufacturing, cell membrane crossing capabilities, minimal drug-drug interactions, minimal changes in blood-brain barrier (BBB) integrity, selective targeting, chemical and biological diversities, and effects on liver and kidney functions. We discussed the significance of cyanobacterial peptides in generating cytotoxic effects and their potential to prevent cancer cell proliferation via apoptosis, the activation of caspases, cell cycle arrest, sodium channel blocking, autophagy, and anti-metastasis behavior.

Surface modified iron-oxide based engineered nanomaterials for hyperthermia therapy of cancer cells

Magnetic hyperthermia is emerging as a promising alternative to the currently available cancer treatment modalities. Superparamagnetic iron-oxide nanoparticles (SPIONs) are extensively studied functional nanomaterials for biomedical applications, owing to their tunable physio-chemical properties and magnetic properties. Out of various ferrite classes, spinel and inverse-spinel ferrites are widely used but are affected by particle size distribution, particle shape, particle-particle interaction, geometry, and crystallinity. Notably, their heating ability makes them suitable candidates for heat-mediated cancer cell ablation or hyperthermia therapy. Exposing SPIONs to an externally applied magnetic field of appropriate frequency and intensity causes them to release heat to ablate cancer cells. Majorly, three heating mechanisms are exhibited by magnetic nanomaterials: Nèel relaxation, Brownian relaxation, and hysteresis losses. In SPIONs, Nèel and Brownian relaxations dominate, whereas hysteric losses are negligible. These nanomaterials possess high magnetization values capable of generating heat to ablate cancer cells. Furthermore, surface functionalization of these materials imparts the ability to selectively target cancer cells and deliver cargo to the affected area sparing the normal body cells. The surface of nanoparticles can be functionalized with various physical, chemical, and biological coatings. Moreover, hyperthermia can be applied in combination with other cancer treatment modalities in order to enhance the efficiency of treatment.

A Practical Peptide Synthesis Workflow Using Amino-Li-Resin

Herein we report a practical approach for peptide synthesis using second-generation fibrous polyacrylamide resin (Li-resin, “Li” is coming from the name of its inventor, Yongfu Li). This resin with the corresponding handle was used for solid phase peptide synthesis (SPPS) using a fluorenylmethoxycarbonyl (Fmoc) approach. We reveal that the most appropriate mixing and filtration strategy when using amino-Li-resin in SPPS is via shaking and gravity filtration, instead of mechanical stirring and suction filtration used with other resins. The strategy was demonstrated with the SPPS of H-Tyr-Ile-Ile-Phe-Leu-NH₂, which contains the difficult sequence Ile-Ile. The peptide was obtained with excellent purity and yield. We are confident that this strategy will be rapidly implemented by other peptide laboratories.