The future of peptide-based drugs

A sandwich ELISA for the quantification of the anticancer peptide CIGB-552 in human plasma

CIGB-552 is a synthetic anticancer peptide that has been evaluated in vitro and in vivo in lung and colon cancer models. To optimize therapy in the clinic, pharmacokinetic studies are necessary. Previously, a sandwich-type enzyme-linked immunosorbent assay (ELISA) had been developed by our working group for the quantification of CIGB-552 in biological matrices. The objective of this work was to carry out the full validation of the ELISA to support its application in clinical trials. First, we obtained a polyclonal antibody specific for CIGB-552 and with purity greater than 95 %. The lower limit of quantification and the upper limit of quantification were 3125 ng/ml and 200 ng/ml, respectively. The method is exact and precise in the quantification of the peptide with relative error and coefficient of variation values less than 20 %. The ELISA is specific in the presence of CIGB-552 metabolites in the sample, and also presents robustness to certain protocol variations. In summary, the validated ELISA meets the requirements for its application in upcoming clinical trials as part of pharmacokinetic studies.

Cyclic natural product oligomers: diversity and (bio)synthesis of macrocycles

Cyclic compounds are generally preferred over linear compounds for functional studies due to their enhanced bioavailability, stability towards metabolic degradation, and selective receptor binding. This has led to a need for effective cyclization strategies for compound synthesis and hence increased interest in macrocyclization mediated by thioesterase (TE) domains, which naturally boost the chemical diversity and bioactivities of cyclic natural products. Many non-ribosomal peptide synthetase (NRPS) and polyketide synthase (PKS) derived natural products are assembled to form cyclodimeric compounds, with these molecules possessing diverse structures and biological activities. There is significant interest in identifying the biosynthetic pathways that produce such molecules given the challenge that cyclodimerization represents from a biosynthetic perspective. In the last decade, many groups have pursued the characterization of TE domains and have provided new insights into this biocatalytic machinery: however, the enzymes involved in formation of cyclodimeric compounds have proven far more elusive. In this review we focus on natural products that involve macrocyclization in their biosynthesis and chemical synthesis, with an emphasis on the function and biosynthetic investigation on the special family of TE domains responsible for forming cyclodimeric natural products. We also introduce additional macrocyclization catalysts, including butelase and the CT-mediated cyclization of peptides, alongside the formation of cyclodipeptides mediated by cyclodipeptide synthases (CDPS) and single-module NRPSs. Due to the interdisciplinary nature of biosynthetic research, we anticipate that this review will prove valuable to synthetic chemists, drug discovery groups, enzymologists, and the biosynthetic community in general, and inspire further efforts to identify and exploit these biocatalysts for the formation of novel bioactive molecules.

Optical Detection of Proteins Using Microgel-Stabilized Pickering Liquid Crystal-in-Water Emulsions

Herein, we present a novel liquid crystal (LC)-based sensing platform utilizing microgel-stabilized Pickering LC droplets dispersed in water for simple and label-free detection of proteins in an aqueous environment. This could be achieved by tailoring the surface of 4-cyano-4'-pentylbiphenyl (5CB) LC droplets dispersed in aqueous medium through the interfacial adsorption of poly(N-isopropylacrylamide) (PNIPAM) microgel particles, followed by the introduction of model surfactants, such as anionic sodium dodecyl sulfate and cationic dodecyltrimethylammonium bromide. These surfactant/microgel complex-coated LC droplets underwent a configurational transition from radial-to-bipolar under a polarized optical microscope, upon exposure to model proteins, namely bovine serum albumin and lysozyme. This transition stemmed from the interfacial adsorption of proteins, which was facilitated by their strong interaction with the preadsorbed microgel particles and surfactant molecules. The adsorption of proteins led to the disruption of the interfacial packing density of surfactant molecules, inducing a switch from homeotropic-to-planar surface anchoring of LCs within the droplets. In addition to providing remarkable Pickering stability to the LC droplets, the microgel coating significantly enhanced the sensitivity of the resulting emulsions to proteins. The dose-response behavior and detection limit of these modified LC droplets were strongly influenced by the microgel concentration, surfactant charge, pH of the medium, and the types of proteins. Notably, the droplets exhibited heightened responsiveness under conditions that favor attractive interactions between the proteins and interfacial surfactant molecules. Thus, this study opens avenues for engineering Pickering LC-based biosensors to discern biomolecular interactions, thereby facilitating various interfacial and sensing applications.

Enhancing leuprolide penetration through enterocytes via the ER-Golgi pathway using lipophilic complexation

Oral delivery of peptide drugs remains one of the most formidable challenges in the frontier of pharmaceutical research. Peptide drugs typically suffer from exceptionally low oral bioavailability, primarily attributed to rigorous enzymatic degradation within the gastrointestinal (GI) tract, limited ability to traverse the enterocyte barrier, and significant first-pass hepatic metabolism. Absorption of peptide drugs via the lymphatic route could potentially bypass intracellular lysosome degradation and hepatic first-pass metabolism. In this study, we present a strategy to enhance the lymphatic absorption of the model peptide leuprolide (LEU) by diverting its intracellular trafficking towards the endoplasmic-reticulum (ER)-Golgi pathway. Complexes were formed between LEU and lipophilic excipient and then formulated as an oral emulsion. We observed that the penetration of LEU in the emulsion across the Caco-2 cell monolayer model was diverted from the endosome-lysosome pathway, and LEU entered the bloodstream via the mesenteric lymph nodes (MLNs). The data obtained illustrates that the lipophilic LEU complexes could improve enterocyte permeability and bypass lysosomal degradation, and the change of absorption pathway may reduce hepatic first pass metabolism.

Enhancing Digestibility and Intestinal Peptide Release of Pleurotus eryngii Protein: An Enzymatic Approach

Pleurotus eryngii is a tasty and low-calorie mushroom containing abundant high-quality protein. This study aims to improve the digestibility of P. eryngii protein (PEP) and hence to facilitate its development as a healthy alternative protein. The extracted PEP was pretreated with 1000-5000 U of papain, neutral protease and alkaline protease. The Chyme collected from in vitro simulated gastrointestinal digestion was analyzed by fluorescence microscopy and protein particle analyzer, and the endpoint profiles of peptides and amino acids were determined by UHPLC-MS/MS and NanoLC-MS/MS. The particle size curve and fluorescence microscopy images jointly supported that protease hydrolysis improved decomposition and dispersion of PEP during digestion, particularly in the gastric phase. The impact on Zeta potential was minimal. Proteases effectively increased the abundance of amino acids after digestion, particularly L-isomer Lys and Arg Maximum release was achieved when pretreated with 5000 U of alkaline protease, reaching 7.54 times that of control. Pretreatments by proteases also notably increased digestive yields of 16,736-19,870 peptides, with the maximum reaching 1.70 times that of the control, which mainly consisted of small peptides composed of 7-15 amino acids with molecular weight below 800 Da. The findings indicated that protease hydrolysis, especially pretreatment with 5000 U of alkaline protease, effectively enhanced the digestibility of PEP, which shed light on providing enzymatic approaches for improving bioavailability and developing healthy fungal proteins.

Target-Specific De Novo Peptide Binder Design with DiffPepBuilder

Despite the exciting progress in target-specific de novo protein binder design, peptide binder design remains challenging due to the flexibility of peptide structures and the scarcity of protein-peptide complex structure data. In this study, we curated a large synthetic data set, referred to as PepPC-F, from the abundant protein-protein interface data and developed DiffPepBuilder, a de novo target-specific peptide binder generation method that utilizes an SE(3)-equivariant diffusion model trained on PepPC-F to codesign peptide sequences and structures. DiffPepBuilder also introduces disulfide bonds to stabilize the generated peptide structures. We tested DiffPepBuilder on 30 experimentally verified strong peptide binders with available protein-peptide complex structures. DiffPepBuilder was able to effectively recall the native structures and sequences of the peptide ligands and to generate novel peptide binders with improved binding free energy. We subsequently conducted de novo generation case studies on three targets. In both the regeneration test and case studies, DiffPepBuilder outperformed AfDesign and RFdiffusion coupled with ProteinMPNN, in terms of sequence and structure recall, interface quality, and structural diversity. Molecular dynamics simulations confirmed that the introduction of disulfide bonds enhanced the structural rigidity and binding performance of the generated peptides. As a general peptide binder de novo design tool, DiffPepBuilder can be used to design peptide binders for given protein targets with three-dimensional and binding site information.

Rh(III)-Catalyzed Double C-H Activation toward Peptide-Benzazepine Conjugates

We herein report the efficient synthesis of peptide-benzazepine conjugates from Lys-based peptides and acroleins via Rh(III)-catalyzed double C-H activation. This reaction features mild reaction conditions, broad scope, high atom and step economies, and excellent chemo- and site selectivity. The synthetic utility of this strategy is further demonstrated by scale-up experiments and product derivatizations, including diverse late-stage ligations based on the aldehyde moiety. The preliminary biological activity studies show that peptide-benzazepine conjugates have good antifungal activities toward crop and forest pathogenic fungi.

In silico bioprospecting of receptors for Oligoventin: An antimicrobial peptide isolated from spider eggs of Phoneutria nigriventer

BACKGROUND

Irresponsible and wholesale use of antimicrobial agents is the principal cause of the emergence of strains of resistant microorganisms to traditional drugs. Oligoventin is a neutral peptide isolated from spider eggs of Phoneutria nigriventer, with antimicrobial activity against Gram-positive, Gram-negative, and yeast organisms. However, the molecular target and pathways of antimicrobial activity are still unknown. Thus, the aim of the present study is to prospect receptors associated with the antimicrobial activity of Oligoventin using in silico tools.

METHODS

The PharmMapper and PDB server was used to prospect targets originating from microorganisms. Additionally, the PatchDock server was utilized to perform molecular docking between Oligoventin and the targets. Subsequently, the I-TASSER server was adopted to predict the ligand site. Finally, the docking results and predicted sites were compared with literature sites of each target.

RESULTS

Over 100 potential receptors for oligoventin have been identified. Among these, enoyl-ACP reductase (Idpdb1LXC) and thymidylate synthase ThyX (Idpdb 1O28) from bacteria and N-acetylglucosamine phosphate mutase (Idpdb 2DKD) showed superior interaction with oligoventin, exhibiting colocalization between docked residues and cofactor/active sites. These enzymes play a crucial role in fatty acid and DNA biosynthesis in prokaryotes and in cell wall synthesis in yeast.

CONCLUSION

Therefore, in silico results suggest that Oligoventin can impair fatty acid DNA, cell wall synthesis, thereby reducing microbial proliferation and causing microorganism death.

Designing microplastic-binding peptides with a variational quantum circuit-based hybrid quantum-classical approach

De novo peptide design exhibits great potential in materials engineering, particularly for the use of plastic-binding peptides to help remediate microplastic pollution. There are no known peptide binders for many plastics-a gap that can be filled with de novo design. Current computational methods for peptide design exhibit limitations in sampling and scaling that could be addressed with quantum computing. Hybrid quantum-classical methods can leverage complementary strengths of near-term quantum algorithms and classical techniques for complex tasks like peptide design. This work introduces a hybrid quantum-classical generative framework for designing plastic-binding peptides combining variational quantum circuits with a variational autoencoder network. We demonstrate the framework's effectiveness in generating peptide candidates, evaluate its efficiency for property-oriented design, and validate the candidates with molecular dynamics simulations. This quantum computing-based approach could accelerate the development of biomolecular tools for environmental and biomedical applications while advancing the study of biomolecular systems through quantum technologies.

Loading bioactive peptides within different nanocarriers to enhance their functionality and bioavailability; in vitro and in vivo studies

A hydrolyzed protein is a blend of peptides and amino acids which is the result of hydrolysis by enzymes, acids or alkalis. The Bioactive Peptides (BPs) show important biological roles including antioxidant, antimicrobial, anti-diabetic, anti-cancer, and anti-hypertensive effects, as well as positive effects on the immune, nervous, and digestive systems. Despite the benefits of BPs, challenges such as undesired organoleptic properties, solubility profile, chemical instability, and low bioavailability limit their use in functional food formulations and dietary supplements. Nanocarriers have emerged as a promising solution for overcoming these challenges by improving the stability, solubility, resistance to gastric digestion, and bioavailability, allowing for the targeted and controlled delivery, and reduction or masking of the undesirable flavor of BPs. This study reviews the recent scientific accomplishments concerning the loading of BPs into various nanocarriers including lipid, carbohydrate and protein based-nanocarriers. A special emphasis is given to their application in food formulations in accordance to the challenges associated with their use.

mHPpred: Accurate identification of peptide hormones using multi-view feature learning

Peptide hormones were first used in medicine in the early 20th century, with the pivotal event being the isolation and purification of insulin in 1921. These hormones are integral to a sophisticated system that emerged early in evolution to regulate growth, development, and homeostasis. They serve as targeted signaling molecules that transfer specific information between cells and organs, ensuring coordinated and precise physiological responses. While experimental methods for identifying peptide hormones present challenges such as low abundance, stability issues, and complexity, computational methods offer promising alternatives. Advances in machine learning and bioinformatics have facilitated the prediction of peptide hormones, further enhancing their therapeutic potential. In this study, we explored three different computational frameworks for peptide hormone identification and determined that the meta-approach was the most suitable. Firstly, we evaluated the discriminative power of 26 feature descriptors using a series of baseline models and identified seven feature descriptors with high predictive potential. Through a systematic approach, we then selected the top 20 performing baseline models and integrated their predicted probabilities to train a meta-model, leveraging the strengths of multiple prediction strategies. Our final light gradient boosting-based meta-model, mHPpred, significantly outperformed the existing method, HOPPred, on both benchmarking and independent datasets. Notably, mHPpred also demonstrated superior performance compared to the hybrid and integrative framework approaches employed in this study. This superiority demonstrates the effectiveness of our multi-view feature learning strategy in capturing discriminative features and providing a more accurate prediction model for peptide hormones. mHPpred is publicly accessible at: https://balalab-skku.org/mHPpred.

Lasso peptides realm: Insights and applications

Lasso peptides exhibit a range of bioactivities, including antiviral effects, inhibition of the glucagon receptor, blockade of the endothelin type B receptor, inhibition of myosin light chain kinase, and modulation of the atrial natriuretic factor, as well as notable antimicrobial properties. Intriguingly, lasso peptides exhibit remarkable proteolytic and thermal stability, addressing one of the key challenges that traditional peptides often face. The challenge in producing those valuable peptides remains the main hurdle in the way of producing larger quantities or even modifying them with more potent analogues. Genome mining and heterologous expression approaches have greatly facilitated the production of lasso peptides, moving beyond mere isolation techniques. This advancement not only allows for larger quantities but also enables the creation of additional analogues with improved stability and potency. This review aims to explore the unique bioactivities and stability of lasso peptides, along with recent advancements in genome mining and heterologous expression that address production challenges and open pathways for engineering potent analogues.

Proline Analogues in Drug Design: Current Trends and Future Prospects

Proline analogues are versatile chemical building blocks that enable modular construction of small-molecule drugs and pharmaceutical peptides. Over the past 15 years, the FDA has approved over 15 drugs containing proline analogues in their structures, five in the last three years alone (daridorexant, trofinetide, nirmatrelvir, rezafungin, danicopan). This perspective offers an analysis of the most common types of proline analogues currently trending in drug design. We focus on examples of fluoroprolines, α-methylproline, bicyclic proline analogues, and aminoprolines, while also highlighting proline analogues that remain underrepresented. We supplement our analysis with physicochemical information regarding the specific molecular properties of these moieties. Additionally, we discuss several intriguing cases where nonproline residues were replaced with proline analogues as a strategy to eliminate unwanted hydrogen bond donor sites. In conclusion, we present some suggestions for the future exploration of this promising class of molecular entities in drug discovery.

Marine Peptides: Potential Basic Structures for the Development of Hybrid Compounds as Multitarget Therapeutics for the Treatment of Multifactorial Diseases

Marine-derived peptides display potent antihypertensive, antioxidant, analgesic and antimicrobial biological effects. Some of them have also been found to have anticancer activity via various mechanisms differing from those of continental organisms. This diversity of properties-together with the peptides' efficacy, which has been confirmed in several in vitro and in vivo studies-make these compounds attractive as functional ingredients in pharmacy, especially in regard to multitarget drugs known as hybrids. Given the possibilities offered by chimeric structures, it is expected that a hybridization strategy based on a marine-derived compound could result in a long-awaited success in the development of new effective compounds to combat a range of complex diseases. However, despite the fact that the biological activity of such new hybrids may exceed that of their parent compounds, there is still an urgent need to carefully determine their potential off-targets and thus possible clinically important side effects. Given the above, the aim of this paper is to provide information on compounds of marine origin with peptide structures and to verify the occurrence and usage of hybrid compounds built from these structures. Furthermore, the authors believe that information presented here will serve to increase public awareness of the new opportunities arising from the combination of hybridization strategies with marine molecules with known structures and biological properties, thereby accelerating the development of effective drug candidates.

Recent Advances in Peptide Drug Discovery: Novel Strategies and Targeted Protein Degradation

Recent technological advancements, including computer-assisted drug discovery, gene-editing techniques, and high-throughput screening approaches, have greatly expanded the palette of methods for the discovery of peptides available to researchers. These emerging strategies, driven by recent advances in bioinformatics and multi-omics, have significantly improved the efficiency of peptide drug discovery when compared with traditional in vitro and in vivo methods, cutting costs and improving their reliability. An added benefit of peptide-based drugs is the ability to precisely target protein-protein interactions, which are normally a particularly challenging aspect of drug discovery. Another recent breakthrough in this field is targeted protein degradation through proteolysis-targeting chimeras. These revolutionary compounds represent a noteworthy advancement over traditional small-molecule inhibitors due to their unique mechanism of action, which allows for the degradation of specific proteins with unprecedented specificity. The inclusion of a peptide as a protein-of-interest-targeting moiety allows for improved versatility and the possibility of targeting otherwise undruggable proteins. In this review, we discuss various novel wet-lab and computational multi-omic methods for peptide drug discovery, provide an overview of therapeutic agents discovered through these cutting-edge techniques, and discuss the potential for the therapeutic delivery of peptide-based drugs.

Exploring the Potential of Biomimetic Peptides in Targeting Fibrillar and Filamentous Alpha-Synuclein-An In Silico and Experimental Approach to Parkinson's Disease

Alpha-synuclein (ASyn) is a protein that is known to play a critical role in Parkinson's disease (PD) due to its propensity for misfolding and aggregation. Furthermore, this process leads to oxidative stress and the formation of free radicals that cause neuronal damage. In this study, we have utilized a biomimetic approach to design new peptides derived from marine natural resources. The peptides were designed using a peptide scrambling approach where antioxidant moieties were combined with fibrillary inhibition motifs in order to design peptides that would have a dual targeting effect on ASyn misfolding. Of the 20 designed peptides, 12 were selected for examining binding interactions through molecular docking and molecular dynamics approaches, which revealed that the peptides were binding to the pre-NAC and NAC (non-amyloid component) domain residues such as Tyr39, Asn65, Gly86, and Ala85, among others. Because ASyn filaments derived from Lewy body dementia (LBD) have a different secondary structure compared to pathogenic ASyn fibrils, both forms were tested computationally. Five of those peptides were utilized for laboratory validation based on those results. The binding interactions with fibrils were confirmed using surface plasmon resonance studies, where EQALMPWIWYWKDPNGS, PYYYWKDPNGS, and PYYYWKELAQM showed higher binding. Secondary structural analyses revealed their ability to induce conformational changes in ASyn fibrils. Additionally, PYYYWKDPNGS and PYYYWKELAQM also demonstrated antioxidant properties. This study provides insight into the binding interactions of varying forms of ASyn implicated in PD. The peptides may be further investigated for mitigating fibrillation at the cellular level and may have the potential to target ASyn.

Pharmacological and Biological Targeting of FGFR1 in Cancer

FGFR1 is a key member of the fibroblast growth factor receptor family, mediating critical signaling pathways such as RAS-MAPK and PI3K-AKT. which are integral to regulating essential cellular processes, including proliferation, differentiation, and survival. Alterations in FGFR1 can lead to constitutive activation of signaling pathways that drive oncogenesis by promoting uncontrolled cell division, inhibiting apoptosis, and enhancing the metastatic potential of cancer cells. This article reviews the activation mechanisms and signaling pathways of FGFR1 and provides a detailed exposition of the types of FGFR1 aberration. Furthermore, we have compiled a comprehensive overview of current therapies targeting FGFR1 aberration in cancer, aiming to offer new perspectives for future cancer treatments by focusing on drugs that address specific FGFR1 alterations.

Phage display screening in breast cancer: From peptide discovery to clinical applications

Breast cancer is known as the most common type of cancer found in women and a leading cause of cancer death in women, with the global incidence only increasing. Breast cancer in Malaysia is also unfortunately the most prevalent in Malaysian women. Many treatment options are available for breast cancer, but there is increasing resistance developed against treatment and increased recurrence risk, emphasizing the need for new treatment options. This review will focus on the applications of phage display screening in the context of breast cancer. Phage display screening can facilitate the drug discovery process by providing rapid screening and isolation of peptides that bind to targets of interest with high specificity. Peptides derived from phage display target various types of proteins involved in breast cancer, including HER2, C5AR1, p53 and PRDM14, either for therapeutic or diagnostic purposes. Different approaches were employed as well to produce potential peptides using radiolabelling and conjugation techniques. Promising results were reported for in vitro and in vivo studies utilizing peptides derived from phage display screening. Further optimization of the protocols and factors to consider are required to mitigate the challenges involved with phage display screening of peptides for breast cancer diagnosis and treatment.

Thermo-amplifier circuit in probiotic E. coli for stringently temperature-controlled release of a novel antibiotic

Peptide drugs have seen rapid advancement in biopharmaceutical development, with over 80 candidates approved globally. Despite their therapeutic potential, the clinical translation of peptide drugs is hampered by challenges in production yields and stability. Engineered bacterial therapeutics is a unique approach being explored to overcome these issues by using bacteria to produce and deliver therapeutic compounds at the body site of use. A key advantage of this technology is the possibility to control drug delivery within the body in real time using genetic switches. However, the performance of such genetic switches suffers when used to control drugs that require post-translational modifications or are toxic to the host. In this study, these challenges were experienced when attempting to establish a thermal switch for the production of a ribosomally synthesized and post-translationally modified peptide antibiotic, darobactin, in probiotic E. coli. These challenges were overcome by developing a thermo-amplifier circuit that combined the thermal switch with a T7 RNA Polymerase. Due to the orthogonality of the Polymerase, this strategy overcame limitations imposed by the host transcriptional machinery. This circuit enabled production of pathogen-inhibitory levels of darobactin at 40 °C while maintaining leakiness below the detection limit at 37 °C. Furthermore, the thermo-amplifier circuit sustained gene expression beyond the thermal induction duration such that with only 2 h of induction, the bacteria were able to produce pathogen-inhibitory levels of darobactin. This performance was maintained even in physiologically relevant simulated conditions of the intestines that include bile salts and low nutrient levels.

DRAMP 4.0: an open-access data repository dedicated to the clinical translation of antimicrobial peptides

Antimicrobial peptides (AMPs) are potential candidates for treating multidrug-resistant bacterial infections, yet only a small number of them have progressed into clinical trials. The main challenges include the poor stability and hemolytic/cytotoxic properties of AMPs. Considering this, in the update of the Data Repository of Antimicrobial Peptides (DRAMP), a new annotation on serum and protease stability is added, and special efforts were made to update the hemolytic/cytotoxic information of AMPs. The DRAMP 4.0 currently holds 30 260 entries (8 001 newly added), consisting of 11 612 general entries, 17 886 patent entries, 96 clinical entries, 377 specific entries, 110 entries with stability data, and 179 expanded entries. A total of 2891 entries possess experimentally determined hemolytic activity information, while 2674 entries contain cytotoxicity data by experimental validation. The update also covers new annotations, statistics, categories, functions, and download links. DRAMP is available online at http://dramp.cpu-bioinfor.org/.

Comparison of Protocols to Test Peptide Stability in Blood Plasma and Cell Culture Supernatants

Due to their high specificity, peptides are promising candidates in drug development, but fast degradation often limits their biological activity. Thus, a short half-life is one of the major challenges in the development of new peptide therapeutics. Moreover, the enzymatic cleavage of peptides can be a reason for misleading results in biological assays. Peptide stability assays typically consist of incubation, precipitation, and detection steps. However, the current methods differ greatly regarding these three steps, thus limiting the compatibility. Here, we systematically evaluate different parameters of peptide stability assays. First, we quantified and compared the analyte loss during the precipitation of plasma proteins. Especially, broadly used precipitation by strong acids was found to be unsuitable, while mixtures of organic solvents preserved more peptides for further analysis. Next, the stability of four fluorescently labeled model peptides was analyzed in blood plasma and two different cell culture supernatants. Strong variation in the degradation dynamics and patterns was found. Finally, we evaluated the role of fluorescent labeling on peptide stability and compared results to peptides with isotopic labels, underlining the individual advantages of both methods. Altogether, the data provide important parameters for analyzing and comparing the peptide stability.

Engineering peptide drug therapeutics through chemical conjugation and implication in clinics

The development of peptide drugs has made tremendous progress in the past few decades because of the advancements in modification chemistry and analytical technologies. The novel-designed peptide drugs have been modified through various biochemical methods with improved diagnostic, therapeutic, and drug-delivery strategies. Researchers found it a helping hand to overcome the inherent limitations of peptides and bring continued advancements in their applications. Furthermore, the emergence of peptide-drug conjugates (PDCs)-utilizes target-oriented peptide moieties as a vehicle for cytotoxic payloads via conjugation with cleavable chemical agents, resulting in the key foundation of the new era of targeted peptide drugs. This review summarizes the various classifications of peptide drugs, suitable chemical modification strategies to improve the ADME (adsorption, distribution, metabolism, and excretion) features of peptide drugs, and recent (2015-early 2024) progress/achievements in peptide-based drug delivery systems as well as their fruitful implication in preclinical and clinical studies. Furthermore, we also summarized the brief description of other types of PDCs, including peptide-MOF conjugates and peptide-UCNP conjugates. The principal aim is to provide scattered and diversified knowledge in one place and to help researchers understand the pinching knots in the science of PDC development and progress toward a bright future of novel peptide drugs.

The role of CART peptide in learning and memory: A potential therapeutic target in memory-related disorders

Cocaine and amphetamine-regulated transcript (CART) mRNA and peptide are vastly expressed in both cortical and subcortical brain areas and are involved in critical cognitive functions. CART peptide (CARTp), described in reward-related brain structures, regulates drug-induced learning and memory, and its role appears specific to psychostimulants. However, many other drugs of abuse, such as alcohol, opiates, nicotine, and caffeine, have been shown to alter the expression levels of CART mRNA and peptides in brain structures directly or indirectly associated with learning and memory processes. However, the number of studies demonstrating the contribution of CARTp in learning and memory is still minimal. Notably, the exact cellular and molecular mechanisms underlying CARTp effects are still unknown. The discoveries that CARTp effects are mediated through a putative G-protein coupled receptor and activation of cellular signaling cascades via NMDA receptor-coupled ERK have enhanced our knowledge about the action of this neuropeptide and allowed us to comprehend better CARTp exact cellular/molecular mechanisms that could mediate drug-induced changes in learning and memory functions. Unfortunately, these efforts have been impeded by the lack of suitable and specific CARTp receptor antagonists. In this review, following a short introduction about CARTp, we report on current knowledge about CART's roles in learning and memory processes and its recently described role in memory-related neurological disorders. We will also discuss the importance of further investigating how CARTp interacts with its receptor(s) and other neurotransmitter systems to influence learning and memory functions. This topic is sure to intrigue and motivate further exploration in the field of neuroscience.

Quest for New Generation Biocompatible Materials: Tailoring β-Peptide Structure and Interactions via Synergy of Experiments and Modelling

Peptide-based self-assembly has been used to produce a wide range of nanostructures. While most of these systems involve self-assembly of α-peptides, more recently β-peptides have also been shown to undergo supramolecular self-assembly, and have been used to produce materials for applications in tissue engineering, cell culture and drug delivery. In order to engineer new materials with specific structure and function, theoretical molecular modelling can provide significant insights into the collective balance of non-covalent interactions that drive the self-assembly and determine the structure of the resultant supramolecular materials under different conditions. However, this approach has only recently become feasible for peptide-based self-assembled nanomaterials, particularly those that incorporate non α-amino acids. This perspective provides an overview of the challenges associated with computational modelling of the self-assembly of β-peptides and the recent success using a combination of experimental and computational techniques to provide insights into the self-assembly mechanisms and fully atomistic models of these new biocompatible materials.

Proteomimetic polymer blocks mitochondrial damage, rescues Huntington's neurons, and slows onset of neuropathology in vivo

Recently, it has been shown that blocking the binding of valosin-containing protein (VCP) to mutant huntingtin (mtHtt) can prevent neuronal mitochondrial autophagy in Huntington's disease (HD) models. Herein, we describe the development and efficacy of a protein-like polymer (PLP) for inhibiting this interaction in cellular and in vivo models of HD. PLPs exhibit bioactivity in HD mouse striatal cells by successfully inhibiting mitochondrial destruction. PLP is notably resilient to in vitro enzyme, serum, and liver microsome stability assays, which render analogous control oligopeptides ineffective. PLP demonstrates a 2000-fold increase in circulation half-life compared to peptides, exhibiting an elimination half-life of 152 hours. In vivo efficacy studies in HD transgenic mice (R6/2) confirm the superior bioactivity of PLP compared to free peptide through behavioral and neuropathological analyses. PLP functions by preventing pathologic VCP/mtHtt binding in HD animal models; exhibits enhanced efficacy over the parent, free peptide; and implicates the PLP as a platform with potential for translational central nervous system therapeutics.

Stapled peptides as potential therapeutics for diabetes and other metabolic diseases

The field of peptide drug research has experienced notable progress, with stapled peptides featuring stabilized α-helical conformation, emerging as a promising field. These peptides offer enhanced stability, cellular permeability, and binding affinity and exhibit potential in the treatment of diabetes and metabolic disorders. Stapled peptides, through the disruption of protein-protein interactions, present varied functionalities encompassing agonism, antagonism, and dual-agonism. This comprehensive review offers insight into the technology of peptide stapling and targeting of crucial molecular pathways associated with glucose metabolism, insulin secretion, and food intake. Additionally, we address the challenges in developing stapled peptides, including concerns pertaining to structural stability, peptide helicity, isomer mixture, and potential side effects.

A non-bactericidal cathelicidin with antioxidant properties ameliorates UVB-induced mouse skin photoaging via intracellular ROS scavenging and Keap1/Nrf2 pathway activation

Cathelicidins, a category of critical host defense molecules in vertebrates, have been extensively studied for their bactericidal functions, but little is known about their non-bactericidal properties. Herein, a novel cathelicidin peptide (Atonp2) was identified from the plateau frog Nanorana ventripunctata. It did not exhibit bactericidal activity but showed significant therapeutic effects in chronic UVB radiation-induced mouse skin photoaging through inhibiting thickening, pyroptosis and inflammation in the epidermis, while inhibiting cellular senescence, collagen fibre breakage and type Ⅰ collagen reduction in the dermis. Further studies indicated that Atonp2 effectively scavenged UVB-induced intracellular ROS via tyrosines at positions 9 and 10, while activating the Keap1/Nrf2 pathway to protect epidermal keratinocytes against UVB radiation, which in turn indirectly reversed the senescence and collagen degradation of dermal fibroblasts, thereby ameliorating UVB-induced skin photoaging. As such, this study identified a non-bactericidal cathelicidin peptide with potent antioxidant functions, highlighting its potential to treat and prevent skin photoaging.

Therapeutic peptides in the treatment of digestive inflammation: Current advances and future prospects

Digestive inflammation is a widespread global issue that significantly impacts quality of life. Recent advances have highlighted the unique potential of therapeutic peptides for treating this condition, owing to their specific bioactivity and high specificity. By specifically targeting key proteins involved in the pathological process and modulating biomolecular functions, therapeutic peptides offer a novel and promising approach to managing digestive inflammation. This review explores the development history, pharmacological characteristics, clinical applications, and regulatory mechanisms of therapeutic peptides in treating digestive inflammation. Additionally, the review addresses pharmacokinetics and quality control methods of therapeutic peptides, focusing on challenges such as low bioavailability, poor stability, and difficulties in delivery. The role of modern biotechnologies and nanotechnologies in overcoming these challenges is also examined. Finally, future directions for therapeutic peptides and their potential impact on clinical applications are discussed, with emphasis placed on their significant role in advancing medical and therapeutic practices.

Two peptides LLRLTDL and GYALPCDCL inhibit foam cell formation through activating PPAR-γ/LXR-α signaling pathway in oxLDL-treated RAW264.7 macrophages

Foam cell formation plays a pivotal role in atherosclerosis-associated cardiovascular diseases. Bioactive peptides generated from marine sources have been found to provide multifunctional health advantages. In the present study, we investigated the anti-atherosclerotic effects of LLRLTDL (Bu1) and GYALPCDCL (Bu2) peptides, isolated from ark shell protein hydrolysates by assessing their inhibitory effect on oxidized LDL (oxLDL)-induced foam cell formation. The two peptides showed a promising anti-atherosclerotic effect by inhibiting foam cell formation, which was evidenced by inhibiting lipid accumulation in oxLDL-treated RAW264.7 macrophages and oxLDL-treated primary human aortic smooth muscle cells (HASMC). Two peptides effectively reduced total cholesterol, free cholesterol, cholesterol ester, and triglyceride levels by upregulating cholesterol efflux and downregulating cholesterol influx. Expression of cholesterol influx-related proteins such as SR-A1 and CD36 were reduced, whereas cholesterol efflux-related proteins such as ATP-binding cassette transporter ABCA-1 and ABCG-1 were highly expressed. In addition, Bu1 and Bu2 peptides increased PPAR-γ and LXR-α expression. However, PPAR-γ siRNA transfection reversed the foam cell formation inhibitory activity of Bu1 and Bu2 peptides. Furthermore, the synergistic effect of Bu1 and Bu2 peptides on foam cell formation inhibition was observed with PPAR-γ agonist thiazolidinediones, indicating that PPAR-γ signaling pathway plays a key role in foam cell formation of macrophages. Beyond their impact on foam cell formation, Bu1 and Bu2 peptides demonstrated anti-inflammatory potential by inhibiting the generation of pro-inflammatory cytokines and nitric oxide and NF-κB nuclear activation. Taken together, these results suggest that Bu1 and Bu2 peptides may be useful for atherosclerosis and associated anti-inflammatory therapies.

DeepAIP: Deep learning for anti-inflammatory peptide prediction using pre-trained protein language model features based on contextual self-attention network

Non-steroidal anti-inflammatory drugs (NSAIDs), glucocorticoids, and other immunosuppressants are commonly used medications for treating inflammation. However, these drugs often come with numerous side effects. Therefore, finding more effective methods for inflammation treatment has become more necessary. The study of anti-inflammatory peptides can effectively address these issues. In this work, we propose a contextual self-attention deep learning model, coupled with features extracted from a pre-trained protein language model, to predict Anti-inflammatory Peptides (AIP). The contextual self-attention module can effectively enhance and learn the features extracted from the pre-trained protein language model, resulting in high accuracy to predict AIP. Additionally, we compared the performance of features extracted from popular pre-trained protein language models available in the market. Finally, Prot-T5 features demonstrated the best comprehensive performance as the input for our deep learning model named DeepAIP. Compared with existing methods on benchmark test dataset, DeepAIP gets higher Matthews Correlation Coefficient and Accuracy score than the second-best method by 16.35 % and 6.91 %, respectively. Performance comparison analysis was conducted using a dataset of 17 novel anti-inflammatory peptide sequences. DeepAIP demonstrates outstanding accuracy, correctly identifying all 17 peptide types as AIP and predicting values closer to the true ones. Data and code are available at https://github.com/YangQingGuoCCZU/DeepAIP.

Neurotrophin peptidomimetics for the treatment of neurodegenerative diseases

Neurotrophins, such as nerve growth factor and brain-derived neurotrophic factor, play an essential role in the survival of neurons. However, incorporating better features can increase their therapeutic efficacy in neurodegenerative diseases (NDs). Peptidomimetics, which mimic these neurotrophins, show potential for treating NDs. This study emphasizes the use of peptidomimetics from neurotrophins for treating NDs and their benefits. By improving bioavailability and stability, these molecules can completely transform the therapy for NDs. This in-depth review guides researchers and pharmaceutical developers, providing insight into the changing field of neurodegenerative medicine.

Research progress on the protection and mechanism of active peptides in Alzheimer's disease and Parkinson's disease

Neurodegenerative diseases are the main causes of death and morbidity among elderly people worldwide. From the pathological point of view, oxidative stress, neuroinflammation, mitochondrial damage and apoptosis are the causes of neuronal diseases, and play a harmful role in the process of neuronal cell death and neurodegeneration. The most common neurodegenerative diseases are Alzheimer's disease(AD) and Parkinson's disease(PD), and there is no effective treatment. The physiological role of active peptides in the human body is significant. Modern medical research has found that animal and plant peptides, natural peptides in human body, can act on the central nervous system, and their active components can improve learning and memory ability, and play the roles of antioxidation, anti-inflammation, anti-apoptosis and maintaining the structure and function of mitochondria. This review reviews the reports on neurodegenerative diseases such as AD and PD by active peptides from animals and plants and natural peptides from the human body, and summarizes the neuroprotective mechanism of peptides. A theoretical basis for further research and development of active peptides was provided by examining the research and application of peptides, which provided a theoretical basis for further research and development.

Protocol for Designing De Novo Noncanonical Peptide Binders in OSPREY

D-peptides, the mirror image of canonical L-peptides, offer numerous biological advantages that make them effective therapeutics. This article details how to use DexDesign, the newest OSPREY-based algorithm, for designing these D-peptides de novo. OSPREY physics-based models precisely mimic energy-equivariant reflection operations, enabling the generation of D-peptide scaffolds from L-peptide templates. Due to the scarcity of D-peptide:L-protein structural data, DexDesign calls a geometric hashing algorithm, Method of Accelerated Search for Tertiary Ensemble Representatives, as a subroutine to produce a synthetic structural dataset. DexDesign enables mixed-chirality designs with a new user interface and also reduces the conformation and sequence search space using three new design techniques: Minimum Flexible Set, Inverse Alanine Scanning, and K*-based Mutational Scanning.

Transformation of peptides to small molecules in medicinal chemistry: Challenges and opportunities

Peptides are native binders involved in numerous physiological life procedures, such as cellular signaling, and serve as ready-made regulators of biochemical processes. Meanwhile, small molecules compose many drugs owing to their outstanding advantages of physiochemical properties and synthetic convenience. A novel field of research is converting peptides into small molecules, providing a convenient portable solution for drug design or peptidomic research. Endowing properties of peptides onto small molecules can evolutionarily combine the advantages of both moieties and improve the biological druggability of molecules. Herein, we present eight representative recent cases in this conversion and elaborate on the transformation process of each case. We discuss the innovative technological methods and research approaches involved, and analyze the applicability conditions of the approaches and methods in each case, guiding further modifications of peptides to small molecules. Finally, based on the aforementioned cases, we summarize a general procedure for peptide-to-small molecule modifications, listing the technological methods available for each transformation step and providing our insights on the applicable scenarios for these methods. This review aims to present the progress of peptide-to-small molecule modifications and propose our thoughts and perspectives for future research in this field.

A stability-indicating method development and validation for the determination of related substances in novel synthetic decapeptide by HPLC

In the present scenario, peptide is an emerging field of research having vast therapeutic applications. Diverse impurities may rise from various stages of the synthesis process and storage of the peptides. Because these contaminants may have an impact on the therapeutic safety and effectiveness of peptides in their approaching applications, they must be identified and carefully monitored. Considering the pharmaceutical importance of the extent of peptides, we were motivated to synthesize a decapeptide and establish a novel gradient reversed-phase high-performance liquid chromatography (RP-HPLC) method for its analysis along with efficient separation of its six related impurities. Different buffers, organic modifiers, and columns were used in the tests for good separation of these impurities. To establish a stability-indicating method, a stress study was also conducted. The International Conference on Harmonization (ICH) guidelines have been followed for validation of the developed analytical method. The validated method revealed sufficient accuracy, specificity, linearity, robustness, precision, and high sensitivity for its intended use. The proposed method could be appropriate for routine analysis and stability assessment of the decapeptide, which might be useful for further scientific investigation.

Research progress on the therapeutic effects of nanoparticles loaded with drugs against atherosclerosis

Presently, there are many drugs for the treatment of atherosclerosis (AS), among which lipid-lowering, anti-inflammatory, and antiproliferative drugs have been the most studied. These drugs have been shown to have inhibitory effects on the development of AS. Nanoparticles are suitable for AS treatment research due to their fine-tunable and modifiable properties. Compared with drug monotherapy, experimental results have proven that the effects of nanoparticle-encapsulated drugs are significantly enhanced. In addition to nanoparticles containing a single drug, there have been many studies on collaborative drug treatment, collaborative physical treatment (ultrasound, near-infrared lasers, and external magnetic field), and the integration of diagnosis and treatment. This review provides an introduction to the therapeutic effects of nanoparticles loaded with drugs to treat AS and summarizes their advantages, including increased targeting ability, sustained drug release, improved bioavailability, reduced toxicity, and inhibition of plaque and vascular stenosis.

Development of Novel Indole-Based Covalent Inhibitors of TEAD as Potential Antiliver Cancer Agents

Abnormal activation of the YAP transcriptional signaling pathway drives proliferation in many hepatocellular carcinoma (HCC) and hepatoblastoma (HB) cases. Current treatment options often face resistance and toxicity, highlighting the need for alternative therapies. This article reports the discovery of a hit compound C-3 from docking-based virtual screening targeting TEAD lipid binding pocket, which inhibited TEAD-mediated transcription. Optimization led to the identification of a potent and covalent inhibitor CV-4-26 that exhibited great antitumor activity in HCC and HB cell lines in vitro, xenografted human HCC, and murine HB in vivo. These outcomes signify the potential of a highly promising therapeutic candidate for addressing a subset of HCC and HB cancers. In the cases of current treatment challenges due to high upregulation of YAP-TEAD activity, these findings offer a targeted alternative for more effective interventions against liver cancer.

ToxGIN: an In silico prediction model for peptide toxicity via graph isomorphism networks integrating peptide sequence and structure information

Peptide drugs have demonstrated enormous potential in treating a variety of diseases, yet toxicity prediction remains a significant challenge in drug development. Existing models for prediction of peptide toxicity largely rely on sequence information and often neglect the three-dimensional (3D) structures of peptides. This study introduced a novel model for short peptide toxicity prediction, named ToxGIN. The model utilizes Graph Isomorphism Network (GIN), integrating the underlying amino acid sequence composition and the 3D structures of peptides. ToxGIN comprises three primary modules: (i) Sequence processing module, converting peptide 3D structures and sequences into information of nodes and edges; (ii) Feature extraction module, utilizing GIN to learn discriminative features from nodes and edges; (iii) Classification module, employing a fully connected classifier for toxicity prediction. ToxGIN performed well on the independent test set with F1 score = 0.83, AUROC = 0.91, and Matthews correlation coefficient = 0.68, better than existing models for prediction of peptide toxicity. These results validated the effectiveness of integrating 3D structural information with sequence data using GIN for peptide toxicity prediction. The proposed ToxGIN and data can be freely accessible at https://github.com/cihebiyql/ToxGIN.

Investigation of therapeutic potential of the Il24-p20 fusion protein against breast cancer: an in-silico approach

Targeted delivery of therapeutic anticancer chimeric molecules enhances drug efficacy. Numerous studies have focused on developing novel treatments by employing cytokines, particularly interleukins, to inhibit the growth of cancer cells. In the present study, we fused interleukin 24 with the tumor-targeting peptide P20 through a rigid linker to selectively target cancer cells. The secondary structure, tertiary structure, and physicochemical characteristics of the constructed chimeric IL-24-P20 protein were predicted by using bioinformatics tools. In-silico analysis revealed that the fusion construct has a basic nature with 175 amino acids and a molecular weight of 20 kDa. By using the Rampage and ERRAT2 servers, the validity and quality of the fusion protein were evaluated. The results indicated that 93% of the chimeric proteins contained 90.1% of the residues in the favoured region, resulting in a reliable structure. Finally, docking and simulation studies were conducted via ClusPro and Desmond Schrödinger, respectively. Our results indicate that the constructed fusion protein exhibits excellent quality, interaction capabilities, validity, and stability. These findings suggest that the fusion protein is a promising candidate for targeted cancer therapy.

Recent Progress on Transition Metal Catalyzed Macrocyclizations Based on C-H Bond Activation at Heterocyclic Scaffolds

Macrocycles are essential in protein-protein interactions and the preferential intake of bioactive scaffolds. Macrocycles are commonly synthesized by late-stage macrolactonizations, macrolactamizations, transition metal-catalyzed ring-closing metathesis, S-S bond-forming reactions, and copper-catalyzed alkyne-azide cycloaddition. Recently, transition metal-catalyzed C-H activation strategies have gained significant interest among chemists to synthesize macrocycles. This article provides a comprehensive overview of the transition metal-catalyzed macrocyclization via C-H bond functionalization of heterocycle-containing peptides, annulations, and heterocycle-ring construction through direct C-H bond functionalization. In the first part, palladium salt catalyzed coupling with indolyl C(sp3)-H and C(sp2)-H bonds for macrocyclization is reported. The second part summarizes rhodium-catalyzed macrocyclizations via site-selective C-H bond functionalization. Earth-abundant, less toxic 3d metal salt Mn-catalyzed cyclizations are reported in the latter part. This summary is expected to spark interest in emerging methods of macrocycle production among organic synthesis and chemical biology practitioners, helping to develop the discipline. We hope that this mini-review will also inspire synthetic chemists to explore new and broadly applicable C-C bond-forming strategies for macrocyclization via intramolecular C-H activation.

Chemoenzymatic Synthesis of DNP-Functionalized FGFR1-Binding Peptides as Novel Peptidomimetic Immunotherapeutics for Treating Lung Cancer

Receptor-binding peptides are promising candidates for tumor target therapy. However, the inability to occupy "hot spots" on the PPI interface and rapid metabolic instability are significant limitations to their clinical application. We investigated a new strategy in which an FGFR1-binding peptide (Pep1) was site-specifically functionalized with the dinitrophenyl (DNP) hapten at the C-terminus. The resulting Pep1-DNP conjugates retained FGFR1 binding affinity and exhibited a similar potency in inhibiting FGF2-dependent cell proliferation, comparable to that of native Pep1 in vitro. In addition, three conjugates could recruit anti-DNP antibodies onto the surface of cancer cells, thereby mediating the CDC efficacy. In vivo pharmacokinetic studies and antitumor studies demonstrated that optimal conjugate 9 exhibited significantly prolonged half-lives and improved antitumor efficacy without prominent toxicity compared to those of native Pep1. This is a general and cost-effective approach for generating peptidomimetic immunotherapeutics with multiple antitumor mechanisms that may have broad applications in cancer therapy.

A novel class of potent antiangiogenic and antioxidant pyrazoles: synthesis, bioactivity, docking and ADMET studies

Aim: Angiogenesis is the hallmark of cancer progression driven by VEGF/VEGFR-2 signalling pathway, inhibition of which could be a solution to tackle the progression of tumour cells and thus arresting their growth.Materials & methods: A novel class of pyrazoles was synthesized using arginine and dibromo ketones. Antiangiogenic activity was performed by in vivo yolk sac method. Antioxidant activity was evaluated by hydroxyl and superoxide radical scavenging assays. Docking studies were performed to determine the pyrazoles' binding potential with VEGFR-2 receptor and VEGF tyrosine kinase. ADMET properties were calculated using SwissADME and admetSAR for drug-likeness.Results: Compounds 5a-e showed significant antiangiogenic effects. Compound 5f exhibited effective hydroxyl and superoxide radical scavenging activities. Docking results confirmed the potential binding efficiency with VEGFR-2 receptor over VEGF tyrosine kinase, thus, functioning as competitive-inhibitors. ADMET studies revealed that the compounds possess favourable drug-like qualities.Conclusion: This study presents a novel class of pyrazoles as promising antioxidant and antiangiogenic agents with favourable drug-likeness properties.

Structure-Aided Computational Design of Triazole-Based Targeted Covalent Inhibitors of Cruzipain

Cruzipain (CZP), the major cysteine protease present in T. cruzi, the ethiological agent of Chagas disease, has attracted particular attention as a therapeutic target for the development of targeted covalent inhibitors (TCI). The vast chemical space associated with the enormous molecular diversity feasible to explore by means of modern synthetic approaches allows the design of CZP inhibitors capable of exhibiting not only an efficient enzyme inhibition but also an adequate translation to anti-T. cruzi activity. In this work, a computer-aided design strategy was developed to combinatorially construct and screen large libraries of 1,4-disubstituted 1,2,3-triazole analogues, further identifying a selected set of candidates for advancement towards synthetic and biological activity evaluation stages. In this way, a virtual molecular library comprising more than 75 thousand diverse and synthetically feasible analogues was studied by means of molecular docking and molecular dynamic simulations in the search of potential TCI of CZP, guiding the synthetic efforts towards a subset of 48 candidates. These were synthesized by applying a Cu(I)-catalyzed azide-alkyne cycloaddition (CuAAC) centered synthetic scheme, resulting in moderate to good yields and leading to the identification of 12 hits selectively inhibiting CZP activity with IC50 in the low micromolar range. Furthermore, four triazole derivatives showed good anti-T. cruzi inhibition when studied at 50 μM; and Ald-6 excelled for its high antitrypanocidal activity and low cytotoxicity, exhibiting complete in vitro biological activity translation from CZP to T. cruzi. Overall, not only Ald-6 merits further advancement to preclinical in vivo studies, but these findings also shed light on a valuable chemical space where molecular diversity might be explored in the search for efficient triazole-based antichagasic agents.

Predicting the Long-Term Stability of Biologics with Short-Term Data

Understanding the long-term stability of biologics is crucial to ensure safe, effective, and cost-efficient life-saving therapeutics. Current industry and regulatory practices require arduous real-time data collection over three years; thus, reducing this bottleneck while still ensuring product quality would enhance the speed of medicine to patients. We developed a parallel-pathway kinetic model, combined with Monte Carlo simulations for prediction intervals, to predict the long-term (2+ years) stability of biotherapeutic critical quality attributes (aggregates, fragments, charge variants, purity, and potency) with short-term (3-6 months) data from intended, accelerated, and stressed temperatures. We rigorously validated the model with 18 biotherapeutic drug products, composed of IgG1 and IgG4 monoclonal antibodies, antibody-drug conjugates, dual protein coformulations, and a fusion protein, including high concentration (≥100 mg/mL) formulations, in liquid and lyophilized presentations. For each drug product, we accurately predicted the long-term trends of multiple quality attributes using just 6 months of data. Further, we demonstrated superior stability prediction via our methods compared with industry-standard linear regression methods. The robust and repeatable results of this work across an unprecedented suite of 18 biotherapeutic compounds suggest that kinetic models with Monte Carlo simulation can predict the long-term stability of biologics with short-term data.

Counteracting TGM2 by a Fibroin peptide ameliorated Adriamycin-induced nephropathy via regulation of lipid metabolism through PANX1-PPAR α/PANK1 pathway

Peptide drug discovery for the treatment of chronic kidney disease (CKD) has attracted much attention in recent years due to the urge to find novel drugs and mechanisms to delay the progression of the disease. In this study, we identified a novel short peptide (named YR-7, primary sequence 'YEVEDYR') from the natural Fibroin protein, and demonstrated that it significantly alleviated pathological renal changes in ADR-induced nephropathy. PANX1 was identified as the most notably upregulated component by RNA-sequencing. Further analysis showed that YR-7 alleviated the accumulation of lipid droplets via regulation of the lipid metabolism-related proteins PPAR α and PANK1. Using chemical proteomics, fluorescence polarization, microscale thermophoresis, surface plasmon resonance, and molecular docking, YR-7 was proven to directly bind to β-barrel domains of TGM2 protein to inhibit lipid accumulation. TGM2 knockdown in vivo increased the protein levels of PPAR α and PANK1 while decreased the levels of fibrotic-related proteins to alleviate nephropathy. In vitro, overexpression TGM2 reversed the protective effects of YR-7. Co-immunoprecipitation indicated that TGM2 interacted with PANX1 to promote lipid deposition, and pharmacological inhibition or knockdown of PANX1 decreased the levels of PPAR α and PANK1 induced by ADR. Taken together, our findings revealed that TGM2-PANX1 interaction in promoting lipid deposition may be a new signaling in promoting ADR-induced nephropathy. And a novel natural peptide could ameliorate renal fibrosis through TGM2-PANX1-PPAR α/PANK1 pathway, which highlight the potential of it in the treatment of CKD.

ToxinPred 3.0: An improved method for predicting the toxicity of peptides

Toxicity emerges as a prominent challenge in the design of therapeutic peptides, causing the failure of numerous peptides during clinical trials. In 2013, our group developed ToxinPred, a computational method that has been extensively adopted by the scientific community for predicting peptide toxicity. In this paper, we propose a refined variant of ToxinPred that showcases improved reliability and accuracy in predicting peptide toxicity. Initially, we utilized a similarity/alignment-based approach employing BLAST to predict toxic peptides, which yielded satisfactory accuracy; however, the method suffered from inadequate coverage. Subsequently, we employed a motif-based approach using MERCI software to uncover specific patterns or motifs that are exclusively observed in toxic peptides. The search for these motifs in peptides allowed us to predict toxic peptides with a high level of specificity with poor sensitivity. To overcome the coverage limitations, we developed alignment-free methods using machine/deep learning techniques to balance sensitivity and specificity of prediction. Deep learning model (ANN - LSTM with fixed sequence length) developed using one-hot encoding achieved a maximum AUROC of 0.93 with MCC of 0.71 on an independent dataset. Machine learning model (extra tree) developed using compositional features of peptides achieved a maximum AUROC of 0.95 with MCC of 0.78. We also developed large language models and achieved maximum AUC of 0.93 using ESM2-t33. Finally, we developed hybrid or ensemble methods combining two or more methods to enhance performance. Our specific hybrid method, which combines a motif-based approach with a machine learning-based model, achieved a maximum AUROC of 0.98 with MCC 0.81 on an independent dataset. In this study, all models were trained and tested on 80 % of data using five-fold cross-validation and evaluated on the remaining 20 % of data called independent dataset. The evaluation of all methods on an independent dataset revealed that the method proposed in this study exhibited better performance than existing methods. To cater to the needs of the scientific community, we have developed a standalone software, pip package and web-based server ToxinPred3 (https://github.com/raghavagps/toxinpred3 and https://webs.iiitd.edu.in/raghava/toxinpred3/).

Discovery of potential antidiabetic peptides using deep learning

Antidiabetic peptides (ADPs), peptides with potential antidiabetic activity, hold significant importance in the treatment and control of diabetes. Despite their therapeutic potential, the discovery and prediction of ADPs remain challenging due to limited data, the complex nature of peptide functions, and the expensive and time-consuming nature of traditional wet lab experiments. This study aims to address these challenges by exploring methods for the discovery and prediction of ADPs using advanced deep learning techniques. Specifically, we developed two models: a single-channel CNN and a three-channel neural network (CNN + RNN + Bi-LSTM). ADPs were primarily gathered from the BioDADPep database, alongside thousands of non-ADPs sourced from anticancer, antibacterial, and antiviral peptide datasets. Subsequently, data preprocessing was performed with the evolutionary scale model (ESM-2), followed by model training and evaluation through 10-fold cross-validation. Furthermore, this work collected a series of newly published ADPs as an independent test set through literature review, and found that the CNN model achieved the highest accuracy (90.48 %) in predicting the independent test set, surpassing existing ADP prediction tools. Finally, the application of the model was considered. SeqGAN was used to generate new candidate ADPs, followed by screening with the constructed CNN model. Selected peptides were then evaluated using physicochemical property prediction and structural forecasts for pharmaceutical potential. In summary, this study not only established robust ADP prediction models but also employed these models to screen a batch of potential ADPs, addressing a critical need in the field of peptide-based antidiabetic research.

Antibody-peptide conjugates deliver covalent inhibitors blocking oncogenic cathepsins

Cysteine cathepsins are a family of proteases that are relevant therapeutic targets for the treatment of different cancers and other diseases. However, no clinically approved drugs for these proteins exist, as their systemic inhibition can induce deleterious side effects. To address this problem, we developed a modular antibody-based platform for targeted drug delivery by conjugating non-natural peptide inhibitors (NNPIs) to antibodies. NNPIs were functionalized with reactive warheads for covalent inhibition, optimized with deep saturation mutagenesis and conjugated to antibodies to enable cell-type-specific delivery. Our antibody-peptide inhibitor conjugates specifically blocked the activity of cathepsins in different cancer cells, as well as osteoclasts, and showed therapeutic efficacy in vitro and in vivo. Overall, our approach allows for the rapid design of selective cathepsin inhibitors and can be generalized to inhibit a broad class of proteases in cancer and other diseases.

Dual electro-/pH-responsive nanoparticle/hydrogel system for controlled delivery of anticancer peptide

An electro-chemo-responsive carrier has been engineered for the controlled release of a highly hydrophilic anticancer peptide, CR(NMe)EKA (Cys-Arg- N-methyl-Glu-Lys-Ala). Remotely controlled on demand release of CR(NMe)EKA, loaded in electro-responsive poly(3,4-ethylenedioxythiophene) (PEDOT) nanoparticles, has been achieved by applying electrical stimuli consisting of constant positive (+0.50 V) or negative voltages (-0.50 V) at pre-defined time intervals. In addition, after loading CR(NMe)EKA/PEDOT nanoparticles into an injectable pH responsive hydrogel formed by phenylboronic acid grafted to chitosan (PBA-CS), the efficiency of the controlled peptide release has increased approximately by a factor of 2.6. The hydration ratio of such hydrogel is significantly lower in acidic environments than in neutral and basic media, which has been attributed to the dissociation of the boronate bonds between polymer chains. Hence, the electro-controlled peptide release from PBA-CS/CR(NMe)EKA/PEDOT hydrogels, in the acidic environment of tumors, combines the effects of the oxidation and reduction of PEDOT chains on the interactions with the peptide and the carrier, with the peptide concentration gradient at the interface between the collapsed hydrogel and the release medium. Furthermore, the peptide released by electro-stimulation preserved its bioactivity assessed by promoting human prostate cancer cells death. Overall, this work is a promising attempt to develop a carrier platform for small hydrophilic anticancer peptides, which delivery rationale is synergistically regulated by the electrical and pH responsiveness of the carrier.

Genetically encoded libraries and spider venoms as emerging sources for crop protective peptides

Agricultural crops are targeted by various pathogens (fungi, bacteria, and viruses) and pests (herbivorous arthropods). Antimicrobial and insecticidal peptides are increasingly recognized as eco-friendly tools for crop protection due to their low propensity for resistance development and the fact that they are fully biodegradable. However, historical challenges have hindered their development, including poor stability, limited availability, reproducibility issues, high production costs, and unwanted toxicity. Toxicity is a primary concern because crop-protective peptides interact with various organisms of environmental and economic significance. This review focuses on the potential of genetically encoded peptide libraries like the use of two-hybrid-based methods for antimicrobial peptides identification and insecticidal spider venom peptides as two main approaches for targeting plant pathogens and pests. We discuss some key findings and challenges regarding the practical application of each strategy. We conclude that genetically encoded peptide library- and spider venom-derived crop protective peptides offer a sustainable and environmentally responsible approach for addressing modern crop protection needs in the agricultural sector.