The Current State of Peptide Drug Discovery: Back to the Future?

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/).

ProBAN: Neural network algorithm for predicting binding affinity in protein-protein complexes

Determining binding affinities in protein-protein and protein-peptide complexes is a challenging task that directly impacts the development of peptide and protein pharmaceuticals. Although several models have been proposed to predict the value of the dissociation constant and the Gibbs free energy, they are currently not capable of making stable predictions with high accuracy, in particular for complexes consisting of more than two molecules. In this work, we present ProBAN, a new method for predicting binding affinity in protein-protein complexes based on a deep convolutional neural network. Prediction is carried out for the spatial structures of complexes, presented in the format of a 4D tensor, which includes information about the location of atoms and their abilities to participate in various types of interactions realized in protein-protein and protein-peptide complexes. The effectiveness of the model was assessed both on an internal test data set containing complexes consisting of three or more molecules, as well as on an external test for the PPI-Affinity service. As a result, we managed to achieve the best prediction quality on these data sets among all the analyzed models: on the internal test, Pearson correlation R = 0.6, MAE = 1.60, on the external test, R = 0.55, MAE = 1.75. The open-source code, the trained ProBAN model, and the collected dataset are freely available at the following link https://github.com/EABogdanova/ProBAN.

Organophotoredox-Catalyzed Synthesis of Unnatural α/β Amino Acids and Peptides via Deaminative Three-Component Coupling

Herein, we disclose an expedient visible-light-mediated, organophotoredox-catalyzed multicomponent synthesis of unnatural amino acids using a Katritzky salt, glyoxal derivatives, and substituted anilines. Mechanistically, an alkyl radical is generated from the Katritzky salt via a deaminative process that undergoes addition to the in situ-generated imine to furnish α-amino acids in a moderate diastereoisomeric ratio. For the first time, we have demonstrated this deaminative protocol to access substituted β-amino acids from α-amino acid-derived Katritzky salts. Furthermore, α-amino amides are also generated from the corresponding 2-oxoacetamide derivatives.

Digital nets conformational sampling (DNCS) - an enhanced sampling technique to explore the conformational space of intrinsically disordered peptides

We propose digital nets conformational sampling (DNCS) - an enhanced sampling technique to explore the conformational ensembles of peptides, especially intrinsically disordered peptides (IDPs). The DNCS algorithm relies on generating history-dependent samples of dihedral variables using bitwise XOR operations and binary angle measurements (BAM). The algorithm was initially studied using met-enkephalin, a highly elusive neuropeptide. The DNCS method predicted near-native structures and the energy landscape of met-enkephalin was observed to be in direct correlation with earlier studies on the neuropeptide. Clustering analysis revealed that there are only 24 low-lying conformations of the molecule. The DNCS method has then been tested for predicting optimal conformations of 42 oligopeptides of length varying from 3 to 8 residues. The closest-to-native structures of 86% of cases are near-native and 24% of them have a root mean square deviation of less than 1.00 Å with respect to their crystal structures. The results obtained reveal that the DNCS method performs well, that too in less computational time.

Medium-sized peptides from microbial sources with potential for antibacterial drug development

Covering: 1993 to the end of 2022As the rapid development of antibiotic resistance shrinks the number of clinically available antibiotics, there is an urgent need for novel options to fill the existing antibiotic pipeline. In recent years, antimicrobial peptides have attracted increased interest due to their impressive broad-spectrum antimicrobial activity and low probability of antibiotic resistance. However, macromolecular antimicrobial peptides of plant and animal origin face obstacles in antibiotic development because of their extremely short elimination half-life and poor chemical stability. Herein, we focus on medium-sized antibacterial peptides (MAPs) of microbial origin with molecular weights below 2000 Da. The low molecular weight is not sufficient to form complex protein conformations and is also associated to a better chemical stability and easier modifications. Microbially-produced peptides are often composed of a variety of non-protein amino acids and terminal modifications, which contribute to improving the elimination half-life of compounds. Therefore, MAPs have great potential for drug discovery and are likely to become key players in the development of next-generation antibiotics. In this review, we provide a detailed exploration of the modes of action demonstrated by 45 MAPs and offer a concise summary of the structure-activity relationships observed in these MAPs.

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.

Targeting Leishmania Promastigotes and Amastigotes Forms through Amino Acids and Peptides: A Promising Therapeutic Strategy

Millions of people worldwide are affected by leishmaniasis, caused by the Leishmania parasite. Effective treatment is challenging due to the biological complexity of the parasite, drug toxicity, and increasing resistance to conventional drugs. To combat this disease, the development of specific strategies to target and selectively eliminate the parasite is crucial. This Review highlights the importance of amino acids in the developmental stages of Leishmania as a factor determining whether the infection progresses or is suppressed. It also explores the use of peptides as alternatives in parasite control and the development of novel targeted treatments. While these strategies show promise for more effective and targeted treatment, further studies to address the remaining challenges are imperative.

PICKAPEP: An application for parameter calculation and visualization of cyclized and modified peptidomimetics

The interest in peptides and especially in peptidomimetic structures has risen enormously in the past few years. Novel modification strategies including nonnatural amino acids, sophisticated cyclization strategies, and side chain modifications to improve the pharmacokinetic properties of peptides are continuously arising. However, a calculator tool accompanying the current development in peptide sciences towards modified peptides is missing. Herein, we present the application PICKAPEP, enabling the virtual construction and visualization of peptidomimetics ranging from well-known cyclized and modified peptides such as ciclosporin A up to fully self-designed peptide-based structures with custom amino acids. Calculated parameters include the molecular weight, the water-octanol partition coefficient, the topological polar surface area, the number of rotatable bonds, and the peptide SMILES code. To our knowledge, PICKAPEP is the first tool allowing users to add custom amino acids as building blocks and also the only tool giving the possibility to process large peptide libraries and calculate parameters for multiple peptides at once. We believe that PICKAPEP will support peptide researchers in their work and will find wide application in current as well as future peptide drug development processes. PICKAPEP is available open source for Windows and Mac operating systems (https://urldefense.com/v3/__https://www.research-collection.ethz.ch/handle/20.500.11850/681174__;!!N11eV2iwtfs!qt5f_2lNd6IZUDH1HVSVwg0zYzS8-nFazQ8c61jS5GaD5vkVS5C3igyfh3haJRnaX8ugW7o9VWUiCihPqcptmaWoqwYf9LvZTQ$).

Selective Macrocyclization of Unprotected Peptides with an Ex Situ Gaseous Linchpin Reagent

Peptide cyclization has dramatic effects on a variety of important properties, enhancing metabolic stability, limiting conformational flexibility, and altering cellular entry and intracellular localization. The hydrophilic, polyfunctional nature of peptides creates chemoselectivity challenges in macrocyclization, especially for natural sequences without biorthogonal handles. Herein, we describe a gaseous sulfonyl chloride derived reagent that achieves amine-amine, amine-phenol, and amine-aniline crosslinking through a minimalist linchpin strategy that affords macrocyclic urea or carbamate products. The cyclization reaction is metal-mediated and involves a novel application of sulfine species that remains unexplored in aqueous or biological contexts. The aqueous method delivers unique cyclic or bicyclic topologies directly from a variety of natural bioactive peptides without the need for protecting-group strategies.

Crafting Unnatural Peptide Macrocycles via Rh(III)-Catalyzed Carboamidation

Contemporary developments in the field of peptide macrocyclization methodology are imperative for enabling the advance of drug design in medicinal chemistry. This report discloses a Rh(III)-catalyzed macrocyclization via carboamidation, reacting acryloyl-peptide-dioxazolone precursors and arylboronic acids to form complex cyclic peptides with concomitant incorporation of noncanonical α-amino acids. The diverse and modular technology allows for expedient access to a wide variety of cyclic peptides from 4 to 15 amino acids in size and features simultaneous formation of unnatural phenylalanine and tyrosine derivatives with up to >20:1 diastereoselectivity. The reaction showcases an expansive substrate scope with 45 examples and is compatible with the majority of standard protected amino acids used in Fmoc-solid phase peptide synthesis. The methodology is applied to the synthesis of multiple peptidomimetic macrocyclic analogs, including derivatives of cyclosomatostatin and gramicidin S.

Iridium-catalyzed diacylmethylation of tyrosine and its peptides with sulfoxonium ylides

Pyridyloxy-directed Ir(III)-catalyzed diacylmethylation of protected tyrosines was achieved with alkyl and (hetero)aryl sulfoxonium ylides, furnishing tyrosine-based unnatural amino acids in good yields. Furthermore, the late stage exemplification of the strategy was successfully accomplished in tyrosine-containing dipeptides, tripeptides and tetrapeptides in moderate yields. This methodology is distinguished by its site-selectivity, tolerance of sensitive functional groups, scalability, and retention of the chiral configuration for tyrosine motifs.

Rational design of small-sized peptidomimetic inhibitors disrupting protein-protein interaction

Protein-protein interactions are fundamental to nearly all biological processes. Due to their structural flexibility, peptides have emerged as promising candidates for developing inhibitors targeting large and planar PPI interfaces. However, their limited drug-like properties pose challenges. Hence, rational modifications based on peptide structures are anticipated to expedite the innovation of peptide-based therapeutics. This review comprehensively examines the design strategies for developing small-sized peptidomimetic inhibitors targeting PPI interfaces, which predominantly encompass two primary categories: peptidomimetics with abbreviated sequences and low molecular weights and peptidomimetics mimicking secondary structural conformations. We have also meticulously detailed several instances of designing and optimizing small-sized peptidomimetics targeting PPIs, including MLL1-WDR5, PD-1/PD-L1, and Bak/Bcl-xL, among others, to elucidate the potential application prospects of these design strategies. Hopefully, this review will provide valuable insights and inspiration for the future development of PPI small-sized peptidomimetic inhibitors in pharmaceutical research endeavors.

Late-stage peptide modification and macrocyclization enabled by tertiary amine catalyzed tryptophan allylation

Late-stage modification of peptides could potentially endow peptides with significant bioactivity and physicochemical properties, and thereby provide novel opportunities for peptide pharmaceutical studies. Since tryptophan (Trp) bears a unique indole ring residue and plays various critical functional roles in peptides, the modification methods for tryptophan were preliminarily developed with considerable progress via transition-metal mediated C-H activation. Herein, we report an unprecedented tertiary amine catalyzed peptide allylation via the SN2'-SN2' pathway between the N1 position of the indole ring of Trp and Morita-Baylis-Hillman (MBH) carbonates. Using this method that proceeds under mild conditions, we demonstrated an extremely broad scope of Trp-containing peptides and MBH carbonates to prepare a series of peptide conjugates and cyclic peptides. The reaction is amenable to either solid-phase (on resin) or solution-phase conditions. In addition, the modified peptides can be further conjugated with other biomolecules at Trp, providing a new handle for bioconjugation.

Ultrashort-Peptide-Responsive Gene Switches for Regulation of Therapeutic Protein Expression in Mammalian Cells

Despite the array of mammalian transgene switches available for regulating therapeutic protein expression in response to small molecules or physical stimuli, issues remain, including cytotoxicity of chemical inducers and limited biocompatibility of physical cues. This study introduces gene switches driven by short peptides comprising eight or fewer amino acid residues. Utilizing a competence regulator (ComR) and sigma factor X-inducing peptide (XIP) from Streptococcus vestibularis as the receptor and inducer, respectively, this study develops two strategies for a peptide-activated transgene control system. The first strategy involves fusing ComR with a transactivation domain and utilizes ComR-dependent synthetic promoters to drive expression of the gene-of-interest, activated by XIP, thereby confirming its membrane penetrability and intracellular functionality. The second strategy features an orthogonal synthetic receptor exposing ComR extracellularly (ComREXTRA), greatly increasing sensitivity with exceptional responsiveness to short peptides. In a proof-of-concept study, peptides are administered to type-1 diabetic mice with microencapsulated engineered human cells expressing ComREXTRA for control of insulin expression, restoring normoglycemia. It is envisioned that this system will encourage the development of short peptide drugs and promote the introduction of non-toxic, orthogonal, and highly biocompatible personalized biopharmaceuticals for gene- and cell-based therapies.

Iron-Catalyzed C-H Alkylamination of Tyrosine Derivatives

An efficient method for the direct alkylamination of tyrosine derivatives via iron-catalyzed C-H amination has been developed. The method, using O-benzoyl-N,N-dialkylhydroxylamines as aminating agents, provides various C-amino-functionalized tyrosine derivatives in up to 77% yield. The utility of this method is showcased by its application to the direct introduction of drug molecules into tyrosine, facilitating access to structurally diverse amino-functionalized tyrosine derivatives.

Phage-encoded bismuth bicycles enable instant access to targeted bioactive peptides

Genetically encoded libraries play a crucial role in discovering structurally rigid, high-affinity macrocyclic peptide ligands for therapeutic applications. Bicyclic peptides with metal centres like bismuth were recently developed as a new type of constrained peptide with notable affinity, stability and membrane permeability. This study represents the genetic encoding of peptide-bismuth and peptide-arsenic bicycles in phage display. We introduce bismuth tripotassium dicitrate (gastrodenol) as a water-soluble bismuth(III) reagent for phage library modification and in situ bicyclic peptide preparation, eliminating the need for organic co-solvents. Additionally, we explore arsenic(III) as an alternative thiophilic element that is used analogously to our previously introduced bicyclic peptides with a bismuth core. The modification of phage libraries and peptides with these elements is instantaneous and entirely biocompatible, offering an advantage over conventional alkylation-based methods. In a pilot display screening campaign aimed at identifying ligands for the biotin-binding protein streptavidin, we demonstrate the enrichment of bicyclic peptides with dissociation constants two orders of magnitude lower than those of their linear counterparts, underscoring the impact of structural constraint on binding affinity.

In silico design of peptide inhibitors for Dengue virus to treat Dengue virus-associated infections

Dengue virus is a single positive-strand RNA virus that is composed of three structural proteins including capsid, envelope, and precursor membrane while seven non-structural proteins (NS1, NS2A, NS2B, NS3A, NS3B, NS4, and NS5). Dengue is a viral infection caused by the dengue virus (DENV). DENV infections are asymptomatic or produce only mild illness. However, DENV can occasionally cause more severe cases and even death. There is no specific treatment for dengue virus infections. Therapeutic peptides have several important advantages over proteins or antibodies: they are small in size, easy to synthesize, and have the ability to penetrate the cell membranes. They also have high activity, specificity, affinity, and less toxicity. Based on the known peptide inhibitor, the current study designs peptide inhibitors for dengue virus envelope protein using an alanine and residue scanning technique. By replacing I21 with Q21, L14 with H14, and V28 with K28, the binding affinity of the peptide inhibitors was increased. The newly designed peptide inhibitors with single residue mutation improved the binding affinity of the peptide inhibitors. The inhibitory capability of the new promising peptide inhibitors was further confirmed by the utilization of MD simulation and free binding energy calculations. The molecular dynamics simulation demonstrated that the newly engineered peptide inhibitors exhibited greater stability compared to the wild-type peptide inhibitors. According to the binding free energies MM(GB)SA of these developed peptides, the first peptide inhibitor was the most effective against the dengue virus envelope protein. All peptide derivatives had higher binding affinities for the envelope protein and have the potential to treat dengue virus-associated infections. In this study, new peptide inhibitors were developed for the dengue virus envelope protein based on the already reported peptide inhibitor.

A production platform for disulfide-bonded peptides in the periplasm of Escherichia coli

BACKGROUND

Recombinant peptide production in Escherichia coli provides a sustainable alternative to environmentally harmful and size-limited chemical synthesis. However, in-vivo production of disulfide-bonded peptides at high yields remains challenging, due to degradation by host proteases/peptidases and the necessity of translocation into the periplasmic space for disulfide bond formation.

RESULTS

In this study, we established an expression system for efficient and soluble production of disulfide-bonded peptides in the periplasm of E. coli. We chose model peptides with varying complexity (size, structure, number of disulfide bonds), namely parathyroid hormone 1-84, somatostatin 1-28, plectasin, and bovine pancreatic trypsin inhibitor (aprotinin). All peptides were expressed without and with the N-terminal, low molecular weight CASPON™ tag (4.1 kDa), with the expression cassette being integrated into the host genome. During BioLector™ cultivations at microliter scale, we found that most of our model peptides can only be sufficiently expressed in combination with the CASPON™ tag, otherwise expression was only weak or undetectable on SDS-PAGE. Undesired degradation by host proteases/peptidases was evident even with the CASPON™ tag. Therefore, we investigated whether degradation happened before or after translocation by expressing the peptides in combination with either a co- or post-translational signal sequence. Our results suggest that degradation predominantly happened after the translocation, as degradation fragments appeared to be identical independent of the signal sequence, and expression was not enhanced with the co-translational signal sequence. Lastly, we expressed all CASPON™-tagged peptides in two industry-relevant host strains during C-limited fed-batch cultivations in bioreactors. We found that the process performance was highly dependent on the peptide-host-combination. The titers that were reached varied between 0.6-2.6 g L-1, and exceeded previously published data in E. coli. Moreover, all peptides were shown by mass spectrometry to be expressed to completion, including full formation of disulfide bonds.

CONCLUSION

In this work, we demonstrated the potential of the CASPON™ technology as a highly efficient platform for the production of soluble peptides in the periplasm of E. coli. The titers we show here are unprecedented whenever parathyroid hormone, somatostatin, plectasin or bovine pancreatic trypsin inhibitor were produced in E. coli, thus making our proposed upstream platform favorable over previously published approaches and chemical synthesis.

Therapeutic peptides for coronary artery diseases: in silico methods and current perspectives

Many drug formulations containing small active molecules are used for the treatment of coronary artery disease, which affects a significant part of the world's population. However, the inadequate profile of these molecules in terms of therapeutic efficacy has led to the therapeutic use of protein and peptide-based biomolecules with superior properties, such as target-specific affinity and low immunogenicity, in critical diseases. Protein‒protein interactions, as a consequence of advances in molecular techniques with strategies involving the combined use of in silico methods, have enabled the design of therapeutic peptides to reach an advanced dimension. In particular, with the advantages provided by protein/peptide structural modeling, molecular docking for the study of their interactions, molecular dynamics simulations for their interactions under physiological conditions and machine learning techniques that can work in combination with all these, significant progress has been made in approaches to developing therapeutic peptides that can modulate the development and progression of coronary artery diseases. In this scope, this review discusses in silico methods for the development of peptide therapeutics for the treatment of coronary artery disease and strategies for identifying the molecular mechanisms that can be modulated by these designs and provides a comprehensive perspective for future studies.

Bioinspired Synthesis of Allysine for Late-Stage Functionalization of Peptides

Inspired by the enzyme lysyl oxidase, which selectively converts the side chain of lysine into allysine, an aldehyde-containing post-translational modification, we report herein the first chemical method for the synthesis of allysine by selective oxidation of dimethyl lysine. This approach is highly chemoselective for dimethyl lysine on proteins. We highlight the utility of this biomimetic approach for generating aldehydes in a variety of pharmaceutically active linear and cyclic peptides at a late stage for their diversification with various affinity and fluorescent tags. Notably, we utilized this approach for generating small-molecule aldehydes from the corresponding tertiary amines. We further demonstrated the potential of this approach in generating cellular models for studying allysine-associated diseases.

Binding Mechanism between Platelet Glycoprotein and Cyclic Peptide Elucidated by McMD-Based Dynamic Docking

The cyclic peptide OS1 (amino acid sequence: CTERMALHNLC), which has a disulfide bond between both termini cysteine residues, inhibits complex formation between the platelet glycoprotein Ibα (GPIbα) and the von Willebrand factor (vWF) by forming a complex with GPIbα. To study the binding mechanism between GPIbα and OS1 and, therefore, the inhibition mechanism of the protein-protein GPIbα-vWF complex, we have applied our multicanonical molecular dynamics (McMD)-based dynamic docking protocol starting from the unbound state of the peptide. Our simulations have reproduced the experimental complex structure, although the top-ranking structure was an intermediary one, where the peptide was bound in the same location as in the experimental structure; however, the β-switch of GPIbα attained a different conformation. Our analysis showed that subsequent refolding of the β-switch results in a more stable binding configuration, although the transition to the native configuration appears to take some time, during which OS1 could dissociate. Our results show that conformational changes in the β-switch are crucial for successful binding of OS1. Furthermore, we identified several allosteric binding sites of GPIbα that might also interfere with vWF binding, and optimization of the peptide to target these allosteric sites might lead to a more effective inhibitor, as these are not dependent on the β-switch conformation.

Asymmetric Phase-Transfer Alkylation of Readily Available Aryl Aldehyde Schiff Bases of Amino Acid Ethyl Esters

Asymmetric phase-transfer alkylation of the N-(arylmethylene)-α-alkylamino acid ethyl esters and N-(arylmethylene)glycine ethyl esters was found to be catalyzed by the (R)- or (S)-Simplified Maruoka Catalyst with high efficiency and excellent enantioselectivity. This approach was successfully applied to the enantioselective formal synthesis of the angiotensin II type 2 receptor (AT2R) antagonists Olodanrigan and LX9211, and the practical aspect is demonstrated by the kilogram-scale synthesis of a key intermediate for the synthesis of LX9211.

Process Development of a Macrocyclic Peptide Inhibitor of PD-L1

This article outlines the process development leading to the manufacture of 800 g of BMS-986189, a macrocyclic peptide active pharmaceutical ingredient. Multiple N-methylated unnatural amino acids posed challenges to manufacturing due to the lability of the peptide to cleavage during global side chain deprotection and precipitation steps. These issues were exacerbated upon scale-up, resulting in severe yield loss and necessitating careful impurity identification, understanding the root cause of impurity formation, and process optimization to deliver a scalable synthesis. A systematic study of macrocyclization with its dependence on concentration and pH is presented. In addition, a side chain protected peptide synthesis is discussed where the macrocyclic protected peptide is extremely labile to hydrolysis. A computational study explains the root cause of the increased lability of macrocyclic peptide over linear peptide to hydrolysis. A process solution involving the use of labile protecting groups is discussed. Overall, the article highlights the advancements achieved to enable scalable synthesis of an unusually labile macrocyclic peptide by solid-phase peptide synthesis. The sustainability metric indicates the final preparative chromatography drives a significant fraction of a high process mass intensity (PMI).

Diversification of Phage-Displayed Peptide Libraries with Noncanonical Amino Acid Mutagenesis and Chemical Modification

Sitting on the interface between biologics and small molecules, peptides represent an emerging class of therapeutics. Numerous techniques have been developed in the past 30 years to take advantage of biological methods to generate and screen peptide libraries for the identification of therapeutic compounds, with phage display being one of the most accessible techniques. Although traditional phage display can generate billions of peptides simultaneously, it is limited to expression of canonical amino acids. Recently, several groups have successfully undergone efforts to apply genetic code expansion to introduce noncanonical amino acids (ncAAs) with novel reactivities and chemistries into phage-displayed peptide libraries. In addition to biological methods, several different chemical approaches have also been used to install noncanonical motifs into phage libraries. This review focuses on these recent advances that have taken advantage of both biological and chemical means for diversification of phage libraries with ncAAs.

Therapeutic stapled peptides: Efficacy and molecular targets

Peptide stapling, by employing a stable, preformed alpha-helical conformation, results in the production of peptides with improved membrane permeability and enhanced proteolytic stability, compared to the original peptides, and provides an effective solution to accelerate the rapid development of peptide drugs. Various reviews present peptide stapling chemistries, anchoring residues and one- or two-component cyclization, however, therapeutic stapled peptides have not been systematically summarized, especially focusing on various disease-related targets. This review highlights the latest advances in therapeutic peptide drug development facilitated by the application of stapling technology, including different stapling techniques, synthetic accessibility, applicability to biological targets, potential for solving biological problems, as well as the current status of development. Stapled peptides as therapeutic drug candidates have been classified and analysed mainly by receptor- and ligand-based stapled peptide design against various diseases, including cancer, infectious diseases, inflammation, and diabetes. This review is expected to provide a comprehensive reference for the rational design of stapled peptides for different diseases and targets to facilitate the development of therapeutic peptides with enhanced pharmacokinetic and biological properties.

The design of an RGD in situ sustained delivery system utilizing scallop byssal protein through genetic engineering

Although bioactive peptides enhancing bone healing have demonstrated effectiveness in treating bone defects, in vivo instability poses a challenge to their clinical application. Currently reported peptide delivery systems do not meet the demands of bone tissue repair regarding stability and peptide release efficacy. Herein, the self-assembling recombinant chimeric protein (Sbp5-2RGD) is developed by genetic engineering with cell adhesion peptide RGD as the targeted peptide and a newly discovered scallop byssal-derived protein Sbp5-2 that can assemble into wet stable films as the structural domain. In vitro studies show that the Sbp5-2RGD film exhibits excellent extensibility and biocompatibility. In vitro and in vivo degradation experiments demonstrate that the film remains stable due to the layer-by-layer degradation mode, resulting in sustained delivery of RGD in situ for up to 4 weeks. Consequently, the film can effectively promote osteogenesis, which accelerates bone defect healing and the implants osseointegration. Cell-level studies further show that the film up-regulates the expression of genes and proteins (ALP, OCN, OSX, OPN, RUNX2, VEGF) associated with osteogenesis and angiogenesis. Overall, this novel protein film represents an intelligent platform for peptide immobilization, protection, and release through its self-assembly, dense structure, and degradation mode, providing a therapeutic strategy for bone repair.

Synthesis and biological evaluation of EGFR binding peptides for near-infrared photoimmunotherapy

Near-infrared photoimmunotherapy (NIR-PIT) is a new cancer treatment that involves photoimmunotherapy drug injection and NIR light exposure. In NIR-PIT, antibodies are commonly used as target-directed molecules carrying IRDye700DX (IR700). However, antibodies have disadvantages, such as high cost, complex development strategies, and poor tumor penetration. In contrast, peptides have lower production costs, can be easy to chemically synthesize and modify, and can also be used for tumor-targeting like antibodies. In this study, we developed a novel PIT drug using a peptide as the target-directed molecule. Epidermal growth factor receptor (EGFR) was selected as the target, and monovalent and bivalent EGFR-binding peptides were synthesized. The bivalent peptide showed sufficient binding to EGFR-positive cells, and a bivalent peptide-IR700 conjugate with a long linker induced morphological changes in EGFR-positive cells. Additionally, the drug significantly reduced cell viability in vitro in an NIR light-dose- and drug-concentration-dependent manner. These results indicate the feasibility of NIR-PIT in treating cancer using peptide-based drugs.

iDVEIP: A computer-aided approach for the prediction of viral entry inhibitory peptides

With the notable surge in therapeutic peptide development, various peptides have emerged as potential agents against virus-induced diseases. Viral entry inhibitory peptides (VEIPs), a subset of antiviral peptides (AVPs), offer a promising avenue as entry inhibitors (EIs) with distinct advantages over chemical counterparts. Despite this, a comprehensive analytical platform for characterizing these peptides and their effectiveness in blocking viral entry remains lacking. In this study, we introduce a groundbreaking in silico approach that leverages bioinformatics analysis and machine learning to characterize and identify novel VEIPs. Cross-validation results demonstrate the efficacy of a model combining sequence-based features in predicting VEIPs with high accuracy, validated through independent testing. Additionally, an EI type model has been developed to distinguish peptides specifically acting as Eis from AVPs with alternative activities. Notably, we present iDVEIP, a web-based tool accessible at http://mer.hc.mmh.org.tw/iDVEIP/, designed for automatic analysis and prediction of VEIPs. Emphasizing its capabilities, the tool facilitates comprehensive analyses of peptide characteristics, providing detailed amino acid composition data for each prediction. Furthermore, we showcase the tool's utility in identifying EIs against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2).

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.

Organic Solvent Nanofiltration in Pharmaceutical Applications

Separation and purification in organic solvents are indispensable procedures in pharmaceutical manufacturing. However, they still heavily rely on the conventional separation technologies of distillation and chromatography, resulting in high energy and massive solvent consumption. As an alternative, organic solvent nanofiltration (OSN) offers the benefits of low energy consumption, low solid waste generation, and easy scale-up and incorporation into continuous processes. Thus, there is a growing interest in employing membrane technology in the pharmaceutical area to improve process sustainability and energy efficiency. This Review comprehensively summarizes the recent progress (especially the last 10 years) of organic solvent nanofiltration and its applications in the pharmaceutical industry, including the concentration and purification of active pharmaceutical ingredients, homogeneous catalyst recovery, solvent exchange and recovery, and OSN-assisted peptide/oligonucleotide synthesis. Furthermore, the challenges and future perspectives of membrane technology in pharmaceutical applications are discussed in detail.

An arresten-derived anti-angiogenic peptide triggers apoptotic cell death in endothelial cells

BACKGROUND

In recent years, anti-angiogenic peptides have received considerable attention as candidates for cancer treatment. Arresten is an angiogenesis inhibitor that cleaves from the α1 chain of type IV collagen and stimulates apoptosis in endothelial cells. We have recently indicated that a peptide corresponding to the amino acid 78 to 86 of arresten, so-called Ars, prevented the migration and tube formation of HUVECs and the colon carcinoma growth in mice significantly. The current study aimed to determine whether induction of apoptotic cell death in endothelial cells is one of the biochemical mechanisms of this anti-angiogenic peptide.

METHODS AND RESULTS

This hypothesis was assessed using the MTT assay, cell cycle analysis, Annexin V-FITC/PI staining, BCL2, CASP8, CASP9, p53, and CDKN2A gene expression studies as well as evaluating apoptosis in tumor tissues by TUNEL assay. Results demonstrated that 40 µM of Ars significantly stimulated 46.2% of early and late apoptosis in HUVECs compared to 13.6% in the untreated cells and did not significantly alter the cell cycle distribution. Moreover, BCL2 and CASP8 were down-regulated, while CASP9 and p53 were up-regulated in endothelial cells. CDKN2A gene expression, the regulator of G1 cell cycle arrest, was not significantly altered.

CONCLUSIONS

It might be suggested that Ars induced apoptosis in endothelial cells through the mitochondrial pathway and had no effect on the cell cycle. Besides, Ars induced apoptosis significantly in vivo. However, further studies are required to confirm the detailed molecular mechanism of Ars, this peptide has the potential to be optimized for clinical translations.

On-Resin Photochemical Decarboxylative Arylation of Peptides

Here we describe the application of photochemical decarboxylative arylation as a late-stage functionalization reaction for peptides. The reaction uses redox-active esters of aspartic acid and glutamic acid on the solid phase to provide analogues of aromatic amino acids. By using aryl bromides as arylation reagents, a wide variety of amino acids can be accessed without having to synthesize them individually in solution. The reaction is compatible with proteinogenic amino acids and was used to perform a structure-activity relationship study of a PRMT5 binding peptide.

Peptide Dendrimer-Based Antibacterial Agents: Synthesis and Applications

Pathogenic bacteria cause the deaths of millions of people every year. With the development of antibiotics, hundreds and thousands of people's lives have been saved. Nevertheless, bacteria can develop resistance to antibiotics, rendering them insensitive to antibiotics over time. Peptides containing specific amino acids can be used as antibacterial agents; however, they can be easily degraded by proteases in vivo. To address these issues, branched peptide dendrimers are now being considered as good antibacterial agents due to their high efficacy, resistance to protease degradation, and low cytotoxicity. The ease with which peptide dendrimers can be synthesized and modified makes them accessible for use in various biological and nonbiological fields. That is, peptide dendrimers hold a promising future as antibacterial agents with prolonged efficacy without bacterial resistance development. Their in vivo stability and multivalence allow them to effectively target multi-drug-resistant strains and prevent biofilm formation. Thus, it is interesting to have an overview of the development and applications of peptide dendrimers in antibacterial research, including the possibility of employing machine learning approaches for the design of AMPs and dendrimers. This review summarizes the synthesis and applications of peptide dendrimers as antibacterial agents. The challenges and perspectives of using peptide dendrimers as the antibacterial agents are also discussed.

Therapeutic proteins: developments, progress, challenges, and future perspectives

Proteins are considered magic molecules due to their enormous applications in the health sector. Over the past few decades, therapeutic proteins have emerged as a promising treatment option for various diseases, particularly cancer, cardiovascular disease, diabetes, and others. The formulation of protein-based therapies is a major area of research, however, a few factors still hinder the large-scale production of these therapeutic products, such as stability, heterogenicity, immunogenicity, high cost of production, etc. This review provides comprehensive information on various sources and production of therapeutic proteins. The review also summarizes the challenges currently faced by scientists while developing protein-based therapeutics, along with possible solutions. It can be concluded that these proteins can be used in combination with small molecular drugs to give synergistic benefits in the future.

N-Terminal-Specific Dual Modification of Peptides through Copper-Catalyzed [3+2] Cycloaddition

Site-specific introduction of multiple components into peptides is greatly needed for the preparation of densely functionalized and structurally uniform peptides. In this regard, N-terminal-specific peptide modification is attractive, but it can be difficult due to the presence of highly nucleophilic lysine ϵ-amine. In this work, we developed a method for the N-terminal-specific dual modification of peptides through a three-component [3+2] cycloaddition with aldehydes and maleimides under mild copper catalysis. This approach enables exclusive functionalization at the glycine N-terminus of iminopeptides, regardless of the presence of lysine ϵ-amine, thus affording the cycloadducts in excellent yields. Tolerating a broad range of functional groups and molecules, the present method provides the opportunity to rapidly construct doubly functionalized peptides using readily accessible aldehyde and maleimide modules.

Deep learning for advancing peptide drug development: Tools and methods in structure prediction and design

Peptides can bind challenging disease targets with high affinity and specificity, offering enormous opportunities for addressing unmet medical needs. However, peptides' unique features, including smaller size, increased structural flexibility, and limited data availability, pose additional challenges to the design process compared to proteins. This review explores the dynamic field of peptide therapeutics, leveraging deep learning to enhance structure prediction and design. Our exploration encompasses various facets of peptide research, ranging from dataset curation handling to model development. As deep learning technologies become more refined, we channel our efforts into peptide structure prediction and design, aligning with the fundamental principles of structure-activity relationships in drug development. To guide researchers in harnessing the potential of deep learning to advance peptide drug development, our insights comprehensively explore current challenges and future directions of peptide therapeutics.

Catalyst-free decarboxylative cross-coupling of N-hydroxyphthalimide esters with tert-butyl 2-(trifluoromethyl)acrylate and its application

Here, we demonstrate a practical method toward the facile synthesis of CF3-containing amino acids through visible light promoted decarboxylative cross-coupling of a redox-active ester with tert-butyl 2-(trifluoromethyl)acrylate. The reaction was driven by the photochemical activity of electron donor-acceptor (EDA) complexes that were formed by the non-covalent interaction between a Hantzsch ester and a redox-active ester. The advantages of this protocol are its synthetic simplicity, rich functional group tolerance, and a cost-effective reaction system.

Peptide Therapeutics: Unveiling the Potential against Cancer-A Journey through 1989

The United States Food and Drug Administration (FDA) has approved a plethora of peptide-based drugs as effective drugs in cancer therapy. Peptides possess high specificity, permeability, target engagement, and a tolerable safety profile. They exhibit selective binding with cell surface receptors and proteins, functioning as agonists or antagonists. They also serve as imaging agents for diagnostic applications or can serve a dual-purpose as both diagnostic and therapeutic (theragnostic) agents. Therefore, they have been exploited in various forms, including linkers, peptide conjugates, and payloads. In this review, the FDA-approved prostate-specific membrane antigen (PSMA) peptide antagonists, peptide receptor radionuclide therapy (PRRT), somatostatin analogs, antibody-drug conjugates (ADCs), gonadotropin-releasing hormone (GnRH) analogs, and other peptide-based anticancer drugs are analyzed in terms of their chemical structures and properties, therapeutic targets and mechanisms of action, development journey, administration routes, and side effects.

Venomous gland transcriptome and venom proteomic analysis of the scorpion Androctonus amoreuxi reveal new peptides with anti-SARS-CoV-2 activity

The recent COVID-19 pandemic shows the critical need for novel broad spectrum antiviral agents. Scorpion venoms are known to contain highly bioactive peptides, several of which have demonstrated strong antiviral activity against a range of viruses. We have generated the first annotated reference transcriptome for the Androctonus amoreuxi venom gland and used high performance liquid chromatography, transcriptome mining, circular dichroism and mass spectrometric analysis to purify and characterize twelve previously undescribed venom peptides. Selected peptides were tested for binding to the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein and inhibition of the spike RBD - human angiotensin-converting enzyme 2 (hACE2) interaction using surface plasmon resonance-based assays. Seven peptides showed dose-dependent inhibitory effects, albeit with IC50 in the high micromolar range (117-1202 µM). The most active peptide was synthesized using solid phase peptide synthesis and tested for its antiviral activity against SARS-CoV-2 (Lineage B.1.1.7). On exposure to the synthetic peptide of a human lung cell line infected with replication-competent SARS-CoV-2, we observed an IC50 of 200 nM, which was nearly 600-fold lower than that observed in the RBD - hACE2 binding inhibition assay. Our results show that scorpion venom peptides can inhibit the SARS-CoV-2 replication although unlikely through inhibition of spike RBD - hACE2 interaction as the primary mode of action. Scorpion venom peptides represent excellent scaffolds for design of novel anti-SARS-CoV-2 constrained peptides. Future studies should fully explore their antiviral mode of action as well as the structural dynamics of inhibition of target virus-host interactions.

Mirror-image ligand discovery enabled by single-shot fast-flow synthesis of D-proteins

Widespread adoption of mirror-image biological systems presents difficulties in accessing the requisite D-protein substrates. In particular, mirror-image phage display has the potential for high-throughput generation of biologically stable macrocyclic D-peptide binders with potentially unique recognition modes but is hindered by the individualized optimization required for D-protein chemical synthesis. We demonstrate a general mirror-image phage display pipeline that utilizes automated flow peptide synthesis to prepare D-proteins in a single run. With this approach, we prepare and characterize 12 D-proteins - almost one third of all reported D-proteins to date. With access to mirror-image protein targets, we describe the successful discovery of six macrocyclic D-peptide binders: three to the oncoprotein MDM2, and three to the E3 ubiquitin ligase CHIP. Reliable production of mirror-image proteins can unlock the full potential of D-peptide drug discovery and streamline the study of mirror-image biology more broadly.

Development of a Double-Stapled Peptide Stabilizing Both α-Helix and β-Sheet Structures for Degrading Transcription Factor AR-V7

Peptide drugs offer distinct advantages in therapeutics; however, their limited stability and membrane penetration abilities hinder their widespread application. One strategy to overcome these challenges is the hydrocarbon peptide stapling technique, which addresses issues such as poor conformational stability, weak proteolytic resistance, and limited membrane permeability. Nonetheless, while peptide stapling has successfully stabilized α-helical peptides, it has shown limited applicability for most β-sheet peptide motifs. In this study, we present the design of a novel double-stapled peptide capable of simultaneously stabilizing both α-helix and β-sheet structures. Our designed double-stapled peptide, named DSARTC, specifically targets the androgen receptor (AR) DNA binding domain and MDM2 as E3 ligase. Serving as a peptide-based PROTAC (proteolysis-targeting chimera), DSARTC exhibits the ability to degrade both the full-length AR and AR-V7. Molecular dynamics simulations and circular dichroism analysis validate the successful constraint of both secondary structures, demonstrating that DSARTC is a "first-in-class" heterogeneous-conformational double-stapled peptide drug candidate. Compared to its linear counterpart, DSARTC displays enhanced stability and an improved cell penetration ability. In an enzalutamide-resistant prostate cancer animal model, DSARTC effectively inhibits tumor growth and reduces the levels of both AR and AR-V7 proteins. These results highlight the potential of DSARTC as a more potent and specific peptide PROTAC for AR-V7. Furthermore, our findings provide a promising strategy for expanding the design of staple peptide-based PROTAC drugs, targeting a wide range of "undruggable" transcription factors.

Near-infrared photoimmunotherapy and anti-cancer immunity

The activation of the anti-cancer immune system is an important strategy to control cancer. A new form of cancer phototherapy, near-infrared photoimmunotherapy (NIR-PIT), was approved for clinical use in 2020 and uses IRDye® 700DX (IR700)-conjugated antibodies and NIR light. After irradiation with NIR light, the antibody-IR700 conjugate forms water-insoluble aggregations on the plasma membrane of target cells. This aggregation causes lethal damage to the plasma membrane, and effectively leads to immunogenic cell death (ICD). Subsequently, ICD activates anti-cancer immune cells such as dendritic cells and cytotoxic T cells. Combination therapy with immune-checkpoint blockade has synergistically improved the anti-cancer effects of NIR-PIT. Additionally, NIR-PIT can eliminate immunosuppressive immune cells in light-irradiated tumors by using specific antibodies against regulatory T cells and myeloid-derived suppressor cells. In addition to cancer-cell-targeted NIR-PIT, such immune-cell-targeted NIR-PIT has shown promising results by activating the anti-cancer immune system. Furthermore, NIR-PIT can be used to manipulate the tumor microenvironment by eliminating only targeted cells in the tumor, and thus it also can be used to gain insight into immunity in basic research.

The Potential Use of Peptides in the Fight against Chagas Disease and Leishmaniasis

Chagas disease and leishmaniasis are both neglected tropical diseases that affect millions of people around the world. Leishmaniasis is currently the second most widespread vector-borne parasitic disease after malaria. The World Health Organization records approximately 0.7-1 million newly diagnosed leishmaniasis cases each year, resulting in approximately 20,000-30,000 deaths. Also, 25 million people worldwide are at risk of Chagas disease and an estimated 6 million people are infected with Trypanosoma cruzi. Pentavalent antimonials, amphotericin B, miltefosine, paromomycin, and pentamidine are currently used to treat leishmaniasis. Also, nifurtimox and benznidazole are two drugs currently used to treat Chagas disease. These drugs are associated with toxicity problems such as nephrotoxicity and cardiotoxicity, in addition to resistance problems. As a result, the discovery of novel therapeutic agents has emerged as a top priority and a promising alternative. Overall, there is a need for new and effective treatments for Chagas disease and leishmaniasis, as the current drugs have significant limitations. Peptide-based drugs are attractive due to their high selectiveness, effectiveness, low toxicity, and ease of production. This paper reviews the potential use of peptides in the treatment of Chagas disease and leishmaniasis. Several studies have demonstrated that peptides are effective against Chagas disease and leishmaniasis, suggesting their use in drug therapy for these diseases. Overall, peptides have the potential to be effective therapeutic agents against Chagas disease and leishmaniasis, but more research is needed to fully investigate their potential.

Visible Light-Driven Flexible Synthesis of α-Alkylated Glycine Derivatives Catalyzed by Reusable Covalent Organic Frameworks

Herein, we report a heterogeneous visible light-driven preparation of α-alkylated glycine derivatives. This approach employed a β-ketoenamine-linked covalent organic framework (2D-COF-4) as the heterogeneous photocatalyst and N-hydroxy phthalimide (NHPI) esters as the alkyl radical sources. Numerous glycine derivatives, including dipeptides, were precisely and efficiently alkylated under visible light-driven reaction conditions. Based on the excellent photoactivity and organic reaction compatibility of 2D-COF-4, this alkylation could proceed flexibly in a green solvent (ethanol) without any other additives. The photocatalyst and phthalimide were fruitfully recycled with a simple workup procedure, revealing a high ecoscale value and low environmental factor (E-factor).

Chemically modified antiviral peptides against SARS-CoV-2

To date, the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) COVID-19 pandemic continues to be a potentially lethal disease. Although both vaccines and specific antiviral drugs have been approved, the search for more specific therapeutic approaches is still ongoing. The infection mechanism of SARS-CoV-2 consists of several stages, and each one can be selectively blocked to disrupt viral infection. Peptides are a promising class of antiviral compounds, which may be suitably modified to be more stable, more effective, and more selective towards a specific viral replication step. The latter two goals might be obtained by increasing the specificity and/or the affinity of the interaction with a specific target and often imply the stabilization of the secondary structure of the active peptide. This review is focused on modified antiviral peptides against SARS-CoV-2 acting at different stages of virus replication, including ACE2-RBD interaction, membrane fusion mechanism, and the proteolytic cleavage by different viral proteases. Therefore, the landscape presented herein provides a useful springboard for the design of new and powerful antiviral therapeutics.

Mirror-Image Phage Display for the Selection of D-Amino Acid Peptide Ligands as Potential Therapeutics

In neurodegenerative diseases like Alzheimer's disease (AD), endogenous proteins or peptides aggregate with themselves. These proteins may lose their function or aggregates and/or oligomers can obtain toxicity, causing injury or death to cells. Aggregation of two major proteins characterizes AD. Amyloid-β peptide (Aβ) is deposited in amyloid plaques within the extracellular space of the brain and Tau in so-called neurofibrillary tangles in neurons. Finding peptide ligands to halt protein aggregation is a promising therapeutical approach. Using mirror-image phage display with a commercially available, randomized 12-mer peptide library, we have selected D-amino acid peptides, which bind to the Tau protein and modulate its aggregation in vitro. Peptides can bind specifically and selectively to a target molecule, but natural L-amino acid peptides may have crucial disadvantages for in vivo applications, as they are sensitive to protease degradation and may elicit immune responses. One strategy to circumvent these disadvantages is the use of non-naturally occurring D-amino acid peptides as they exhibit increased protease resistance and generally do not activate the immune system. To perform mirror-image phage display, the target protein needs to be synthesized as D-amino acid version. If the target protein sequence is too long to be synthesized properly, smaller peptides derived from the full length protein can be used for the selection process. This also offers the possibility to influence the binding region of the selected D-peptides in the full-length target protein. Here we provide the protocols for mirror-image phage display selection on the PHF6* peptide of Tau, based on the commercially available Ph.D.™-12 Phage Display Peptide Library Kit, leading to D-peptides that also bind the full length Tau protein (Tau441), next to PHF6*. In addition, we provide protocols and data for the first characterization of those D-peptides that inhibit Tau aggregation in vitro. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Mirror image phage display selection against D-PHF6* fibrils Support Protocol 1: Single phage ELISA Basic Protocol 2: Sequencing and D-peptide generation Basic Protocol 3: Thioflavin-T (ThT) test to control inhibition of Tau aggregation Support Protocol 2: Purification of full-length Tau protein Basic Protocol 4: ELISA to demonstrate the binding of the generated D-peptides to PHF6* and full-length Tau fibrils.

Amphibian-derived peptide RL-RF10 ameliorates paraquat-induced pulmonary fibrosis injury

Pulmonary fibrosis is the result of dysfunctional repair after lung tissue injury, characterized by fibroblast proliferation and massive extracellular matrix aggregation. Once fibrotic lesions develop, effective treatment is difficult, with few drugs currently available. Here, we identified a short cyclic decapeptide RL-RF10 derived from frog skin secretions as a potential novel lead molecule for the amelioration of pulmonary fibrosis. In vivo experiments indicated that RL-RF10 treatment ameliorated lung histopathological damage and fibrogenesis after paraquat (PQ) induction in a concentration-dependent manner. On day 7, bronchoalveolar lavage fluid assays performed on mice showed that RL-RF10 exerted anti-inflammatory effects by decreasing the expression of inflammation-related factors, including transforming growth factor-β1 (TGF-β1) and tumor necrosis factor-α, in lung tissue. In addition, RL-RF10 down-regulated the levels of collagen I, collagen III, and vimentin, while increasing the expression of E-cadherin to inhibit epithelial-mesenchymal transition. Further research demonstrated that the SMAD2/3 signaling pathway, which is strongly linked to TGF-β1, played a critical function in enhancing the pulmonary fibrosis relief achieved by RL-RF10. Both in vivo and in vitro assays showed that RL-RF10 treatment led to a significant reduction in the phosphorylation levels of SMAD2 and SMAD3 following PQ induction. Overall, we investigated the protective effects and underlying mechanisms of the RL-RF10 peptide against pulmonary fibrosis and demonstrated its potential as a novel therapeutic drug candidate for the treatment of pulmonary fibrotic diseases.

Inhibition of protein-protein interactions using biodegradable depsipeptide nanoassemblies

Although peptides notoriously have poor intrinsic pharmacokinetic properties, it is well-known that nanostructures with excellent pharmacokinetic properties can be designed. Noticing that peptide inhibitors are generally nonpolar, here, we consolidate the peptide inhibitor targeting intracellular protein-protein interactions (PPIs) as an integral part of biodegradable self-assembled depsipeptide nanostructures (SdPNs). Because the peptide inhibitor has the dual role of PPI inhibition and self-assembly in this design, problems associated with the poor pharmacokinetics of peptides and encapsulation/entrapment processes can be overcome. Optimized SdPNs displayed better tumor targeting and PPI inhibition properties than the comparable small molecule inhibitor in vivo. Kinetics of PPI inhibition for SdPNs were gradual and controllable in contrast to the rapid inhibition kinetics of the small molecule. Because SdPN is modular, any appropriate peptide inhibitor can be incorporated into the platform without concern for the poor pharmacokinetic properties of the peptide.

Traceless Peptide and Protein Modification via Rational Tuning of Pyridiniums

Herein, we report a versatile reaction platform for tracelessly cleavable cysteine-selective peptide/protein modification. This platform offers highly tunable and predictable conjugation and cleavage by rationally estimating the electron effect on the nucleophilic halopyridiniums. Cleavable peptide stapling, antibody conjugation, enzyme masking/de-masking, and proteome labeling were achieved based on this facile pyridinium-thiol-exchange protocol.

Structure prediction of linear and cyclic peptides using CABS-flex

The structural modeling of peptides can be a useful aid in the discovery of new drugs and a deeper understanding of the molecular mechanisms of life. Here we present a novel multiscale protocol for the structure prediction of linear and cyclic peptides. The protocol combines two main stages: coarse-grained simulations using the CABS-flex standalone package and an all-atom reconstruction-optimization process using the Modeller program. We evaluated the protocol on a set of linear peptides and two sets of cyclic peptides, with cyclization through the backbone and disulfide bonds. A comparison with other state-of-the-art tools (APPTEST, PEP-FOLD, ESMFold and AlphaFold implementation in ColabFold) shows that for most cases, AlphaFold offers the highest resolution. However, CABS-flex is competitive, particularly when it comes to short linear peptides. As demonstrated, the protocol performance can be further improved by combination with the residue-residue contact prediction method or more efficient scoring. The protocol is included in the CABS-flex standalone package along with online documentation to aid users in predicting the structure of peptides and mini-proteins.