Therapeutic peptides: current applications and future directions

Novel drug delivery systems for hirudin-based product development and clinical applications

Hirudin, a natural biological polypeptide macromolecule secreted by the salivary glands of medicinal leech, is a specific thrombin inhibitor with multiple favourable bioactivities, including anti-coagulation, anti-fibrotic, and anti-tumour. Despite several anticoagulants have been widely applied in clinic, hirudin shows advantages in reducing the incidence of bleeding side effects by virtue of its high specificity in binding to thrombin. As a result, hirudin has been tested in clinical practice to prevent and treat several complex diseases. However, the application of this polypeptide macromolecule is compromised by its low bioavailability and bioactivity due to poor serum stability and susceptibility to protease degradation in vivo. To overcome these drawbacks, several studies have proposed novel drug delivery systems (NDDSs) to prevent the degradation and increase the targeting efficiency of hirudin. This systematic review summarises the clinical research on hirudin, including its classification and bioactivities, and highlights the opportunities and challenges in the clinical use of hirudin. The NDDSs designed to enhance the bioavailability and bioactivity of hirudin are discussed to explore its application in the treatment of related diseases. This review may considerably contribute to the advancement of delivery science and technology, particularly in the context of polypeptide-based therapeutics.

In silico identification and ex vivo evaluation of Toxoplasma gondii peptides restricted to HLA-A*02, HLA-A*24 and HLA-B*35 alleles in human PBMC from a Colombian population

Toxoplasma gondii infects approximately 30% of the population, and there is currently no approved vaccine. Identifying immunogenic peptides with high affinity to different HLA molecules is a promising vaccine strategy. This study used an in silico approach using artificial neural networks to identify T. gondii peptides restricted to HLA-A*02, HLA-A*24, and HLA-B*35 alleles. Proteomes from seven T. gondii strains and transcriptomic data of overexpressed genes from T. gondii-RH in human PBMC were also used. Parasite protein sequences were analyzed with R 'Epitope Prediction' library. Peptide candidates were evaluated in the artificial neural networks based on the probabilities of output neurons (p > 0.5). The IFN-γ responses in PBMC from T. gondii seronegative and seropositive individuals were evaluated by ELISpot. Peptides with higher IFN-γ induction were evaluated to identify cytotoxic response in CD8+ T cells (CD107a). In silico analysis identified 36 peptides from T. gondii proteins with predicted affinity to HLA-A*02, A*24, and B*35 alleles. Experiments with PBMCs revealed that a peptide restricted to HLA-A02 (P1: FLFAWITYV) induced a significant increase in IFN-γ-producing cells (p = 0.004). For HLA-A24, a peptide (P8: VFAFAFAFFLI) also induced a significant IFN-γ response (p = 0.004), while for the HLA-B*35 allele, the P6 peptide (YPIAPSFAM) induced a response that differed significantly from the control (p = 0.05). These peptides induced also a significant percentage of central memory CD8 + T cells expressing the degranulation marker CD107a (p < 0.05). Finally, we identified three T. gondii peptides that induced IFN-γ response, and a cytotoxic response measured by CD107a expression on CD45RAneg-CD8 cells. These peptides could be considered part of a multi-epitope vaccine against toxoplasmosis in humans.

Targeting Invasion: The Role of MMP-2 and MMP-9 Inhibition in Colorectal Cancer Therapy

Colorectal cancer (CRC) remains one of the most prevalent and lethal cancers worldwide, prompting ongoing research into innovative therapeutic strategies. This review aims to systematically evaluate the role of gelatinases, specifically MMP-2 and MMP-9, as therapeutic targets in CRC, providing a critical analysis of their potential to improve patient outcomes. Gelatinases, specifically MMP-2 and MMP-9, play critical roles in the processes of tumor growth, invasion, and metastasis. Their expression and activity are significantly elevated in CRC, correlating with poor prognosis and lower survival rates. This review provides a comprehensive overview of the pathophysiological roles of gelatinases in CRC, highlighting their contribution to tumor microenvironment modulation, angiogenesis, and the metastatic cascade. We also critically evaluate recent advancements in the development of gelatinase inhibitors, including small molecule inhibitors, natural compounds, and novel therapeutic approaches like gene silencing techniques. Challenges such as nonspecificity, adverse side effects, and resistance mechanisms are discussed. We explore the potential of gelatinase inhibition in combination therapies, particularly with conventional chemotherapy and emerging targeted treatments, to enhance therapeutic efficacy and overcome resistance. The novelty of this review lies in its integration of recent findings on diverse inhibition strategies with insights into their clinical relevance, offering a roadmap for future research. By addressing the limitations of current approaches and proposing novel strategies, this review underscores the potential of gelatinase inhibitors in CRC prevention and therapy, inspiring further exploration in this promising area of oncological treatment.

Co-Localized in Amyloid Plaques Cathepsin B as a Source of Peptide Analogs Potential Drug Candidates for Alzheimer's Disease

Alzheimer's disease (AD) is a complex neurodegenerative disorder characterized by extracellular amyloid plaques, predominantly consisting of amyloid-β (Aβ) peptides. The oligomeric form of Aβ is acknowledged as the most neurotoxic, propelling the pathological progression of AD. Interestingly, besides Aβ, other proteins are co-localized within amyloid plaques. Peptide analogs corresponding to the "aggregation-prone" regions (APRs) of these proteins could exhibit high-affinity binding to Aβ and significant inhibitory potential against the Aβ oligomerization process. The peptide analogs of co-localized protease, Cathepsin B, may act as such potent inhibitors. In silico studies on the complexes of the oligomeric state of Aβ and Cathepsin B peptide analogs were performed utilizing molecular docking and molecular dynamics simulations, revealing that these analogs disrupt the β-sheet-rich core of Aβ oligomers, a critical structural feature of their stability. Of the four peptide analogs evaluated, two demonstrated considerable potential by effectively destabilizing oligomers while maintaining low self-aggregation propensity, i.e., a crucial consideration for therapeutic safety. These findings point out the potential of APR-derived peptide analogs from co-localized proteins as innovative agents against AD, paving the way for further exploration in peptide-based therapeutic development.

Identification and Evaluation of Natural Compounds as Potential Inhibitors of NS2B-NS3 Zika Virus Protease: A Computational Approach

The Zika virus (ZIKV), an arbovirus within the Flavivirus genus, is associated with severe neurological complications, including Guillain-Barré syndrome in affected individuals and microcephaly in infants born to infected mothers. With no approved vaccines or antiviral treatments available, there is an urgent need for effective therapeutic options. This study aimed to identify new natural compounds with inhibitory potential against the NS2B-NS3 protease (PDB ID: 5LC0), an essential enzyme in viral replication. An e-pharmacophore model was generated using a five-point (ADDRR) feature approach in the PHASE module of Schrodinger and used for the virtual screening of 26,689 natural compounds from the PubChem database. The screening yielded 14,277 prioritized compounds based on fitness scores, further refined through extra precision (XP) docking in GLIDE, resulting in 24 compounds. Eight top hits were selected following ADME analysis with SwissADME, and toxicity screening with ProTox-II identified four non-toxic lead candidates. Molecular dynamic simulations confirmed the stability of the three most promising leads, CID 44418637, CID 163078083, and CID 68734190, with binding affinities of - 7.721, - 8.226, and - 8.307 kcal/mol, respectively. MM/GBSA analysis revealed that Compounds 68734190 (- 50.192 kcal/mol) and 163078083 (- 49.947 kcal/mol) possess superior binding affinities to the ZIKV NS2B-NS3 protease compared to the reference compound (- 38.347 kcal/mol). Given their natural origin, these compounds may offer safer options to mitigate severe ZIKV-related symptoms while providing a favourable safety and pharmacokinetic profile. This study lays the groundwork for developing targeted ZIKV therapies, potentially addressing a significant unmet need in public health by reducing the incidence of ZIKV-related complications. Further experimental validation is required to confirm efficacy and address potential development challenges.

Hydrophobic ion pairing as a novel approach to co-axial electrospraying of peptide-PLGA particles

Electrospraying is a processing technique that has gained much interest to prepare polymeric particles. The technique operates at ambient temperature, thereby avoiding heat induced degradation of labile therapeutics (e.g. peptides and proteins). Exposure to organic solvents can be minimised by co-axial electrospraying through separation of core (aqueous) and shell (organic) solvents. However, aqueous solutions are often difficult to electrospray due to high surface tension. Immiscibility between the core-shell solvents creates a further process challenge. Herein, we describe for the first time the use of hydrophobic ion pairing (HIP) to encapsulate a polypeptide into polymeric particles prepared by co-axial electrospraying. Peptide ion pairs were prepared to incorporate a model peptide - teriparatide - into an organic solvent, permitting facile electrospraying while also protecting the peptide from denaturation. Teriparatide loaded PLGA particles were generated by electrospraying from aqueous or ethanolic peptide solutions (core). A PLGA solution in chloroform (with and without co-solvents) was employed as the shell solution. The aqueous core solution led to a teriparatide encapsulation efficiency of 79.2 ± 19.8 %, which was not significantly different from the ethanolic core (57.1 ± 14.5 %). When aqueous solutions were used the process lacked reproducibility, resulting in low process yields (61.3 ± 4.0 %). In contrast, when an organic core was used a dry powder bed was achieved with a yield of 102.2 ± 8.8 %. The peptide's integrity and biological functionality were retained after electrospraying as ion pairs, as evidenced in a cell-based PTH1 receptor binding assay.

Extracellular Cold-Inducible RNA-Binding Protein and Hemorrhagic Shock: Mechanisms and Therapeutics

Hemorrhagic shock is a type of hypovolemic shock and a significant cause of trauma-related death worldwide. The innate immune system has been implicated as a key mediator in developing severe complications after shock. Inflammation from the innate immune system begins at the time of initial insult; however, its activation is exaggerated, resulting in early and late-stage complications. Hypoxia and hypoperfusion lead to the release of molecules that act as danger signals known as damage-associated molecular patterns (DAMPs). DAMPs continue to circulate after shock, resulting in excess inflammation and tissue damage. We recently discovered that cold-inducible RNA-binding protein released into the extracellular space acts as a DAMP. During hemorrhagic shock, hypoperfusion leads to cell necrosis and the release of CIRP into circulation, triggering both systemic inflammation and local tissue damage. In this review, we discuss extracellular cold-inducible RNA-binding protein (eCIRP)'s role in sterile inflammation, as well as its various mechanisms of action. We also share our more newly developed anti-eCIRP agents with the eventual goal of producing drug therapies to mitigate organ damage, reduce mortality, and improve patient outcomes related to hemorrhagic shock. Finally, we suggest that future preclinical studies are required to develop the listed therapeutics for hemorrhagic shock and related conditions. In addition, we emphasize on the challenges to the translational phase and caution that the therapy should allow the immune system to continue to function well against secondary infections during hospitalization.

Evaluation of Biologics ACE2/Ang(1-7) Encapsulated in Plant Cells for FDA Approval: Safety and Toxicology Studies

Background/Objectives: For several decades, protein drugs (biologics) made in cell cultures have been delivered as sterile injections, decreasing their affordability and patient preference. Angiotensin Converting Enzyme 2 (ACE2) gum is the first engineered human blood protein expressed in plant cells approved by the FDA without the need for purification and is a cold-chain and noninvasive drug delivery. This biologic is currently being evaluated in human clinical studies to debulk SARS-CoV-2 in the oral cavity to reduce coronavirus infection/transmission (NCT00543318). Methods: Chemistry, manufacturing, and control (CMC) studies for the ACE2/Ang(1-7) drug substances (DSs) and ACE2 gum drug product (DP) were conducted following USP guidelines. GLP-compliant toxicology studies were conducted on Sprague Dawley rats (n = 120; 15/sex/group) in four groups-placebo, low (1.6/1.0 mg), medium (3.2/2.0 mg), and high (8.3/5.0 mg) doses IP/kg/day. Oral gavage was performed twice daily for 14 days (the dosing phase) followed by the recovery phase (35 days). Plasma samples (n = 216) were analyzed for the product Ang(1-7) by ELISA. Results: The ACE2 protein was stable in the gum for at least up to 78 weeks. The toxicology study revealed the dose-related drug delivery to the plasma and increases in the AUC (56.6%) and Cmax (52.9%) after 28 high-dose gavages (95% C.I.), although this quantitation excludes exogenously delivered membrane-associated ACE2/Ang(1-7). Vital biomarkers and organs were not adversely affected despite the 10-fold higher absorption in the tissues, demonstrating the safety for the first in-human clinical trials of ACE2/Ang(1-7). The NOAEL observed in the rats was 2.5-7.5-fold higher than that of the anticipated efficacious therapeutic dose in humans for the treatment of cardiopulmonary disorders, and it was 314-fold higher than the NOAEL for topical delivery via chewing gum. Conclusions: This report lays the foundation for the regulatory process approval for noninvasive and affordable human biologic drugs bioencapsulated in plant cells.

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.

StaPep: An Open-Source Toolkit for Structure Prediction, Feature Extraction, and Rational Design of Hydrocarbon-Stapled Peptides

All-hydrocarbon stapled peptides, with their covalent side-chain constraints, provide enhanced proteolytic stability and membrane permeability, making them superior to linear peptides. However, tools for extracting structural and physicochemical descriptors to predict the properties of hydrocarbon-stapled peptides are lacking. To address this, we present StaPep, a Python-based toolkit for generating 3D structures and calculating 21 features for hydrocarbon-stapled peptides. StaPep supports peptides containing two non-standard amino acids (norleucine and 2-aminoisobutyric acid) and six non-natural anchoring residues (S3, S5, S8, R3, R5, and R8), with customization options for other non-standard amino acids. We showcase StaPep's utility through three case studies. The first generates 3D structures of these peptides with a mean RMSD of 1.62 ± 0.86, offering essential structural insights for drug design and biological activity prediction. The second develops machine learning models based on calculated molecular features to differentiate between membrane-permeable and non-permeable stapled peptides, achieving an AUC of 0.93. The third constructs regression models to predict the antimicrobial activity of stapled peptides against Escherichia coli, with a Pearson correlation of 0.84. StaPep's pipeline spans data retrieval, structure generation, feature calculation, and machine learning modeling for hydrocarbon-stapled peptides. The source codes and data set are freely available on Github: https://github.com/dahuilangda/stapep_package.

Access to β-Keto Amino Acid Derivatives via Interrupted Polonovski Strategy Involving NHC-Catalyzed Aza Benzoin Reaction

A general and practical route to the synthesis of β-keto amino acid derivatives from aldehydes and bench stable imine surrogates is presented. Following the interrupted Polonovski strategy, the imine formed in situ was trapped by the catalytically generated Breslow intermediate in an aza benzoin reaction. The present strategy has been extended to the formal synthesis of florfenicol and an intermediate en route to vancomycin. The functionalization of the synthesized β-keto amino acid derivatives highlights the practical applicability of the current methodology.

Extracellular Peptide-Ligand Dimerization Actuator Receptor Design for Reversible and Spatially Dosed 3D Cell-Material Communication

Transmembrane receptors that endow mammalian cells with the ability to sense and respond to biomaterial-bound ligands will prove instrumental in bridging the fields of synthetic biology and biomaterials. Materials formed with thiol-norbornene chemistry are amenable to thiol-peptide patterning, and this study reports the rational design of synthetic receptors that reversibly activate cellular responses based on peptide-ligand recognition. This transmembrane receptor platform, termed Extracellular Peptide-ligand Dimerization Actuator (EPDA), consists of stimulatory or inhibitory receptor pairs that come together upon extracellular peptide dimer binding with corresponding monobody receptors. Intracellularly, Stimulatory EPDAs phosphorylate a substrate that merges two protein halves, whereas Inhibitory EPDAs revert split proteins back to their unmerged, inactive state via substrate dephosphorylation. To identify ligand-receptor pairs, over 2000 candidate monobodies were built in silico using PETEI, a novel computational algorithm we developed. The top 30 monobodies based on predicted peptide binding affinity were tested experimentally, and monobodies that induced the highest change in protein merging (green fluorescent protein, GFP) were incorporated in the final EPDA receptor design. In soluble form, stimulatory peptides induce intracellular GFP merging in a time- and concentration-dependent manner, and varying levels of green fluorescence were observed based on stimulatory and inhibitory peptide-ligand dosing. EPDA-programmed cells encapsulated in thiol-norbornene hydrogels patterned with stimulatory and inhibitory domains exhibited 3D activation or deactivation based on their location within peptide-patterned hydrogels. EPDA receptors can recognize a myriad of peptide-ligands bound to 3D materials, can reversibly induce cellular responses beyond fluorescence, and are widely applicable in biological research and regenerative medicine.

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.

Giese-type alkylation of dehydroalanine derivatives via silane-mediated alkyl bromide activation

The rising popularity of bioconjugate therapeutics has led to growing interest in late-stage functionalization (LSF) of peptide scaffolds. α,β-Unsaturated amino acids like dehydroalanine (Dha) derivatives have emerged as particularly useful structures, as the electron-deficient olefin moiety can engage in late-stage functionalization reactions, like a Giese-type reaction. Cheap and widely available building blocks like organohalides can be converted into alkyl radicals by means of photoinduced silane-mediated halogen-atom transfer (XAT) to offer a mild and straightforward methodology of alkylation. In this research, we present a metal-free strategy for the photochemical alkylation of dehydroalanine derivatives. Upon abstraction of a hydride from tris(trimethylsilyl)silane (TTMS) by an excited benzophenone derivative, the formed silane radical can undergo a XAT with an alkyl bromide to generate an alkyl radical. Consequently, the alkyl radical undergoes a Giese-type reaction with the Dha derivative, forming a new C(sp3)-C(sp3) bond. The reaction can be performed in a phosphate-buffered saline (PBS) solution and shows post-functionalization prospects through pathways involving classical peptide chemistry.

Bioactive peptides from food science to pharmaceutical industries: Their mechanism of action, potential role in cancer treatment and available resources

Cancer is known as the main cause of mortality in the world, and every year, the rate of incidence and death due to cancer is increasing. Bioactive peptides are one of the novel therapeutic options that are considered a suitable alternative to toxic chemotherapy drugs because they limit side effects with their specific function. In fact, bioactive peptides are short amino acid sequences that obtain diverse physiological functions to maintain human health after being released from parent proteins. This group of biological molecules that can be isolated from different types of natural protein sources has attracted much attention in the field of pharmaceutical and functional foods production. The current article describes the therapeutic benefits of bioactive peptides and specifically and extensively reviews their role in cancer treatment, available sources for discovering anticancer peptides, mechanisms of action, production methods, and existing challenges.

Neuropeptide Y and Pain: Insights from Brain Research

Neuropeptide Y (NPY) is a highly conserved neuropeptide with widespread distribution in the central nervous system and diverse physiological functions. While extensively studied for its inhibitory effects on pain at the spinal cord level, its role in pain modulation within the brain remains less clear. This review aims to summarize the complex landscape of supraspinal NPY signaling in pain processing. We discuss the expression and function of NPY receptors in key pain-related brain regions, including the parabrachial nucleus, periaqueductal gray, amygdala, and nucleus accumbens. Additionally, we highlight the potent efficacy of NPY in attenuating pain sensitivity and nociceptive processing throughout the central nervous system. NPY-based therapeutic interventions targeting the central nervous system represent a promising avenue for novel analgesic strategies and pain-associated comorbidities.

A Reusable Polystyrene Support for Sustainable yet Cost-effective Octreotide Synthesis

The synthesis of peptide drugs has become facile with the use of supports that enable easy separation of the growing peptide. Peptide synthesis on insoluble supports typically employs excess reagents to enhance reaction efficiency and faces challenges during intramolecular cyclization. A non-crosslinked soluble polystyrene support is reported herein that improves cyclization efficiency on the support by using spacers. The support efficiency is illustrated by synthesizing octreotide drug in a scalable manner by on-support cyclization. The methodology drastically reduces the reagent waste, raw-material cost, and solvent requirement. The support can also be recovered and re-used up to 3 times making this a very sustainable method.

Synthesis of DNA-Encoded Macrocyclic Peptides via Visible-Light-Mediated Desulfurative C-C Bond Formation

DNA-encoded library (DEL) technology has been developed to serve as a practical platform for the discovery of biologically active macrocyclic peptide compounds. However, the cyclization of linear peptides has been widely regarded as the challenging step in the production of macrocyclic peptide DELs. Herein, we describe a novel DNA-compatible macrocyclization strategy, which enables the construction of ring systems via visible-light-mediated desulfurative C-C bond formation. The macrocyclization proceeds smoothly under mild conditions and in a good yield. Moreover, the reaction is compatible with a variety of linear substrates and can thus be employed to generate structurally diverse DNA-encoded macrocycles with various ring sizes.

Bioactive peptides and proteins for tissue repair: microenvironment modulation, rational delivery, and clinical potential

Bioactive peptides and proteins (BAPPs) are promising therapeutic agents for tissue repair with considerable advantages, including multifunctionality, specificity, biocompatibility, and biodegradability. However, the high complexity of tissue microenvironments and their inherent deficiencies such as short half-live and susceptibility to enzymatic degradation, adversely affect their therapeutic efficacy and clinical applications. Investigating the fundamental mechanisms by which BAPPs modulate the microenvironment and developing rational delivery strategies are essential for optimizing their administration in distinct tissue repairs and facilitating clinical translation. This review initially focuses on the mechanisms through which BAPPs influence the microenvironment for tissue repair via reactive oxygen species, blood and lymphatic vessels, immune cells, and repair cells. Then, a variety of delivery platforms, including scaffolds and hydrogels, electrospun fibers, surface coatings, assisted particles, nanotubes, two-dimensional nanomaterials, and nanoparticles engineered cells, are summarized to incorporate BAPPs for effective tissue repair, modification strategies aimed at enhancing loading efficiencies and release kinetics are also reviewed. Additionally, the delivery of BAPPs can be precisely regulated by endogenous stimuli (glucose, reactive oxygen species, enzymes, pH) or exogenous stimuli (ultrasound, heat, light, magnetic field, and electric field) to achieve on-demand release tailored for specific tissue repair needs. Furthermore, this review focuses on the clinical potential of BAPPs in facilitating tissue repair across various types, including bone, cartilage, intervertebral discs, muscle, tendons, periodontal tissues, skin, myocardium, nervous system (encompassing brain, spinal cord, and peripheral nerve), endometrium, as well as ear and ocular tissue. Finally, current challenges and prospects are discussed.

Peptides as modulators of FPPS enzyme: A multifaceted evaluation from the design to the mechanism of action

Bone diseases are medical conditions caused by the loss of bone homeostasis consecutive to increased osteoclast activity and diminished osteoblast activity. The mevalonate pathway (MVA) is crucial for maintaining this balance since it drives the post-translational prenylation of small guanosine triphosphatases (GTPases) proteins. Farnesyl pyrophosphate synthase (FPPS) plays a crucial role in the MVA pathway. Consequently, in the treatment of bone-related diseases, FPPS is the target of FDA-approved nitrogen-containing bisphosphonates (N-BPs), which have tropism mainly for bone tissue due to their poor penetration in soft tissues. The development of inhibitors targeting the FPPS enzyme has garnered significant interest in recent decades due to FPPS's role in the biosynthesis of cholesterol and other isoprenoids, which are implicated in cancer, bone diseases, and other conditions. In this study, we describe a multidisciplinary approach to designing novel FPPS inhibitors, combining computational modeling, biochemical assays, and biophysical techniques. A series of peptides and phosphopeptides were designed, synthesized, and evaluated for their ability to inhibit FPPS activity. Molecular docking was employed to predict the binding modes of these compounds to FPPS, while Surface Plasmon Resonance (SPR) and Nuclear Magnetic Resonance (NMR) spectroscopy experiments - based on Saturation Transfer Difference (STD) and an enzymatic NMR assay - were used to measure their binding affinities and kinetics. The biological activity of the most promising compounds was further assessed in cellular assays using murine colorectal cancer (CRC) cells. Additionally, genomics and metabolomics profiling allowed to unravel the possible mechanisms underlying the activity of the peptides, confirming their involvement in the modulation of the MVA pathway. Our findings demonstrate that the designed peptides and phosphopeptides exhibit significant inhibitory activity against FPPS and possess antiproliferative effects on CRC cells, suggesting their potential as therapeutic agents for cancer.

Selective delivery of G-quadruplex ligand in glioma cell lines: the power of cyclic-RGD peptide

Compounds targeting non-canonical secondary structures of nucleic acids, known as G-quadruplexes, are highly cytotoxic, both for cancer and healthy cells, because of their action mechanism's lack of appropriate selectivity. The targeted delivery of cytotoxic molecules to cancer cells is a valuable strategy to expand the repertoire of potential drugs, especially for cancer types for which new therapeutic tools are urgently needed, like glioblastoma. In this work, we conjugated a cyclic arginyl-glycyl-aspartic acid peptide to a naphthalene diimide, previously described as a highly performing stabilizing ligand for DNA G-quadruplexes, to specifically target glioma cells overexpressing RGD-binding integrin receptors. Our results, including confocal microscopy and cell toxicity assays, demonstrated improved efficacy and selective cellular absorption of the new conjugate without affecting the NDI's ability to interact with the G4 target.

Fatty Acid Derivatization and Cyclization of the Immunomodulatory Peptide RP-182 Targeting CD206high Macrophages Improve Antitumor Activity

As tumor-associated macrophages (TAM) exercise a plethora of protumor and immune evasive functions, novel strategies targeting TAMs to inhibit tumor progression have emerged within the current arena of cancer immunotherapy. Activation of the mannose receptor 1 (CD206) is a recent approach that recognizes immunosuppressive CD206high M2-like TAMs as a drug target. Ligation of CD206 both induces reprogramming of CD206high TAMs toward a proinflammatory phenotype and selectively triggers apoptosis in these cells. CD206-activating therapeutics are currently limited to the linear, 10mer peptide RP-182, 1, which is not a drug candidate. In this study, we sought to identify a better suitable candidate for future clinical development by synthesizing and evaluating a series of RP-182 analogs. Surprisingly, fatty acid derivative 1a [RP-182-PEG3-K(palmitic acid)] not only showed improved stability but also increased affinity to the CD206 receptor through enhanced interaction with a hydrophobic binding motif of CD206. Peptide 1a showed superior in vitro activity in cell-based assays of macrophage activation which was restricted to CD206high M2-polarized macrophages. Improvement in responses was disproportionally skewed toward improved induction of phagocytosis including cancer cell phagocytosis. Peptide 1a reprogrammed the immune landscape in genetically engineered murine KPC pancreatic tumors toward increased innate immune surveillance and improved tumor control and effectively suppressed tumor growth of murine B16 melanoma allografts.

Annealed fractional Lévy-Itō diffusion models for protein generation

Protein generation has numerous applications in designing therapeutic antibodies and creating new drugs. Still, it is a demanding task due to the inherent complexities of protein structures and the limitations of current generative models. Proteins possess intricate geometry, and sampling their conformational space is challenging due to its high dimensionality. This paper introduces novel Markovian and non-Markovian generative diffusion models based on fractional stochastic differential equations and the Lévy distribution, allowing for a more effective exploration of the conformational space. The approach is applied to a dataset of 40 , 000 proteins and evaluated in terms of Fréchet distance, fidelity, and diversity, outperforming the state-of-the-art by 25.4%, 35.8%, and 11.8%, respectively.

The limits of prediction: Why intrinsically disordered regions challenge our understanding of antimicrobial peptides

Antimicrobial peptides (AMPs) are molecules found in most organisms, playing a vital role in innate immune defense against pathogens. Their mechanism of action involves the disruption of bacterial cell membranes, causing leakage of cellular contents and ultimately leading to cell death. While AMPs typically lack a defined structure in solution, they often assume a defined conformation when interacting with bacterial membranes. Given this structural flexibility, we investigated whether intrinsically disordered regions (IDRs) with AMP-like properties could exhibit antimicrobial activity. We tested 14 peptides from different IDRs predicted to have antimicrobial activity and found that nearly all of them did not display the anticipated effects. These peptides failed to adopt a defined secondary structure and had compromised membrane interactions, resulting in a lack of antimicrobial activity. We hypothesize that evolutionary constraints may prevent IDRs from folding, even in membrane-like environments, limiting their antimicrobial potential. Moreover, our research reveals that current antimicrobial predictors fail to accurately capture the structural features of peptides when dealing with intrinsically unstructured sequences. Hence, the results presented here may have far-reaching implications for designing and improving antimicrobial strategies and therapies against infectious diseases.

A Thin Polymer Layer Enables Peptide-Polycation Complexes with Ultrahigh Efficient Encapsulation

A monolayer encapsulation is a new opportunity for engineering a system with high drug loading, but immobilizing polymer molecules on the surface of individual peptide nanoparticles is still an ongoing challenge. Herein, an individual peptide nanoparticle encapsulation strategy is proposed via surface adsorption, in which peptide molecules undergo granulation and subsequently aggregate with polymer molecules, forming a network via electrostatic interactions. Under the water phase, surplus polymer molecules dissolve, leading to a single nanoparticle encapsulation with a core-shell structure. As expected, the dense interfacial layer on the peptide nanoparticle surface achieves a superior loading degree of up to 95.4%. What's more, once the core-shell structure is established, the peptide mass fraction in individual encapsulation always exceeds 90% even under fierce external force. Following the individual nanoparticle encapsulation, the insulin-polycation complex (InsNp@PEI) reduces the inflammation from polymer and displays an effective glycemic control in type 1 diabetes. Overall, the newly developed single surface decoration encapsulates peptides with ultrahigh efficiency and opens up the possibility for further encapsulation.

Unraveling the hemolytic toxicity tapestry of peptides using chemical space complex networks

Peptides have emerged as promising therapeutic agents. However, their potential is hindered by hemotoxicity. Understanding the hemotoxicity of peptides is crucial for developing safe and effective peptide-based therapeutics. Here, we employed chemical space complex networks (CSNs) to unravel the hemotoxicity tapestry of peptides. CSNs are powerful tools for visualizing and analyzing the relationships between peptides based on their physicochemical properties and structural features. We constructed CSNs from the StarPepDB database, encompassing 2,004 hemolytic peptides, and explored the impact of seven different (dis)similarity measures on network topology and cluster (communities) distribution. Our findings revealed that each CSN extracts orthogonal information, enhancing the motif discovery and enrichment process. We identified 12 consensus hemolytic motifs, whose amino acid composition unveiled a high abundance of lysine, leucine, and valine residues, whereas aspartic acid, methionine, histidine, asparagine, and glutamine were depleted. Additionally, physicochemical properties were used to characterize clusters/communities of hemolytic peptides. To predict hemolytic activity directly from peptide sequences, we constructed multi-query similarity searching models, which outperformed cutting-edge machine learning-based models, demonstrating robust hemotoxicity prediction capabilities. Overall, this novel in silico approach uses complex network science as its central strategy to develop robust model classifiers, characterize the chemical space, and discover new motifs from hemolytic peptides. This will help to enhance the design/selection of peptides with potential therapeutic activity and low toxicity.

Deep quantification of substrate turnover defines protease subsite cooperativity

Substrate specificity determines protease functions in physiology and in clinical and biotechnological applications, yet quantitative cleavage information is often unavailable, biased, or limited to a small number of events. Here, we develop qPISA (quantitative Protease specificity Inference from Substrate Analysis) to study Dipeptidyl Peptidase Four (DPP4), a key regulator of blood glucose levels. We use mass spectrometry to quantify >40,000 peptides from a complex, commercially available peptide mixture. By analyzing changes in substrate levels quantitatively instead of focusing on qualitative product identification through a binary classifier, we can reveal cooperative interactions within DPP4's active pocket and derive a sequence motif that predicts activity quantitatively. qPISA distinguishes DPP4 from the related C. elegans DPF-3 (a DPP8/9-orthologue), and we relate the differences to the structural features of the two enzymes. We demonstrate that qPISA can direct protein engineering efforts like the stabilization of GLP-1, a key DPP4 substrate used in the treatment of diabetes and obesity. Thus, qPISA offers a versatile approach for profiling protease and especially exopeptidase specificity, facilitating insight into enzyme mechanisms and biotechnological and clinical applications.

Exploring Multivalency in the Development of Anti-PD-L1 Peptides for Cancer Immunotherapy

PURPOSE

The PD-1/PD-L1 pathway is one of the most effective immune checkpoint pathways utilized for cancer immunotherapy. Despite the success of anti-PD-1/PD-L1 mAbs, there is growing interest in developing low molecular weight anti-PD-1/PD-1 agents, such as peptides, because of their improved tumor penetration. We recently developed a small anti-PD-L1 peptide and demonstrated its promising anti-tumor activity. In this study, we investigate multivalency as a strategy to increase the binding avidity and blocking efficiency of the anti-PD-L1 peptide.

METHODS

Multivalent peptide inhibitors are designed with multiple copies of a peptide inhibitor in a single molecule. We synthesized peptides with different valences and examined their activity. We also investigated how spacer length affects the activity of these multivalent peptides.

RESULTS

Using this strategy, we developed a multivalent peptide that demonstrated approximately 40 times higher blocking efficiency and improved stability compared to the original peptide. Increasing the valency enhanced the peptide's specificity, which is essential for minimizing side effects.

CONCLUSIONS

Multivalency approach represents a promising platform for improving the efficacy of peptide-based checkpoint inhibitors.

New Insights into Bioactive Peptides: Design, Synthesis, Structure-Activity Relationship

In recent decades, peptides have attracted significant attention not only from Academia but also from big Pharma as novel potential therapeutic compounds [...].

Recent advances in liposomes and peptide-based therapeutics for glioblastoma treatment

In the context of glioblastoma treatment, the penetration of drugs is drastically limited by the blood-brain-barrier (BBB). Emerging therapies have focused on the field of therapeutic peptides for their excellent BBB targeting properties that promote a deep tumor penetration. Peptide-based strategies are also renowned for their abilities of driving cargo such as liposomal system allowing an active targeting of receptors overexpressed on GBM cells. This review provides a detailed description of the internalization mechanisms of specific GBM homing and penetrating peptides as well as the latest in vitro/in vivo studies of liposomes functionalized with them. The purpose of this review is to summarize a selection of promising pre-clinical results that demonstrate the advantages of this nanosystem, including an increase of tumor cell targeting, triggering drug accumulation and thus a strong antitumor effect. Aware of the early stage of these studies, many challenges need to be overcome to promote peptide-directed liposome at clinical level. In particular, the lack of suitable production, the difficulty to characterize the nanosystem and therapeutic competition leaded by antibodies.

Peptide-based therapeutics targeting genetic disorders

Genetic disorders (GDs) are challenging to treat owing to a lack of optimal treatment regimens and intricate and often difficult-to-understand underlying biological processes. Limited therapeutic approaches, which mostly provide symptomatic relief, are available. To date, a limited number of peptide-based drugs for the treatment of GDs are available, and several candidates are under clinical study. This review provides mechanistic insights into GDs and potential target areas where peptide-based drugs are beneficial. In addition, it emphasizes the usefulness of peptides as carriers for gene delivery, biomarkers for mutation detection and peptide-based vaccines for treating GDs.

Porous silicon and silica carriers for delivery of peptide therapeutics

Peptides have gained tremendous popularity as biological therapeutic agents in recent years due to their favourable specificity, diversity of targets, well-established screening methods, ease of production, and lower cost. However, their poor physiological and storage stability, pharmacokinetics, and fast clearance have limited their clinical translation. Novel nanocarrier-based strategies have shown promise in overcoming these issues. In this direction, porous silicon (pSi) and mesoporous silica nanoparticles (MSNs) have been widely explored as potential carriers for the delivery of peptide therapeutics. These materials possess several advantages, including large surface areas, tunable pore sizes, and adjustable pore architectures, which make them attractive carriers for peptide delivery systems. In this review, we cover pSi and MSNs as drug carriers focusing on their use in peptide delivery. The review provides a brief overview of their fabrication, surface modification, and interesting properties that make them ideal peptide drug carriers. The review provides a systematic account of various studies that have utilised these unique porous carriers for peptide delivery describing significant in vitro and in vivo results. We have also provided a critical comparison of the two carriers in terms of their physicochemical properties and short-term and long-term biocompatibility. Lastly, we have concluded the review with our opinion of this field and identified key areas for future research for clinical translation of pSi and MSN-based peptide therapeutic formulations.

Intragenic antimicrobial peptide Hs02 toxicity against leukemia cell lines is associated with increased expression of select pyroptotic components

The anticancer potential of some antimicrobial peptides has been reported. Hs02 is a recently characterized Intragenic Antimicrobial Peptide (IAP), which was able to exhibit potent antimicrobial and anti-inflammatory action. In this study, we evaluate for the first time the antineoplastic potential of the Hs02 IAP using cell lines representing the main types of leukemia as cancer models. Interestingly, this peptide decreased the viability of several leukemic cell lines, without compromising the viability of PBMCs in the same concentration. In the HL-60 line, treatment with Hs02 controlled cell division, leading to cell arrest in the G1 phase of the cell cycle. More importantly, HL-60 cells treated with Hs02 undergo cell death, with the formation of pores in the plasma membrane and the release of LDH. Accordingly, Hs02 treatment stimulated the expression of components involved in pyroptosis, such as NLRP1, CASP-1, GSDME, and IL-1β. Taken together, our data characterize the antineoplastic potential of Hs02 and open an opportunity for both evaluating the peptide's antineoplastic potential in other cancer models and using this molecule as a template for new peptides with therapeutic potential against cancer.

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.

In silico screening of protein-binding peptides with an application to developing peptide inhibitors against antibiotic resistance

The field of therapeutic peptides is experiencing a surge, fueled by their advantageous features. These include predictable metabolism, enhanced safety profile, high selectivity, and reduced off-target effects compared with small-molecule drugs. Despite progress in addressing limitations associated with peptide drugs, a significant bottleneck remains: the absence of a large-scale in silico screening method for a given protein target structure. Such methods have proven invaluable in accelerating small-molecule drug discovery. The high flexibility of peptide structures and the large diversity of peptide sequences greatly hinder the development of urgently needed computational methods. Here, we report a method called MDockPeP2_VS to address these challenges. It integrates molecular docking with structural conservation between protein folding and protein-peptide binding. Briefly, we discovered that when the interfacial residues are conserved, a sequence fragment derived from a monomeric protein exhibits a high propensity to bind a target protein with a similar conformation. This valuable insight significantly reduces the search space for peptide conformations, resulting in a substantial reduction in computational time and making in silico peptide screening practical. We applied MDockPeP2_VS to develop peptide inhibitors targeting the TEM-1 β-lactamase of Escherichia coli, a key mechanism behind antibiotic resistance in gram-negative bacteria. Among the top 10 peptides selected from in silico screening, TF7 (KTYLAQAAATG) showed significant inhibition of β-lactamase activity with a K i value of 1.37 ± 0.37 µM. This fully automated, large-scale structure-based in silico peptide screening software is available for free download at https://zougrouptoolkit.missouri.edu/mdockpep2_vs/download.html.

Therapeutic peptide development revolutionized: Harnessing the power of artificial intelligence for drug discovery

Due to the spread of antibiotic resistance, global attention is focused on its inhibition and the expansion of effective medicinal compounds. The novel functional properties of peptides have opened up new horizons in personalized medicine. With artificial intelligence methods combined with therapeutic peptide products, pharmaceuticals and biotechnology advance drug development rapidly and reduce costs. Short-chain peptides inhibit a wide range of pathogens and have great potential for targeting diseases. To address the challenges of synthesis and sustainability, artificial intelligence methods, namely machine learning, must be integrated into their production. Learning methods can use complicated computations to select the active and toxic compounds of the drug and its metabolic activity. Through this comprehensive review, we investigated the artificial intelligence method as a potential tool for finding peptide-based drugs and providing a more accurate analysis of peptides through the introduction of predictable databases for effective selection and development.

Advancing Therapeutic and Vaccine Proteins: Switching from Recombinant to Ribosomal Delivery-A Humanitarian Cause

Recombinant therapeutic and vaccine proteins have revolutionized healthcare, but there remain challenges, as many are awaiting development due to their slow development speed and high development cost. Cell-free in vivo ribosomes offer one choice, but they come with similar constraints. The validation of in vivo messenger RNA (mRNA) technology has been accomplished for COVID-19 vaccines. The bioreactors inside the body, the ribosomes, deliver these proteins at a small cost, since these are chemical products and do not require extensive analytical and regulatory exercises. In this study, we test and validate the final product. A smaller fraction of the recombinant protein cost is needed, removing both constraints. Although thousands of in vivo mRNA products are under development, their regulatory classification remains unresolved: do they qualify as chemical drugs, biological drug, or gene therapy items? These questions will soon be resolved. Additionally, how would the copies of approved in vivo mRNA protein products be brought in, and how would they be treated: as new drugs, generic drugs, or new biological drugs? Researchers are currently working to answer these questions. Regardless, these products' cost of goods (COGs) remains much smaller than that of ex vivo mRNA or recombinant products. This is necessary to meet the needs of the approximately 6.5 billion people around the world who do not have access to biological drugs; these products will indeed serve the dire needs of humanity. Given the minor cost of establishing the manufacturing of these products, it will also prove financially attractive to investors.

Unnatural Amino Acids: Strategies, Designs, and Applications in Medicinal Chemistry and Drug Discovery

Peptides can operate as therapeutic agents that sit within a privileged space between small molecules and larger biologics. Despite examples of their potential to regulate receptors and modulate disease pathways, the development of peptides with drug-like properties remains a challenge. In the quest to optimize physicochemical parameters and improve target selectivity, unnatural amino acids (UAAs) have emerged as critical tools in peptide- and peptidomimetic-based drugs. The utility of UAAs is illustrated by clinically approved drugs such as methyldopa, baclofen, and gabapentin in addition to small drug molecules, for example, bortezomib and sitagliptin. In this Perspective, we outline the strategy and deployment of UAAs in FDA-approved drugs and their targets. We further describe the modulation of the physicochemical properties in peptides using UAAs. Finally, we elucidate how these improved pharmacological parameters and the role played by UAAs impact the progress of analogs in preclinical stages with an emphasis on the role played by UAAs.

Tackling Undruggable Targets with Designer Peptidomimetics and Synthetic Biologics

The development of potent, specific, and pharmacologically viable chemical probes and therapeutics is a central focus of chemical biology and therapeutic development. However, a significant portion of predicted disease-causal proteins have proven resistant to targeting by traditional small molecule and biologic modalities. Many of these so-called "undruggable" targets feature extended, dynamic protein-protein and protein-nucleic acid interfaces that are central to their roles in normal and diseased signaling pathways. Here, we discuss the development of synthetically stabilized peptide and protein mimetics as an ever-expanding and powerful region of chemical space to tackle undruggable targets. These molecules aim to combine the synthetic tunability and pharmacologic properties typically associated with small molecules with the binding footprints, affinities and specificities of biologics. In this review, we discuss the historical and emerging platforms and approaches to design, screen, select and optimize synthetic "designer" peptidomimetics and synthetic biologics. We examine the inspiration and design of different classes of designer peptidomimetics: (i) macrocyclic peptides, (ii) side chain stabilized peptides, (iii) non-natural peptidomimetics, and (iv) synthetic proteomimetics, and notable examples of their application to challenging biomolecules. Finally, we summarize key learnings and remaining challenges for these molecules to become useful chemical probes and therapeutics for historically undruggable targets.

Multi-site esterification: a tunable, reversible strategy to tailor therapeutic peptides for delivery

Peptides are naturally potent and selective therapeutics with massive potential; however, low cell membrane permeability limits their clinical implementation, particularly for hydrophilic, anionic peptides with intracellular targets. To overcome this limitation, esterification of anionic carboxylic acids on therapeutic peptides can simultaneously increase hydrophobicity and net charge to facilitate cell internalization, whereafter installed esters can be cleaved hydrolytically to restore activity. To date, however, most esterified therapeutics contain either a single esterification site or multiple esters randomly incorporated on multiple sites. This investigation provides molecular engineering insight into how the number and position of esters installed onto the therapeutic peptide α carboxyl terminus 11 (αCT11, RPRPDDLEI) with 4 esterification sites affect hydrophobicity and the hydrolysis process that reverts the peptide to its original form. After installing methyl esters onto αCT11 using Fischer esterification, we isolated 5 distinct products and used 2D nuclear magnetic resonance spectroscopy, reverse-phase high performance liquid chromatography, and mass spectrometry to determine which residues were esterified in each and the resulting increase in hydrophobicity. We found esterifying the C-terminal isoleucine to impart the largest increase in hydrophobicity. Monitoring ester hydrolysis showed the C-terminal isoleucine ester to be the most hydrolytically stable, followed by the glutamic acid, whereas esters on aspartic acids hydrolyze rapidly. LC-MS revealed the formation of transient intramolecular aspartimides prior to hydrolysis to carboxylic acids. In vitro proof-of-concept experiments showed esterifying αCT11 to increase cell migration into a scratch, highlighting the potential of multi-site esterification as a tunable, reversible strategy to enable the delivery of therapeutic peptides.

Peptaloid: A Comprehensive Database for Exploring Peptide Alkaloid

Peptaloid is the first dedicated database for peptide alkaloid molecules, a unique class of naturally derived compounds known for their structural diversity and significant biological activities. Despite their promising potential in drug discovery and therapeutic development, research on peptide alkaloids has been limited by the absence of a comprehensive and centralized resource. Fragmented data across various sources have posed a significant challenge, underscoring the need for a specialized database to facilitate more efficient research and application. Peptaloid addresses this critical gap by providing a database with over 161,000 peptide alkaloid entries, each detailed with structural, physicochemical, and pharmacological properties. By leveraging advanced computational tools and machine learning, Peptaloid generates ADMET profiles, aiding in identifying and optimizing therapeutic candidates. Designed for versatility, the database supports various applications beyond drug discovery, including ecology and material sciences. Peptaloid (as a specialized database for peptide alkaloids) will play a crucial role in innovation and collaboration across scientific disciplines. Peptaloid is accessible at https://peptaloid.niser.ac.in.

Development of cell-free platforms for discovering, characterizing, and engineering post-translational modifications

Post-translational modifications (PTMs) are important for the stability and function of many therapeutic proteins and peptides. Current methods for studying and engineering PTM installing proteins often suffer from low-throughput experimental techniques. Here we describe a generalizable, in vitro workflow coupling cell-free protein synthesis (CFPS) with AlphaLISA for the rapid expression and testing of PTM installing proteins. We apply our workflow to two representative classes of peptide and protein therapeutics: ribosomally synthesized and post-translationally modified peptides (RiPPs) and conjugate vaccines. First, we demonstrate how our workflow can be used to characterize the binding activity of RiPP recognition elements, an important first step in RiPP biosynthesis, and be integrated into a biodiscovery pipeline for computationally predicted RiPP products. Then, we adapt our workflow to study and engineer oligosaccharyltransferases (OSTs) involved in conjugate vaccine production, enabling the identification of mutant OSTs and sites within a carrier protein that enable high efficiency production of conjugate vaccines. In total, we expect that our workflow will accelerate design-build-test cycles for engineering PTMs.

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.

Synthesis of Diazacyclic and Triazacyclic Small-Molecule Libraries Using Vicinal Chiral Diamines Generated from Modified Short Peptides and Their Application for Drug Discovery

Small-molecule probes are powerful tools for studying biological systems and can serve as lead compounds for developing new therapeutics. Especially, nitrogen heterocycles are of considerable importance in the pharmaceutical field. These compounds are found in numerous bioactive structures. Their synthesis often requires several steps or the use of functionalized starting materials. This review describes the use of vicinal diamines generated from modified short peptides to access substituted diaza- and triazacyclic compounds. Small-molecule diaza- and triazacyclic compounds with different substitution patterns and embedded in various molecular frameworks constitute important structure classes in the search for bioactivity. The compounds are designed to follow known drug likeness rules, including "Lipinski's Rule of Five". The screening of diazacyclic and traizacyclic libraries has shown the utility of these classes of compounds for the de novo identification of highly active compounds, including antimalarials, antimicrobial compounds, antifibrotic compounds, potent analgesics, and antitumor agents. Examples of the synthesis of diazacyclic and triazacyclic small-molecule libraries from vicinal chiral polyamines generated from modified short peptides and their application for the identification of highly active compounds are described.

Peptide-aware chemical language model successfully predicts membrane diffusion of cyclic peptides

Language modeling applied to biological data has significantly advanced the prediction of membrane penetration for small molecule drugs and natural peptides. However, accurately predicting membrane diffusion for peptides with pharmacologically relevant modifications remains a substantial challenge. Here, we introduce PeptideCLM, a peptide-focused chemical language model capable of encoding peptides with chemical modifications, unnatural or non-canonical amino acids, and cyclizations. We assess this model by predicting membrane diffusion of cyclic peptides, demonstrating greater predictive power than existing chemical language models. Our model is versatile and can be extended beyond membrane diffusion predictions to other target values. Its advantages include the ability to model macromolecules using chemical string notation, a largely unexplored domain, and a simple, flexible architecture that allows for adaptation to any peptide or other macromolecule dataset.

Bioorthogonal Chemistry: Enzyme Immune and Protein Capture for Enhanced LC-MS Bioanalysis

Immunocapture liquid chromatography-mass spectrometry (IC-LC-MS) bioanalysis has become an indispensable technique across various scientific disciplines, ranging from drug discovery to clinical diagnostics. While traditional immunocapture techniques have proven to be effective, they often encounter limitations in sensitivity, specificity, and compatibility with MS analysis. Chemoenzymatic immunocapture and protein capture (IPC) offers a promising solution, combining the high specificity of antibodies or proteins with the versatility of enzymatic and chemical modifications. This Review explores the foundational principles of chemoenzymatic IPC and examines various modification strategies including bioorthogonal click-chemistry, enzymatic-tagging, and HaloTag/CLIP-tag. Recent advancements in chemoenzymatic IPC techniques have significantly expanded their applicability to a diverse range of biomolecules including small molecules, peptides, RNAs, and proteins. This Review focuses on improvements in analytical performance achieved through these innovative approaches. Moreover, we discuss the broad applications of chemoenzymatic immunocapture in drug discovery, clinical diagnostics, and environmental analysis and explore its potential for future advancements in bioanalysis. We propose a novel solid-phase chemoenzymatic IPC assay (SCEIA) that effectively utilizes bioorthogonal click chemistry and chemoenzymatic approaches for efficient IPC and target analyte release. In summary, chemoenzymatic IPC represents a transformative paradigm shift in IC-LC-MS bioanalysis. By overcoming the limitations of traditional IPC techniques, this approach paves the way for more robust, sensitive, and versatile analytical workflows.

Peptide discovery across the spectrum of neuroinflammation; microglia and astrocyte phenotypical targeting, mediation, and mechanistic understanding

Uncontrolled and chronic inflammatory states in the Central Nervous System (CNS) are the hallmark of neurodegenerative pathology and every injury or stroke-related insult. The key mediators of these neuroinflammatory states are glial cells known as microglia, the resident immune cell at the core of the inflammatory event, and astroglia, which encapsulate inflammatory insults in proteoglycan-rich scar tissue. Since the majority of neuroinflammation is exclusively based on the responses of said glia, their phenotypes have been identified to be on an inflammatory spectrum encompassing developmental, homeostatic, and reparative behaviors as opposed to their ability to affect devastating cell death cascades and scar tissue formation. Recently, research groups have focused on peptide discovery to identify these phenotypes, find novel mechanisms, and mediate or re-engineer their actions. Peptides retain the diverse function of proteins but significantly reduce the activity dependence on delicate 3D structures. Several peptides targeting unique phenotypes of microglia and astroglia have been identified, along with several capable of mediating deleterious behaviors or promoting beneficial outcomes in the context of neuroinflammation. A comprehensive review of the peptides unique to microglia and astroglia will be provided along with their primary discovery methodologies, including top-down approaches using known biomolecules and naïve strategies using peptide and phage libraries.

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.

Nanoparticles as Delivery Systems for Antigenic Saccharides: From Conjugation Chemistry to Vaccine Design

Glycoconjugate vaccines have been effective in preventing numerous bacterial infectious diseases and have shown recent potential to treat cancers through active immunotherapy. Soluble polysaccharides elicit short-lasting immune responses and are usually covalently linked to immunogenic carrier proteins to enhance the antigen-specific immune response by stimulating T-cell-dependent mechanisms. Nonetheless, the conjugation of purified polysaccharides to carrier proteins complexifies vaccine production, and immunization with protein glycoconjugates can lead to the undesirable immunogenic interference of the carrier. Recently, the use of nanoparticles and nanoassemblies for the delivery of antigenic saccharides has gathered attention from the scientific community. Nanoparticles can be easily functionalized with a diversity of functionalities, including T-cell epitope, immunomodulator and synthetic saccharides, allowing for the modulation and polarization of the glycoantigen-specific immune response. Notably, the conjugation of glycan to nanoparticles protects the antigens from degradation and enhances their uptake by immune cells. Different types of nanoparticles, such as liposomes assembled from lipids, inorganic nanoparticles, virus-like particles and dendrimers, have been explored for glycovaccine design. The versatility of nanoparticles and their ability to induce robust immune responses make them attractive delivery platforms for antigenic saccharides. The present review aims at summarizing recent advancements in the use of nano-scaled systems for the delivery of synthetic glycoantigens. After briefly presenting the immunological mechanisms required to promote a robust immune response against antigenic saccharides, this review will offer an overview of the current trends in the nanoparticle-based delivery of glycoantigens.