bims-cepepe 2025-06-29 papers

bims-cepepe

Biomed News

on Cell-penetrating peptides

Issue of 2025–06–29
fourteen papers selected by
Henry Lamb, Queensland University of Technology

Screening macrocyclic peptide libraries by yeast display allows control of selection process and affinity ranking.
Tag-like cyclic peptides: Modular affinity elements for protein integration and bioengineering applications.
Chemoenzymatic synthesis and in vitro selection of de novo thiazole-containing macrocyclic peptides.
From Concepts to Inhibitors: A Blueprint for Targeting Protein-Protein Interactions.
De novo design of D-peptide ligands: Application to influenza virus hemagglutinin.
CPPpred-En: Ensemble framework integrating a protein language model and conventional features for highly accurate cell-penetrating peptide prediction.
Intranasal Therapeutics for Neurodegenerative Disorders: Overcoming the Blood-Brain Barrier with Smart Formulations and Devices.
De Novo Peptides That Induce the Liquid-Liquid Phase Separation of α-Synuclein.
Targeting fungal keratitis: In vivo efficacy of corneal-targeting and non-targeting peptides againstFusarium dimerum.
Innovative strategies for modeling peptide-protein interactions and rational peptide drug design.
Insertion of anthranilyl unit into inert amides: A facile route to oligoamides and cyclic peptides.
Design of peptide-based PAC1 antagonists combining molecular dynamics simulations and a biologically relevant cell-based assay.
Uncovering the Anti-Herpetic Activity of Anionic Peptides Derived From the Cytoplasmic Domain of Nectin-1.
Enhanced Protein-Protein Interaction Discovery via AlphaFold-Multimer.

Nat Commun. 2025 Jun 25. 16(1): 5367

Screening macrocyclic peptide libraries by yeast display allows control of selection process and affinity ranking.

Sara Linciano, Ylenia Mazzocato, Zhanna Romanyuk, Filippo Vascon, Lluc Farrera-Soler, Edward Will, Yuyu Xing, Shiyu Chen, Yoichi Kumada, Marta Simeoni, Alessandro Scarso, Laura Cendron, Christian Heinis, Alessandro Angelini.

Macrocyclic peptides represent an attractive drug modality due to their favourable properties and amenability to in vitro evolution techniques such as phage or mRNA display. Although very powerful, these technologies are not without limitations. In this work, we address some of their drawbacks by developing a yeast display-based strategy to generate, screen and characterise structurally diverse disulfide-cyclised peptides. The use of quantitative flow cytometry enables real-time monitoring of the screening of millions of individual macrocyclic peptides, leading to the identification of ligands with good binding properties to five different protein targets. X-ray analysis of a selected ligand in complex with its target reveals optimal shape complementarity and extensive surface interaction, explaining its exquisite affinity and selectivity. The yeast display-based approach described here offers a facile, quantitative and cost-effective alternative to rapidly and efficiently discover and characterise genetically encoded macrocyclic peptide ligands with sufficiently good binding properties against therapeutically relevant targets.

DOI: https://doi.org/10.1038/s41467-025-60907-x
Bioorg Med Chem. 2025 Jun 13. pii: S0968-0896(25)00224-X. [Epub ahead of print]128 118283

Tag-like cyclic peptides: Modular affinity elements for protein integration and bioengineering applications.

Zirui Zhu, Andrew Poweleit, Louisa Girard, Wenjun Sun, Haowei Ma, Edouard Nice.

  Cyclic peptides have emerged as highly versatile compounds in drug development and bioengineering, offering unique structural stability, binding specificity, and reduced susceptibility to proteolysis compared to their linear counterparts. These properties make cyclic peptides valuable in a range of therapeutic applications, from antimicrobial and anticancer agents to affinity tags in protein engineering. This review provides a comprehensive overview of cyclic peptide types, synthesis methods, and the latest advances in cyclic peptide-based therapeutics. Particular emphasis has been placed on "tag-like" cyclic peptides, which can function as affinity tags for enhancing the bioactivity and targeting capabilities of larger proteins. We explore various cyclization techniques, including disulfide bridging, metal-mediated linkers, and organic reagents, that facilitate the production of both monocyclic and bicyclic peptides with optimized pharmacokinetic and stability profiles. Recent advancements in display technologies, such as phage and mRNA display, further underscore the therapeutic potential of cyclic peptides, enabling rapid identification of candidates with high affinity and selectivity for a range of targets. This review discusses the potential of cyclic peptides as affinity tags that can be engineered onto proteins of interest, bridging the gap between small molecules and larger biologics, and explores future directions for their use in enhancing protein purification, detection, and interaction studies in protein engineering projects.

Keywords:  Affinity tags; Bioengineering applications; Cyclic peptides; Drug development; Protein engineering

DOI:  https://doi.org/10.1016/j.bmc.2025.118283
Chemistry. 2025 Jun 20. e202501355

Chemoenzymatic synthesis and in vitro selection of de novo thiazole-containing macrocyclic peptides.

Akihiro Saito, Hiroyuki Kimura, Hiroyasu Onaka, Hiroaki Suga, Yuki Goto.

  Backbone thiazole moieties prevail in bioactive peptidic natural products and play important roles in their biological functions. However, the de novo discovery of artificial thiazole-containing peptide ligands remains challenging. Here, we report an mRNA display-based selection platform for thiazole-containing macrocyclic peptides (ThzteMP), established through a dedicated posttranslational chemoenzymatic transformation. This method exploits the unique reactivity of ribosomally incorporated thioamides, enabling enzyme-free spontaneous heterocyclization to form thiazoline, which is further oxidized using the substrate-tolerant azoline dehydrogenase (GodE) to yield a thiazole moiety. By integrating this chemoenzymatic process with chloroacetyl-mediated thioether macrocyclization and mRNA display, we have successfully discovered thiazole-containing macrocyclic peptide ligands with high binding affinities against p-21 activated kinase 4 (PAK4). This study establishes a robust system to expedite ligand discovery of pseudo-natural peptides and to investigate the functional benefit of their backbone thiazoles.

Keywords:  RiPPs; enzymes; in vitro translation; mRNA display; peptidomimetics

DOI:  https://doi.org/10.1002/chem.202501355
Chem Rev. 2025 Jun 24.

From Concepts to Inhibitors: A Blueprint for Targeting Protein-Protein Interactions.

Seong Ho Hong, Thu Nguyen, Joseph F Ongkingco, Alex Nazzaro, Paramjit S Arora.

Protein-protein interactions are no longer considered undruggable because of the conceptual and technical advances that allow inhibitors to be generated using rational design principles and high-throughput screening methods. Here we review the concepts and approaches that have underpinned the progress in this field. We begin by assessing what makes a protein surface more tractable than others with a focus on the recent success in targeting Ras, which has long served as a poster child of a therapeutically important yet undruggable target. We discuss computational approaches to dissect protein surfaces to design macrocycles and miniprotein ligands. Traditional drug discovery has benefitted from leveraging natural products but this benefit has not extended to the design of ligands for protein surfaces because few natural products have been characterized as inhibitors of protein complexes. However, nature does provide a template in the form of binding epitopes of partner proteins. We review design of protein structure mimics that enable rational design of inhibitors through multiple weak contacts. Lastly, we focus on contemporary screening methods that are being merged with constrained peptides to offer unprecedented side chain diversity on conformationally defined scaffolds. We will focus on the concepts underlying advancements in the field rather than the application of these concepts and technologies that have led to inhibitors of specific interactions.

DOI: https://doi.org/10.1021/acs.chemrev.5c00046
Proc Natl Acad Sci U S A. 2025 Jul;122(26): e2426554122

De novo design of D-peptide ligands: Application to influenza virus hemagglutinin.

Jarek Juraszek, Rameshwar U Kadam, Davide Branduardi, Jeroen van Ameijde, Divita Garg, Nicolas Dailly, Mandy Jongeneelen, Jan Vermond, Just P J Brakenhoff, Boerries Brandenburg, Maria J P van Dongen, Ronald Vogels, Robert H E Friesen, Ian A Wilson.

  D-peptides hold great promise as therapeutics by alleviating the challenges of metabolic stability and immunogenicity in L-peptides. However, current D-peptide discovery methods are severely limited by specific size, structure, and the chemical synthesizability of their protein targets. Here, we describe a computational method for de novo design of D-peptides that bind to an epitope of interest on the target protein using Rosetta's hotspot-centric approach. The approach comprises identifying hotspot sidechains in a functional protein-protein interaction and grafting these side chains onto much smaller structured peptide scaffolds of opposite chirality. The approach enables more facile design of D-peptides and its applicability is demonstrated by design of D-peptidic binders of influenza A virus hemagglutinin, resulting in identification of multiple D-peptide lead series. The X-ray structure of one of the leads at 2.38 Å resolution verifies the validity of the approach. This method should be generally applicable to targets with detailed structural information, independent of molecular size, and accelerate development of stable, peptide-based therapeutics.

Keywords:  D-peptide; X-ray crystallography; computational design; hemagglutinin; influenza

DOI:  https://doi.org/10.1073/pnas.2426554122
Comput Biol Med. 2025 Jun 20. pii: S0010-4825(25)00941-2. [Epub ahead of print]195 110590

CPPpred-En: Ensemble framework integrating a protein language model and conventional features for highly accurate cell-penetrating peptide prediction.

Yong Eun Jang, Minjun Kwon, Seok Gi Kim, Nimisha Pradeep George, Ji Su Hwang, Shaherin Basith, Gwang Lee.

  Cell-penetrating peptides (CPPs) have gained significant attention for biomedical applications, including drug delivery and therapeutic development, due to their ability to penetrate cell membranes. The accurate prediction of CPPs is critical for accelerating the design and development of novel peptide-based therapies. Approaches for CPP prediction primarily depend on either peptide characteristic-based conventional features or one or two protein language models (PLMs), but these methods often fail to fully leverage the potential of combining diverse features. To address this limitation, we propose CPPpred-En, a prediction model that evaluates multiple conventional and PLM-based features across various machine learning classifiers, selects high-performing feature-classifier combinations, and integrates them through ensemble learning. The CPPpred-En model, which was trained on both the CPP924 and MLCPP 2.0 datasets, outperformed existing state-of-the-art predictors, achieving an accuracy (Acc) of 97.27 % and a matthews correlation coefficient (MCC) of 0.964 on the CPP924 dataset and an Acc of 96.10 % and an MCC of 0.707 on the MLCPP 2.0 dataset. The ensemble-based strategy demonstrated robustness across different datasets, highlighting the strong ability of the model to generalise. The combination of conventional and PLM features in an ensemble framework is promising approach for improving peptide-based therapeutics. The CPPpred-En model is a highly accurate and reliable tool for the identification of CPPs and their application in drug delivery and targeted therapy.

Keywords:  Bioinformatics; Cell penetrating peptide; Ensemble learning; Feature encoding; Machine learning; Peptide prediction; Protein language model

DOI:  https://doi.org/10.1016/j.compbiomed.2025.110590
Mol Pharm. 2025 Jun 23.

Intranasal Therapeutics for Neurodegenerative Disorders: Overcoming the Blood-Brain Barrier with Smart Formulations and Devices.

Siddhant Kumar, Akshay Yadav, Rahul K Verma, Akhilesh Kumar, Piyush Kumar Gupta, Rahul Shukla.

  Neurodegenerative diseases have always posed a significant therapeutic challenge due to the restrictive nature of the blood-brain barrier (BBB). Intranasal drug delivery has emerged as a noninvasive approach to bypass the BBB, enabling targeted brain drug delivery while improving drug retention and transport. This review explores the physiological basis of the nose-to-brain pathway and various formulation strategies including mucoadhesive systems, permeation enhancers, and magnetophoretic approaches. Additionally, strategies to enhance intranasal delivery, such as P-glycoprotein inhibitors, cell-penetrating peptides, and enzyme inhibitors, are discussed alongside nanotechnology-based carriers, including surface-modified and bioconjugated systems. The role of specialized intranasal drug delivery devices (e.g., ViaNase, Optimist, and SipNose) in enhancing precision dosing is also highlighted. Despite its promise, intranasal delivery faces challenges such as limited therapeutic windows, scalability issues, and the constraint of the nasal cavity volume, which can accommodate only 200 μL of liquid per nostril. Optimizing drug stability, achieving accurate dosing, and enhancing bioavailability without nasal irritation remain key hurdles. Future research should focus on the development of commercially feasible nanoformulations and innovative medical devices to improve drug targeting and treatment efficacy for patients with neurodegenerative diseases.

Keywords:  Bioconjugated Nanocarriers; Intranasal Devices; Mucoadhesive; Nanotechnology; Neurodegenerative Disorders; Nose-to-Brain Delivery; Stimuli-Responsive Gel

DOI:  https://doi.org/10.1021/acs.molpharmaceut.5c00386
J Am Chem Soc. 2025 Jun 25.

De Novo Peptides That Induce the Liquid-Liquid Phase Separation of α-Synuclein.

Tatsuya Ikenoue, Masatomo So, Naohiro Terasaka, Wei-En Huang, Yasushi Kawata, Yohei Miyanoiri, Kiyoto Kamagata, Hiroaki Suga.

Liquid-liquid phase separation (LLPS) of proteins can form membraneless organelles in the cell and can lead to pathological aggregation associated with neurodegenerative diseases. However, progress in controlling LLPS has been limited, and there has been no emergence of engineered de novo molecules to induce and modulate LLPS of targeted proteins. Here, we report de novo peptides that efficiently induce the LLPS of α-synuclein (αSyn), a protein involved in Parkinson's disease, discovered by the RaPID (random nonstandard peptides integrated discovery) system. These peptides primarily interact with the C-terminal region of αSyn, leading to the formation of an interaction network with αSyn and resulting in efficient droplet formation. Our study demonstrates the capacity of target-specific peptides to control LLPS and the subsequent liquid-solid phase transition (LSPT). Our novel LLPS-inducing and LSPT-modulating peptides may serve as a promising tool for fundamental investigations of LLPS and potentially for therapeutic intervention in amyloid diseases.

DOI: https://doi.org/10.1021/jacs.5c08019
Eur J Pharm Biopharm. 2025 Jun 17. pii: S0939-6411(25)00170-5. [Epub ahead of print] 114793

Targeting fungal keratitis: In vivo efficacy of corneal-targeting and non-targeting peptides againstFusarium dimerum.

Aditi Arora, Prasanjeet Kaur, Shikha Yadav, Priyanka P Srivastava, Shilpi Minocha, Sushmita G Shah, Archana Chugh.

  Fungal keratitis is a major contributor to monocular blindness, globally. This is because, application of conventional topical therapy yields poor outcomes owing to the poor penetration and fungistatic nature of these antifungal agents. Cell penetrating peptides (CPPs) with potent antifungal effect may provide a solution to address these challenges. In this study, the antifungal efficacy of two CPPs: a corneal-targeting peptide (CorTS 1) and a non-targeting peptide (Tat2) was evaluated. Both peptides effectively inhibited the growth of Fusarium dimerum hyphae by modulating membrane permeability in vitro. Additionally, these peptides demonstrated successful trans-epithelial penetration in rabbit eyes and exhibited superior therapeutic effects compared to commercially available natamycin ophthalmic suspension in mouse model of Fusarium keratitis. While Tat2 showed greater antifungal potency, its non-specific targeting and anti-inflammatory properties suggest its potential utility in early-stage fungal keratitis. In contrast, CorTS 1, with its corneal-targeting capability, may be more effective for treating late-stage deep stromal keratitis. These findings highlight the potential of biologically active CPPs as promising new therapies for fungal keratitis.

Keywords:  Cell penetrating peptides; Corneal infections; Fusarium keratitis; Natamycin

DOI:  https://doi.org/10.1016/j.ejpb.2025.114793
Curr Opin Struct Biol. 2025 Jun 25. pii: S0959-440X(25)00101-0. [Epub ahead of print]93 103083

Innovative strategies for modeling peptide-protein interactions and rational peptide drug design.

Lara Scharbert, Birgit Strodel.

This review highlights cutting-edge techniques for modeling peptide-protein interactions and advancing computer-aided peptide-drug design. We examine significant progress in generating peptide poses through docking and artificial intelligence (AI), assessing peptide flexibility via enhanced molecular dynamics simulations, and analyzing binding interactions through free energy calculations. Additionally, we discuss how these insights can inform the rational design of therapeutic peptides by utilizing free energy metrics and strategic modifications to enhance their binding affinity and therapeutic potential. Looking forward, further integrating AI will be crucial for optimizing peptide design and enhancing drug development efforts.

DOI: https://doi.org/10.1016/j.sbi.2025.103083
Sci Adv. 2025 Jun 27. 11(26): eadw0465

Insertion of anthranilyl unit into inert amides: A facile route to oligoamides and cyclic peptides.

Daoshun Wu, Kaili Xie, Yunfang Sun, Li Cao, Fang Liu, Xiaobo Sun, Kendall N Houk, Lei Wang.

Manipulation of polar functional groups to extend the druggability and developability space is an important approach in the current field of drug discovery. Here, we report an editing method that enables the direct insertion of anthranilyl units into inert amides to form versatile oligoamides and cyclic peptides under exceptionally mild reaction conditions. We showcase a diverse array of pharmaceuticals, natural products, and bioactive molecules involving the mentioned scaffold insertion. The synthesis of the secondary metabolites from marine-derived fungi, the expedited construction of bioactive molecules, and the assembly of functionalized peptide macrocycles through iterative insertions highlight the synthetic utility of this method. Computational tools and experimental measurements indicate that a hydrogen bond network formed by reacting and catalytic amide enables the insertion of the anthranilyl unit into a C─N bond.

DOI: https://doi.org/10.1126/sciadv.adw0465
bioRxiv. 2025 May 09. pii: 2025.04.16.649181. [Epub ahead of print]

Design of peptide-based PAC1 antagonists combining molecular dynamics simulations and a biologically relevant cell-based assay.

Wenqin Xu, Abigail M Keith, Wenjuan Ye, Xin Hu, Noel Southall, Juan J Marugan, Marc Ferrer, Mark J Henderson, Patrick M Sexton, Giuseppe Deganutti, Lee E Eiden.

The PACAP receptor PAC1 is a G s -coupled family B1 GPCR for which the highest-affinity endogenous peptide ligands are the pituitary adenylate cyclase-activating peptides PACAP38 and PACAP27, and whose most abundant endogenous ligand is PACAP38. PACAP action at PAC1 is implicated in neuropsychiatric disorders, atherosclerosis, pain chronification, and protection from neurodegeneration and ischemia. As PACAP also interacts with two related receptors, VPAC1 and VPAC2, highly selective ligands, both agonists and antagonists, for PAC1 have been sought. To date, the peptide PACAP(6-38) and polypeptide M65, which is related to maxadilan, a sandfly vasodilator peptide, have been identified as selective for PAC1. Several non-peptide small molecule compounds (SMOLs) have been reported to be specific antagonists at PAC1, albeit their specificities have not been rigorously documented. Here, we present a platform of cellular assays for the screening of biologically relevant antagonists at PAC1 and show that some currently proposed SMOL antagonists do not have activity in this cell reporter assay, while we confirm that PACAP(6-38) and M65 are competitive antagonists. We have used this assay system to explore other peptide antagonists at PAC1, guided by molecular dynamics analysis of the PACAP-PAC1 interaction based on cryo-EM structural models of PAC1 complexed with a number of biologically active ligands. The affinity-trap model for the PAC1-ligand interaction successfully predicts the engagement behavior of PACAP27 and PACAP38 peptide-based PAC1 inhibitors. In particular, C-terminal deletants of PACAP(6-38) that maintain equipotency to PACAP(6-38) allow the shorter sequence to function as a scaffold for further peptide-based antagonist exploration.

DOI: https://doi.org/10.1101/2025.04.16.649181
Bioinform Biol Insights. 2025 ;19 11779322251344130

Uncovering the Anti-Herpetic Activity of Anionic Peptides Derived From the Cytoplasmic Domain of Nectin-1.

Rakesh Rahangdale, Sumit Birangal, Gautham Shenoy, Fayaz Shaik Mohammad, Mukesh Pasupuleti, Raghu Chandrashekar Hariharapura.

  Nectin-1/herpes simplex virus glycoprotein D (HSV gD) interaction is crucial to drive herpes simplex virus (HSV) entry. Polyanions are known to show great potential as antivirals. Thus, we explored a peptide-based biotherapeutic approach and, for the first time, evaluated an anionic peptide derived from nectin-1 designed to bind HSV gD. Peptides enriched in acidic and basic residues were selected and computationally modeled using PEP-FOLD3, PROCHECK, ClusPro 2.0, and Desmond. Their antiviral efficacy was tested through virucidal, cell pretreatment, attachment inhibition, entry inhibition, and cytopathic effect (CPE) inhibition assays using a 10 TCID50 (Tissue Culture Infectious Dose 50%) viral dose. Among 4 designed peptides, C1 and C2 showed strong binding to HSV-1 and HSV-2 gD in molecular dynamic (MD) simulations. Peptide C1 exhibited significant virucidal activity (HSV-1: 64.92%, HSV-2: 67.16%), attachment inhibition (HSV-1: 62.03%, HSV-2: 59.38%), and host cell-entry inhibition (HSV-1: 71.37%, HSV-2: 76.28%) at 250 µg/mL concentration. Combination treatment with peptides C1 and C2 at a final concentration of 250 µg/mL (125 µg/mL each) exhibited an additive effect against HSV-1 (68.57%) and HSV-2 (73.37%) infections when tested by CPE inhibition assay. This highlights the potential of HSV gD-targeted anionic peptides for future anti-HSV therapeutics.

Keywords:  HSV gD; HSV-1 infection; HSV-2 infection; anionic peptide; antiviral peptide; nectin-1

DOI:  https://doi.org/10.1177/11779322251344130
bioRxiv. 2024 Feb 21. pii: 2024.02.19.580970. [Epub ahead of print]

Enhanced Protein-Protein Interaction Discovery via AlphaFold-Multimer.

Ah-Ram Kim, Yanhui Hu, Aram Comjean, Jonathan Rodiger, Stephanie E Mohr, Norbert Perrimon.

Accurately mapping protein-protein interactions (PPIs) is critical for elucidating cellular functions and has significant implications for health and disease. Conventional experimental approaches, while foundational, often fall short in capturing direct, dynamic interactions, especially those with transient or small interfaces. Our study leverages AlphaFold-Multimer (AFM) to re-evaluate high-confidence PPI datasets from Drosophila and human. Our analysis uncovers a significant limitation of the AFM-derived interface pTM (ipTM) metric, which, while reflective of structural integrity, can miss physiologically relevant interactions at small interfaces or within flexible regions. To bridge this gap, we introduce the Local Interaction Score (LIS), derived from AFM's Predicted Aligned Error (PAE), focusing on areas with low PAE values, indicative of the high confidence in interaction predictions. The LIS method demonstrates enhanced sensitivity in detecting PPIs, particularly among those that involve flexible and small interfaces. By applying LIS to large-scale Drosophila datasets, we enhance the detection of direct interactions. Moreover, we present FlyPredictome, an online platform that integrates our AFM-based predictions with additional information such as gene expression correlations and subcellular localization predictions. This study not only improves upon AFM's utility in PPI prediction but also highlights the potential of computational methods to complement and enhance experimental approaches in the identification of PPI networks.

DOI: https://doi.org/10.1101/2024.02.19.580970