bims-cepepe Biomed News
on Cell-penetrating peptides
Issue of 2025–03–30
thirteen papers selected by
Henry Lamb, Queensland University of Technology
  1. De novo discovery of a molecular glue-like macrocyclic peptide that induces MCL1 homodimerization.
  2. Intracellular redistribution of cell-penetrating peptide p28: A mechanism for enhanced anti-cancer activity.
  3. Main methods and tools for peptide development based on protein-protein interactions (PPIs).
  4. How Does an Anti-Cancer Peptide Passively Permeate the Plasma Membrane of a Cancer Cell and Not a Normal Cell?
  5. Cyclic peptide membrane permeability prediction using deep learning model based on molecular attention transformer.
  6. Predicting Distribution Coefficients (LogD) of Cyclic Peptides Using Molecular Dynamics Simulations.
  7. RoseTTAFold diffusion-guided short peptide design: a case study of binders against Keap1/Nrf2.
  8. Targeting Cancer With Bifunctional Peptides: Mechanism of Cell Entry and Inciting Cell Death.
  9. Peptidomimetics design and characterization: Bridging experimental and computer-based approaches.
  10. Antagonistic roles for MITF and TFE3 in melanoma plasticity.
  11. Rational Design Principles for De Novo α-Helical Peptide Barrels with Dynamic Conductive Channels.
  12. Recent advances in blood-brain barrier-on-a-chip models.
  13. Fatty Acid Metabolism Provides an Essential Survival Signal in OxPhos and BCR DLBCL Cells.
  1. Proc Natl Acad Sci U S A. 2025 Apr;122(13): e2426006122
    De novo discovery of a molecular glue-like macrocyclic peptide that induces MCL1 homodimerization.
    Fengwei Li, Mengmeng Zhang, Chao Liu, Jie Cheng, Yawen Yang, Xiangda Peng, Zhifeng Li, Wenfeng Cai, Haipeng Yu, Junjie Wu, Yuyu Guo, Hongkun Geng, Yun Fa, Youming Zhang, Dalei Wu, Yizhen Yin.
      Macrocyclic peptides have emerged as promising drug candidates, filling the gap between small molecules and large biomolecules in drug discovery. The antiapoptotic protein myeloid cell leukemia 1 (MCL1) is crucial for numerous cancers, yet it presents challenges for selective targeting by traditional inhibitors. In this study, we identified a macrocyclic peptide, 5L1, that strongly binds to MCL1, with a dissociation constant (KD) of 7.1 nM. This peptide shows the potential to specifically inhibit the function of MCL1, and demonstrates effective antitumor activity against several blood tumor cell lines with the half maximal inhibitory concentration (IC50) values for cell-penetrating peptide-conjugated 5L1 in the range of 0.6 to 3 μM. Structural analysis revealed that it functions similarly to molecular glue, capable of binding to two MCL1 molecules simultaneously and inducing their homodimerization. This unique mechanism of action distinguishes it from traditional small-molecule MCL1 inhibitors, underscoring the potential of macrocyclic peptides functioning as molecular glues. Moreover, it inspires the development of highly selective inhibitors targeting MCL1 and other related targets with this glue-like mechanism.
    Keywords:  MCL1; antitumor; macrocyclic peptide; molecular glue; specific inhibitor
    DOI:  https://doi.org/10.1073/pnas.2426006122
  2. J Control Release. 2025 Mar 24. pii: S0168-3659(25)00280-9. [Epub ahead of print] 113660
    Intracellular redistribution of cell-penetrating peptide p28: A mechanism for enhanced anti-cancer activity.
    Duy Binh Tran, Konstantin Christov, Sunam Mander, Albert Green, Anne Shilkaitis, Tapas K Das Gupta, Tohru Yamada.
      Cell-penetrating peptides (CPPs) have been studied as they provide an efficient strategy for the intracellular delivery of bioactive molecules in various biomedical applications such as cancer diagnosis and therapy. We have developed an anionic CPP, p28, that can preferentially enter cancer cells and induce cell cycle arrest and apoptotic cell death preclinically and that showed preliminary efficacy in humans. Yet, the underlying intracellular fate after cell entry remains largely uncharacterized. To better understand the intracellular trafficking of p28, we investigated more closely the role of endosomal acidification and retrograde transport in cancer cells. Here, we show that agents such as chloroquine (CQ), NH4Cl, and nordihydroguaiaretic acid (NDGA) that alter discrete steps of endocytosis or Golgi-mediated transport remarkably increased p28 access to the cytosol and nucleus. Moreover, CQ significantly improved the antiproliferative effects induced by p28. Our findings suggest that inadequate intracellular localization is the major limiting factor for the efficacy of CPPs such as p28. Taken together, these results indicate that the effective and adequate alternation of intracellular localization of CPPs can be a promising drug-delivery strategy to specifically deliver the therapeutic molecule to its intracellular therapeutic active site or organelle that leads to potentiate the efficacy for cancer diagnosis and therapy.
    Keywords:  Cell-penetrating peptides; Endosomal escape; cancer
    DOI:  https://doi.org/10.1016/j.jconrel.2025.113660
  3. Biochem Biophys Res Commun. 2025 Apr 12. pii: S0006-291X(25)00337-7. [Epub ahead of print]758 151623
    Main methods and tools for peptide development based on protein-protein interactions (PPIs).
    Javiera Baeza, Mauricio Bedoya, Pablo Cruz, Paola Ojeda, Francisco Adasme-Carreño, Oscar Cerda, Wendy González.
      Protein-protein interactions (PPIs) regulate essential physiological and pathological processes. Due to their large and shallow binding surfaces, PPIs are often considered challenging drug targets for small molecules. Peptides offer a viable alternative, as they can bind these targets, acting as regulators or mimicking interaction partners. This review focuses on competitive peptides, a class of orthosteric modulators that disrupt PPI formation. We provide a concise yet comprehensive overview of recent advancements in in-silico peptide design, highlighting computational strategies that have improved the efficiency and accuracy of PPI-targeting peptides. Additionally, we examine cutting-edge experimental methods for evaluating PPI-based peptides. By exploring the interplay between computational design and experimental validation, this review presents a structured framework for developing effective peptide therapeutics targeting PPIs in various diseases.
    Keywords:  Competitive peptides; In silico peptide design; In vitro peptide evaluation; Protein-protein interactions
    DOI:  https://doi.org/10.1016/j.bbrc.2025.151623
  4. J Phys Chem B. 2025 Mar 24.
    How Does an Anti-Cancer Peptide Passively Permeate the Plasma Membrane of a Cancer Cell and Not a Normal Cell?
    Alfredo E Cardenas, Ehud Neumann, Yang Sung Sohn, Taylor Hays, Rachel Nechushtai, Lauren J Webb, Ron Elber.
      Passive and targeted delivery of peptides to cells and organelles is a fundamental biophysical process controlled by membranes surrounding biological compartments. Embedded proteins, phospholipid composition, and solution conditions contribute to targeted transport. An anticancer peptide, NAF-144-67, permeates to cancer cells but not to normal cells. The mechanism of this selectivity is of significant interest. However, the complexity of biomembranes makes pinpointing passive targeting mechanisms difficult. To dissect contributions to selective transport by membrane components, we constructed simplified phospholipid vesicles as plasma membrane (PM) models of cancer and normal cells and investigated NAF-144-67 permeation computationally and experimentally. We use atomically detailed simulations with enhanced sampling techniques to study kinetics and thermodynamics of the interaction. Experimentally, we study the interaction of the peptide with large and giant unilamellar vesicles. The large vesicles were investigated with fluorescence spectroscopy and the giant vesicles with confocal microscopy. Peptide permeation across a model of cancer PM is more efficient than permeation across a PM model of normal cells. The investigations agree on the mechanism of selectivity, which consists of three steps: (i) early electrostatic attraction of the peptide to the negatively charged membrane, (ii) the penetration of the peptide hydrophobic N-terminal segment into the lipid bilayer, and (iii) exploiting short-range electrostatic forces to create a defect in the membrane and complete the permeation process. The first step is kinetically less efficient in a normal membrane with fewer negatively charged phospholipids. The model of a normal membrane is less receptive to defect creation in the third step.
    DOI:  https://doi.org/10.1021/acs.jpcb.5c00680
  5. Front Bioinform. 2025 ;5 1566174
    Cyclic peptide membrane permeability prediction using deep learning model based on molecular attention transformer.
    Dawei Jiang, Zixi Chen, Hongli Du.
      Membrane permeability is a critical bottleneck in the development of cyclic peptide drugs. Experimental membrane permeability testing is costly, and precise in silico prediction tools are scarce. In this study, we developed CPMP (https://github.com/panda1103/CPMP), a cyclic peptide membrane permeability prediction model based on the Molecular Attention Transformer (MAT) frame. The model demonstrated robust predictive performance, achieving determination coefficients (R 2 ) of 0.67 for PAMPA permeability prediction, and R 2 values of 0.75, 0.62, and 0.73 for Caco-2, RRCK, and MDCK cell permeability predictions, respectively. Its performance outperforms traditional machine learning methods and graph-based neural network models. In ablation experiments, we validated the effectiveness of each component in the MAT architecture. Additionally, we analyzed the impact of data pre-training and cyclic peptide conformation optimization on model performance.
    Keywords:  cyclic peptide; deep learning; membrane permeability; molecular attention transformer; pampa
    DOI:  https://doi.org/10.3389/fbinf.2025.1566174
  6. Pharm Res. 2025 Mar 26.
    Predicting Distribution Coefficients (LogD) of Cyclic Peptides Using Molecular Dynamics Simulations.
    Hao Lou, Mei Feng, Zahraa Al-Tamimi, Krzysztof Kuczera, Michael J Hageman.
       PURPOSE: The distribution coefficient (LogD) is a critical property for oral peptide drug design. In this study, we focused on cyclic peptides (octreotide and its analogs) and aimed to determine their LogD values at four pHs using both the simulation and experimental approaches.
    METHODS: For the experimental approach, the shake-flask method with LCMS quantification was employed to determine LogD values. For the simulation approach, the partition coefficient (LogP) was obtained from the solvation free energy calculations using molecular dynamics (MD) simulation. The LogD values were then calculated from the obtained LogP values considering the predicted pKa and ionization states of each peptide residue. More peptide properties such as polar surface area (PSA), number of intramolecular hydrogen bonds, solvent accessible surface area (SASA), and radius of gyration (Rg) were also calculated with the aid of MD simulation.
    RESULTS: For a total of 28 LogD values across four pHs, the predicted values from the simulation under the OPLS-AA forcefield agreed with the experimental values, with an average deviation of 1.39 ± 0.86 log units, displaying better predictions compared to the data generated under the CHARMM forcefield or using commercial software. In addition, the analysis of PSA, SASA, and Rg data suggested the peptides exhibited some conformational flexibility in both aqueous and organic phases.
    CONCLUSIONS: The method developed in this study can predict the LogD values at a wide pH range covering multiple formulation/physiological conditions and therefore can provide insights into designing oral peptide drugs, especially for early-stage projects.
    Keywords:  hydrophobicity; logD prediction; molecular dynamics simulation; oral peptide delivery; solvation free energy
    DOI:  https://doi.org/10.1007/s11095-025-03850-2
  7. Comput Struct Biotechnol J. 2025 ;27 896-911
    RoseTTAFold diffusion-guided short peptide design: a case study of binders against Keap1/Nrf2.
    Francesco Morena, Chiara Cencini, Carla Emiliani, Sabata Martino.
      In this study, we proposed a novel comprehensive computational framework that combines deep generative modeling with in silico peptide optimization to expedite the discovery of bioactive compounds. Our methodology utilizes RFdiffusion, a variation of the RoseTTAFold model for protein design, in tandem with ProteinMPNN, a deep neural network for protein sequence optimization, to provide short candidate peptides for targeted binding interactions. As a proof-of-concept, we focused on Keap1 (Kelch-like ECH-associated protein 1), a key regulator in the Keap1/Nrf2 antioxidant pathway. To achieve this, we designed peptide sequences that would interact with specific binding subpockets within its Kelch domain. We integrated machine learning models to forecast essential peptide properties, including toxicity, stability, and allergenicity, thus enhancing the selection of prospective candidates. Our in silico screening identified eight top candidates that exhibited strong binding affinity and good biophysical characteristics. The candidates underwent additional validation via comprehensive molecular dynamics simulations, which confirmed their strong binding contacts and structural stability over time. This integrated framework offers a scalable and adaptable platform for the rapid design of therapeutic peptides, merging breakthrough computational techniques with focused case studies. Furthermore, our modular methodology facilitates its straightforward adaptation to alternative protein targets, hence considerably enhancing its potential influence in drug development and discovery.
    Keywords:  Bioactive peptide design; Peptide molecular dynamics simulation; Peptide therapeutic potential; Peptides deep generative modeling
    DOI:  https://doi.org/10.1016/j.csbj.2025.02.032
  8. Cancer Sci. 2025 Mar 26.
    Targeting Cancer With Bifunctional Peptides: Mechanism of Cell Entry and Inciting Cell Death.
    Maria F Setiawan, Oliver Rudan, Ingo G H Schmidt-Wolf.
      Antimicrobial peptides have gained much attention in clinical research due to their extensive possibilities of application beyond antimicrobial use. The modification of antimicrobial peptides enables the peptides to target particular cancer cells, improving the specificity and efficiency of the treatment. In this study, TP2-D-Tox, a derivative of TP-D-Tox, demonstrated a superior anti-tumor activity towards renal carcinoma, Caki-2, and breast carcinoma, SK-BR-3. TP-Tox was previously reported to inhibit tumor growth in a mouse model, increasing the overall survival. TP- and TP2-D-Tox were shown to penetrate the cells via clathrin-mediated endocytosis, triggered by binding to the subunits of non-muscle myosin IIa and S100A9. HSPB1 was observed to have a protective effect towards TP2-D-Tox against the immediate proteolytic inactivation. The intracellular presence of the peptides evoked mitochondrial permeability transition, generation of reactive oxygen species, and formation of MLKL oligomers in the plasma membrane. Our investigation revealed that TP- and TP2-D-Tox induced a similar but distinctly regulated cell death in Caki-2 and SK-BR-3 cells. Both peptides established toxicity without activating any caspases, suggesting the possibility of TP- and TP2-D-Tox as a promising approach to bypass the caspase-dependent apoptosis-resistance issue impairing therapeutic responses of many cancer treatments.
    Keywords:  MLKL; NMIIA; bifunctional peptide; cancer; clathrin‐mediated endocytosis
    DOI:  https://doi.org/10.1111/cas.70065
  9. Prog Mol Biol Transl Sci. 2025 ;pii: S1877-1173(24)00151-0. [Epub ahead of print]212 279-327
    Peptidomimetics design and characterization: Bridging experimental and computer-based approaches.
    Alice Romagnoli, Jesmina Rexha, Nunzio Perta, Samuele Di Cristofano, Noemi Borgognoni, Gloria Venturini, Francesco Pignotti, Domenico Raimondo, Tiziana Borsello, Daniele Di Marino.
      Peptidomimetics, designed to mimic peptide biological activity with more drug-like properties, are increasingly pivotal in medicinal chemistry. They offer enhanced systemic delivery, cell penetration, target specificity, and protection against peptidases when compared to their native peptide counterparts. Already utilized in treating diverse diseases like neurodegenerative disorders, cancer and infectious diseases, their future in medicine seems bright, with many peptidomimetics in clinical trials or development stages. Peptidomimetics are well-suited for addressing disturbed protein-protein interactions (PPIs), which often underlie various pathologies. Structural biology and computational methods like molecular dynamics simulations facilitate rational design, whereas machine learning algorithms accelerate protein structure prediction, enabling efficient drug development. Experimental validation via various spectroscopic, biophysical, and biochemical assays confirms computational predictions and guides further optimization. Peptidomimetics, with their tailored constrained structures, represent a frontier in drug design focused on targeting PPIs. In this overview, we present a comprehensive landscape of peptidomimetics, encompassing perspectives on involvement in pathologies, chemical strategies, and methodologies for their characterization, spanning in silico, in vitro and in cell approaches. With increasing interest from pharmaceutical sectors, peptidomimetics hold promise for revolutionizing therapeutic approaches, marking a new era of precision drug discovery.
    Keywords:  Computational approaches; Drug design; PPI inhibitors; Peptide modifications; Peptide-based therapy; Peptidomimetics
    DOI:  https://doi.org/10.1016/bs.pmbts.2024.07.002
  10. Cell Rep. 2025 Mar 25. pii: S2211-1247(25)00245-1. [Epub ahead of print]44(4): 115474
    Antagonistic roles for MITF and TFE3 in melanoma plasticity.
    Jeremy Chang, Katelyn R Campbell-Hanson, Marion Vanneste, Nicholas I Bartschat, Ryan Nagel, Asdis K Arnadottir, Hong Nhung Vu, Collin Montgomery, Julius Yevdash, Jiarui Jiang, Ardith Bhinu, Annika Helverson, Michael D Henry, Eiríkur Steingrímsson, Ronald J Weigel, Robert A Cornell, Colin Kenny.
      Melanoma cells can switch from a melanocytic and proliferative state to a mesenchymal and invasive state and back again. This plasticity drives intratumoral heterogeneity, progression, and therapeutic resistance. Microphthalmia-associated transcription factor (MITF) promotes the melanocytic/proliferative phenotype, but factors that drive the mesenchymal/invasive phenotype and the mechanisms that effect the switch between cell states are unclear. Here, we identify the MITF paralog, TFE3, and the non-canonical mTORC1 pathway as regulators of the mesenchymal state. We show that TFE3 expression drives the metastatic phenotype in melanoma cell lines and tumors. Deletion of TFE3 in MITF-low melanoma cell lines suppresses their ability to migrate and metastasize. Further, MITF suppresses the mesenchymal phenotype by directly or indirectly activating expression of FNIP1, FNIP2, and FLCN, which encode components of the non-canonical mTORC1 pathway, thereby promoting cytoplasmic retention and lysosome-mediated degradation of TFE3. These findings highlight a molecular pathway controlling melanoma plasticity and invasiveness.
    Keywords:  CP: Cancer; CP: Genomics; MITF; TFE3; cell plasticity; mTORC1; melanoma; metastasis; phenotype switching; protein stability
    DOI:  https://doi.org/10.1016/j.celrep.2025.115474
  11. J Am Chem Soc. 2025 Mar 28.
    Rational Design Principles for De Novo α-Helical Peptide Barrels with Dynamic Conductive Channels.
    Ai Niitsu, Andrew R Thomson, Alistair J Scott, Jason T Sengel, Jaewoon Jung, Kozhinjampara R Mahendran, Mikiko Sodeoka, Hagan Bayley, Yuji Sugita, Derek N Woolfson, Mark I Wallace.
      Despite advances in peptide and protein design, the rational design of membrane-spanning peptides that form conducting channels remains challenging due to our imperfect understanding of the sequence-to-structure relationships that drive membrane insertion, assembly, and conductance. Here, we describe the design and computational and experimental characterization of a series of coiled coil-based peptides that form transmembrane α-helical barrels with conductive channels. Through a combination of rational and computational design, we obtain barrels with 5 to 7 helices, as characterized in detergent micelles. In lipid bilayers, these peptide assemblies exhibit two conductance states with relative populations dependent on the applied potential: (i) low-conductance states that correlate with variations in the designed amino-acid sequences and modeled coiled-coil barrel geometries, indicating stable transmembrane α-helical barrels; and (ii) high-conductance states in which single channels change size in discrete steps. Notably, the high-conductance states are similar for all peptides in contrast to the low-conductance states. This indicates the formation of large, dynamic channels, as observed in natural barrel-stave peptide channels. These findings establish rational routes to design and tune functional membrane-spanning peptide channels with specific conductance and geometry.
    DOI:  https://doi.org/10.1021/jacs.4c13933
  12. Acta Biomater. 2025 Mar 22. pii: S1742-7061(25)00214-4. [Epub ahead of print]
    Recent advances in blood-brain barrier-on-a-chip models.
    Johanna Vetter, Ilaria Palagi, Ari Waisman, Andreas Blaeser.
      The blood-brain barrier is a physiological barrier between the vascular system and the nervous system. Under healthy conditions, it restricts the passage of most biomolecules into the brain, making drug development exceedingly challenging. Conventional cell-based in vitro models provide valuable insights into certain features of the BBB. Nevertheless, these models often lack the three-dimensional structure and dynamic interactions of the surrounding microenvironment, which greatly influence cell functionality. Consequently, considerable efforts have been made to enhance in vitro models for drug development and disease research. Recently, microfluidic organ-on-a-chip systems have emerged as promising candidates to better mimic the dynamic nature of the BBB. This review provides a comprehensive overview of recent BBB-on-chip devices. The typical building blocks, chip designs, the perfusion infrastructure, and readouts used to characterize and evaluate BBB formation are presented, analyzed, and discussed in detail. STATEMENT OF SIGNIFICANCE: The blood-brain barrier (BBB) is a highly selective barrier that controls what can enter the brain. While it protects the brain from harmful substances, it also hinders the delivery of treatments for neurological diseases such as Alzheimer's and Parkinson's. Due to its complexity, studying the BBB in living organisms remains difficult. However, recent advances in "organ-on-a-chip" technology have allowed scientists to create small, engineered models that replicate the BBB. These models provide a powerful platform to study diseases and test potential drugs with greater accuracy than traditional methods. Organ-on-a-chip devices are designed to mimic the behavior of organs or tissues in the human body, offering a more realistic and controlled environment for research. This review highlights recent breakthroughs in BBB-on-a-chip technology, showing how these models enhance current research and have the potential to transform the way we study brain diseases and develop new drugs. By integrating biology and engineering, BBB-on-a-chip technology has the potential to transform neuroscience research, improve drug development, and enhance our understanding of brain disorders.
    Keywords:  Biofabrication; Blood-brain barrier; Organ-on-a-chip; Permeability; Self-assembly; TEER; Vascularization; Vessel
    DOI:  https://doi.org/10.1016/j.actbio.2025.03.041
  13. Biomedicines. 2025 Mar 13. pii: 707. [Epub ahead of print]13(3):
    Fatty Acid Metabolism Provides an Essential Survival Signal in OxPhos and BCR DLBCL Cells.
    Aurélie Montagne, Konstantina Kotta, Karoline Kielbassa-Elkadi, Isabelle Martins, José Ángel Martinez-Climent, Guido Kroemer, Catherine Thieblemont, Véronique Baud.
      Backgroung/objectives: Diffuse large B-cell lymphoma (DLBCL) is the most frequent subtype of malignant lymphoma and is a heterogeneous disease with various gene and chromosomal abnormalities. The development of novel therapeutic treatments has improved DLBCL prognosis, but patients with early relapse or refractory disease have a poor outcome (with a mortality of around 40%). Metabolic reprogramming is a hallmark of cancer cells. Fatty acid (FA) metabolism is frequently altered in cancer cells and recently emerged as a critical survival path for cancer cell survival. Methods: We first performed the metabolic characterization of an extended panel of DLBCL cell lines, including lipid droplet content. Then, we investigated the effect of drugs targeting FA metabolism on DLBCL cell survival. Further, we studied how the combination of drugs targeting FA and either mitochondrial metabolism or mTOR pathway impacts on DLBCL cell death. Results: Here, we reveal, using a large panel of DLBCL cell lines characterized by their metabolic status, that targeting of FA metabolism induces massive DLBCL cell death regardless of their OxPhos or BCR/glycolytic subtype. Further, FA drives resistance of DLBCL cell death induced by mitochondrial stress upon treatment with either metformin or L-asparaginase, two FDA-approved antimetabolic drugs. Interestingly, combining inhibition of FA metabolism with that of the mTOR oncogenic pathway strongly potentiates DLBCL cell death. Conclusion: Altogether, our data highlight the central role played by FA metabolism in DLBCL cell survival, independently of their metabolic subtype, and provide the framework for the use of drugs targeting this metabolic vulnerability to overcome resistance in DLBCL patients.
    Keywords:  B-cell lymphoma; DLBCL; fatty acid; metabolism; mitochondrial stress; survival
    DOI:  https://doi.org/10.3390/biomedicines13030707
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