bims-cepepe 2023-12-03 papers

bims-cepepe

Biomed News

on Cell-penetrating peptides

Issue of 2023–12–03
nine papers selected by
Henry Lamb, Queensland University of Technology

A library-derived peptide inhibitor of the BZLF1 transcription factor.
De novo Design of Peptides that Bind Specific Conformers of α-Synuclein.
Stitched peptides as potential cell permeable inhibitors of oncogenic DAXX protein.
Structure-function and rational design of a spider toxin Ssp1a at human voltage-gated sodium channel subtypes.
PepCNN deep learning tool for predicting peptide binding residues in proteins using sequence, structural, and language model features.
Lipidization as a tool toward peptide therapeutics.
In silico evolution of autoinhibitory domains for a PD-L1 antagonist using deep learning models.
Bioinformatics-guided discovery of biaryl-linked lasso peptides.
Human iPSC-derived renal collecting duct organoid model cystogenesis in ADPKD.

J Pept Sci. 2023 Dec 02. e3557

A library-derived peptide inhibitor of the BZLF1 transcription factor.

Sarah K Madden, Andrew Brennan, Jody M Mason.

  Transcription factor dysregulation is associated with many diseases, including cancer. Peptide-based molecules are increasingly recognised as important modulators of difficult intracellular protein-protein interaction targets, with peptide library screening consequently proven to be a viable strategy in developing inhibitors against a wide range of transcription factors (TFs). However, current strategies simply select the highest affinity of binding to a target TF rather than the ability to inhibit TF function. Here, we utilise our Transcription Block Survival (TBS) screening platform to enable high-throughput identification of peptides that inhibit TFs from binding to cognate DNA sites, hence inhibiting functionality. In this study, we explore whether the TBS can be expanded to derive a potent and functional peptide inhibitor of the BZLF1 transcription factor. The library-derived peptide, AcidicW, is shown to form a more stable dimer with BZLF1 than the BZLF1 homodimer, with a thermal denaturation temperature exceeding 80°C. AcidicW can also functionally inhibit the BZLF1:TRE DNA interaction with high potency and an IC50 of 612 nM.

Keywords:  BZLF1; PCA; ZEBRA; peptide antagonists; peptide screening; transcription factor

DOI:  https://doi.org/10.1002/psc.3557
bioRxiv. 2023 Nov 16. pii: 2023.11.14.567090. [Epub ahead of print]

De novo Design of Peptides that Bind Specific Conformers of α-Synuclein.

Hailey M Wallace, Hyunjun Yang, Sophia Tan, Henry S Pan, Rose Yang, Junyi Xu, Hyunil Jo, Carlo Condello, Nicholas F Polizzi, William F DeGrado.

Insoluble amyloids rich in cross-β fibrils are observed in a number of neurodegenerative diseases. Depending on the clinicopathology, the amyloids can adopt distinct supramolecular assemblies, termed conformational strains. However, rapid methods to study amyloid in a conformationally specific manner are lacking. We introduce a novel computational method for de novo design of peptides that tile the surface of α-synuclein fibrils in a conformationally specific manner. Our method begins by identifying surfaces that are unique to the conformational strain of interest, which becomes a "target backbone" for the design of a peptide binder. Next, we interrogate structures in the PDB database with high geometric complementarity to the target. Then, we identify secondary structural motifs that interact with this target backbone in a favorable, highly occurring geometry. This method produces monomeric helical motifs with a favorable geometry for interaction with the strands of the underlying amyloid. Each motif is then symmetrically replicated to form a monolayer that tiles the amyloid surface. Finally, amino acid sequences of the peptide binders are computed to provide a sequence with high geometric and physicochemical complementarity to the target amyloid. This method was applied to a conformational strain of α-synuclein fibrils, resulting in a peptide with high specificity for the target relative to other amyloids formed by α-synuclein, tau, or Aβ40. This designed peptide also markedly slowed the formation of α-synuclein amyloids. Overall, this method offers a new tool for examining conformational strains of amyloid proteins.

DOI: https://doi.org/10.1101/2023.11.14.567090
RSC Chem Biol. 2023 Nov 29. 4(12): 1096-1110

Stitched peptides as potential cell permeable inhibitors of oncogenic DAXX protein.

Clare Jelinska, Srinivasaraghavan Kannan, Yuri Frosi, Siti Radhiah Ramlan, Fernaldo Winnerdy, Rajamani Lakshminarayanan, Charles W Johannes, Christopher J Brown, Anh-Tuan Phan, Daniela Rhodes, Chandra S Verma.

DAXX (Death Domain Associated Protein 6) is frequently upregulated in various common cancers, and its suppression has been linked to reduced tumor progression. Consequently, DAXX has gained significant interest as a therapeutic target in such cancers. DAXX is known to function in several critical biological pathways including chromatin remodelling, transcription regulation, and DNA repair. Leveraging structural information, we have designed and developed a novel set of stapled/stitched peptides that specifically target a surface on the N-terminal helical bundle domain of DAXX. This surface serves as the anchor point for binding to multiple interaction partners, such as Rassf1C, p53, Mdm2, and ATRX, as well as for the auto-regulation of the DAXX N-terminal SUMO interaction motif (SIM). Our experiments demonstrate that these peptides effectively bind to and inhibit DAXX with a higher affinity than the known interaction partners. Furthermore, these peptides release the auto-inhibited SIM, enabling it to interact with SUMO-1. Importantly, we have developed stitched peptides that can enter cells, maintaining their intracellular concentrations at nanomolar levels even after 24 hours, without causing any membrane perturbation. Collectively, our findings suggest that these stitched peptides not only serve as valuable tools for probing the molecular interactions of DAXX but also hold potential as precursors to the development of therapeutic interventions.

DOI: https://doi.org/10.1039/d3cb00149k
Front Pharmacol. 2023 ;14 1277143

Structure-function and rational design of a spider toxin Ssp1a at human voltage-gated sodium channel subtypes.

Yashad Dongol, David T Wilson, Norelle L Daly, Fernanda C Cardoso, Richard J Lewis.

  The structure-function and optimization studies of NaV-inhibiting spider toxins have focused on developing selective inhibitors for peripheral pain-sensing NaV1.7. With several NaV subtypes emerging as potential therapeutic targets, structure-function analysis of NaV-inhibiting spider toxins at such subtypes is warranted. Using the recently discovered spider toxin Ssp1a, this study extends the structure-function relationships of NaV-inhibiting spider toxins beyond NaV1.7 to include the epilepsy target NaV1.2 and the pain target NaV1.3. Based on these results and docking studies, we designed analogues for improved potency and/or subtype-selectivity, with S7R-E18K-rSsp1a and N14D-P27R-rSsp1a identified as promising leads. S7R-E18K-rSsp1a increased the rSsp1a potency at these three NaV subtypes, especially at NaV1.3 (∼10-fold), while N14D-P27R-rSsp1a enhanced NaV1.2/1.7 selectivity over NaV1.3. This study highlights the challenge of developing subtype-selective spider toxin inhibitors across multiple NaV subtypes that might offer a more effective therapeutic approach. The findings of this study provide a basis for further rational design of Ssp1a and related NaSpTx1 homologs targeting NaV1.2, NaV1.3 and/or NaV1.7 as research tools and therapeutic leads.

Keywords:  ICK toxins; Ssp1a; rational design; spider toxin; structure-function; voltage-gated sodium channels

DOI:  https://doi.org/10.3389/fphar.2023.1277143
Sci Rep. 2023 Nov 28. 13(1): 20882

PepCNN deep learning tool for predicting peptide binding residues in proteins using sequence, structural, and language model features.

Abel Chandra, Alok Sharma, Iman Dehzangi, Tatsuhiko Tsunoda, Abdul Sattar.

Protein-peptide interactions play a crucial role in various cellular processes and are implicated in abnormal cellular behaviors leading to diseases such as cancer. Therefore, understanding these interactions is vital for both functional genomics and drug discovery efforts. Despite a significant increase in the availability of protein-peptide complexes, experimental methods for studying these interactions remain laborious, time-consuming, and expensive. Computational methods offer a complementary approach but often fall short in terms of prediction accuracy. To address these challenges, we introduce PepCNN, a deep learning-based prediction model that incorporates structural and sequence-based information from primary protein sequences. By utilizing a combination of half-sphere exposure, position specific scoring matrices from multiple-sequence alignment tool, and embedding from a pre-trained protein language model, PepCNN outperforms state-of-the-art methods in terms of specificity, precision, and AUC. The PepCNN software and datasets are publicly available at https://github.com/abelavit/PepCNN.git .

DOI: https://doi.org/10.1038/s41598-023-47624-5
Drug Deliv. 2023 Dec;30(1): 2284685

Lipidization as a tool toward peptide therapeutics.

Aneta Myšková, David Sýkora, Jaroslav Kuneš, Lenka Maletínská.

  Peptides, as potential therapeutics continue to gain importance in the search for active substances for the treatment of numerous human diseases, some of which are, to this day, incurable. As potential therapeutic drugs, peptides have many favorable chemical and pharmacological properties, starting with their great diversity, through their high affinity for binding to all sort of natural receptors, and ending with the various pathways of their breakdown, which produces nothing but amino acids that are nontoxic to the body. Despite these and other advantages, however, they also have their pitfalls. One of these disadvantages is the very low stability of natural peptides. They have a short half-life and tend to be cleared from the organism very quickly. Their instability in the gastrointestinal tract, makes it impossible to administer peptidic drugs orally. To achieve the best pharmacologic effect, it is desirable to look for ways of modifying peptides that enable the use of these substances as pharmaceuticals. There are many ways to modify peptides. Herein we summarize the approaches that are currently in use, including lipidization, PEGylation, glycosylation and others, focusing on lipidization. We describe how individual types of lipidization are achieved and describe their advantages and drawbacks. Peptide modifications are performed with the goal of reaching a longer half-life, reducing immunogenicity and improving bioavailability. In the case of neuropeptides, lipidization aids their activity in the central nervous system after the peripheral administration. At the end of our review, we summarize all lipidized peptide-based drugs that are currently on the market.

Keywords:  Peptide therapeutics; lipidization; structure modification; therapeutic lipopeptides

DOI:  https://doi.org/10.1080/10717544.2023.2284685
Proc Natl Acad Sci U S A. 2023 Dec 05. 120(49): e2307371120

In silico evolution of autoinhibitory domains for a PD-L1 antagonist using deep learning models.

Odessa J Goudy, Amrita Nallathambi, Tomoaki Kinjo, Nicholas Z Randolph, Brian Kuhlman.

  There has been considerable progress in the development of computational methods for designing protein-protein interactions, but engineering high-affinity binders without extensive screening and maturation remains challenging. Here, we test a protein design pipeline that uses iterative rounds of deep learning (DL)-based structure prediction (AlphaFold2) and sequence optimization (ProteinMPNN) to design autoinhibitory domains (AiDs) for a PD-L1 antagonist. With the goal of creating an anticancer agent that is inactive until reaching the tumor environment, we sought to create autoinhibited (or masked) forms of the PD-L1 antagonist that can be unmasked by tumor-enriched proteases. Twenty-three de novo designed AiDs, varying in length and topology, were fused to the antagonist with a protease-sensitive linker, and binding to PD-L1 was measured with and without protease treatment. Nine of the fusion proteins demonstrated conditional binding to PD-L1, and the top-performing AiDs were selected for further characterization as single-domain proteins. Without any experimental affinity maturation, four of the AiDs bind to the PD-L1 antagonist with equilibrium dissociation constants (KDs) below 150 nM, with the lowest KD equal to 0.9 nM. Our study demonstrates that DL-based protein modeling can be used to rapidly generate high-affinity protein binders.

Keywords:  PD-L1; computational protein design; de novo protein design; deep learning; protein–protein interactions

DOI:  https://doi.org/10.1073/pnas.2307371120
Chem Sci. 2023 Nov 22. 14(45): 13176-13183

Bioinformatics-guided discovery of biaryl-linked lasso peptides.

Hamada Saad, Thomas Majer, Keshab Bhattarai, Sarah Lampe, Dinh T Nguyen, Markus Kramer, Jan Straetener, Heike Brötz-Oesterhelt, Douglas A Mitchell, Harald Gross.

Lasso peptides are a class of ribosomally synthesized and post-translationally modified peptides (RiPPs) that feature an isopeptide bond and a distinct lariat fold. A growing number of secondary modifications have been described that further decorate lasso peptide scaffolds. Using genome mining, we have discovered a pair of lasso peptide biosynthetic gene clusters (BGCs) that include cytochrome P450 genes. Using mass spectrometry, stable isotope incorporation, and extensive 2D-NMR spectrometry, we report the structural characterization of two unique examples of (C-N) biaryl-linked lasso peptides. Nocapeptin A, from Nocardia terpenica, is tailored with a Trp-Tyr crosslink, while longipepetin A, from Longimycelium tulufanense, features a Trp-Trp linkage. Besides the unusual bicyclic frame, a Met of longipepetin A undergoes S-methylation to yield a trivalent sulfonium, a heretofore unprecedented RiPP modification. A bioinformatic survey revealed additional lasso peptide BGCs containing P450 enzymes which await future characterization. Lastly, nocapeptin A bioactivity was assessed against a panel of human and bacterial cell lines with modest growth-suppression activity detected towards Micrococcus luteus.

DOI: https://doi.org/10.1039/d3sc02380j
Cell Rep. 2023 Nov 10. pii: S2211-1247(23)01443-2. [Epub ahead of print] 113431

Human iPSC-derived renal collecting duct organoid model cystogenesis in ADPKD.

Shin-Ichi Mae, Fumihiko Hattanda, Hiroyoshi Morita, Aya Nozaki, Naoko Katagiri, Hanako Ogawa, Kaori Teranaka, Yu Nishimura, Aoi Kudoh, Sanae Yamanaka, Kyoko Matsuse, Makoto Ryosaka, Akira Watanabe, Tomoyoshi Soga, Saori Nishio, Kenji Osafune.

  In autosomal dominant polycystic kidney disease (ADPKD), renal cyst lesions predominantly arise from collecting ducts (CDs). However, relevant CD cyst models using human cells are lacking. Although previous reports have generated in vitro renal tubule cyst models from human induced pluripotent stem cells (hiPSCs), therapeutic drug candidates for ADPKD have not been identified. Here, by establishing expansion cultures of hiPSC-derived ureteric bud tip cells, an embryonic precursor that gives rise to CDs, we succeed in advancing the developmental stage of CD organoids and show that all CD organoids derived from PKD1-/- hiPSCs spontaneously develop multiple cysts, clarifying the initiation mechanisms of cystogenesis. Moreover, we identify retinoic acid receptor (RAR) agonists as candidate drugs that suppress in vitro cystogenesis and confirm the therapeutic effects on an ADPKD mouse model in vivo. Therefore, our in vitro CD cyst model contributes to understanding disease mechanisms and drug discovery for ADPKD.

Keywords:  CP: Stem cell research; autosomal dominant polycystic kidney disease; collecting duct; high-throughput screening; human induced pluripotent stem cell; in vitro model; organoid; ureteric bud

DOI:  https://doi.org/10.1016/j.celrep.2023.113431