Refinement of a Quantitative Structure–Activity Relationship Model for Prediction of Cell-Penetrating Peptide Based Transfection Systems

POSEIDON: Peptidic Objects SEquence-based Interaction with cellular DOmaiNs: a new database and predictor

Cell-penetrating peptides (CPPs) are short chains of amino acids that have shown remarkable potential to cross the cell membrane and deliver coupled therapeutic cargoes into cells. Designing and testing different CPPs to target specific cells or tissues is crucial to ensure high delivery efficiency and reduced toxicity. However, in vivo/in vitro testing of various CPPs can be both time-consuming and costly, which has led to interest in computational methodologies, such as Machine Learning (ML) approaches, as faster and cheaper methods for CPP design and uptake prediction. However, most ML models developed to date focus on classification rather than regression techniques, because of the lack of informative quantitative uptake values. To address these challenges, we developed POSEIDON, an open-access and up-to-date curated database that provides experimental quantitative uptake values for over 2,300 entries and physicochemical properties of 1,315 peptides. POSEIDON also offers physicochemical properties, such as cell line, cargo, and sequence, among others. By leveraging this database along with cell line genomic features, we processed a dataset of over 1,200 entries to develop an ML regression CPP uptake predictor. Our results demonstrated that POSEIDON accurately predicted peptide cell line uptake, achieving a Pearson correlation of 0.87, Spearman correlation of 0.88, and r2 score of 0.76, on an independent test set. With its comprehensive and novel dataset, along with its potent predictive capabilities, the POSEIDON database and its associated ML predictor signify a significant leap forward in CPP research and development. The POSEIDON database and ML Predictor are available for free and with a user-friendly interface at https://moreiralab.com/resources/poseidon/ , making them valuable resources for advancing research on CPP-related topics. Scientific Contribution Statement: Our research addresses the critical need for more efficient and cost-effective methodologies in Cell-Penetrating Peptide (CPP) research. We introduced POSEIDON, a comprehensive and freely accessible database that delivers quantitative uptake values for over 2,300 entries, along with detailed physicochemical profiles for 1,315 peptides. Recognizing the limitations of current Machine Learning (ML) models for CPP design, our work leveraged the rich dataset provided by POSEIDON to develop a highly accurate ML regression model for predicting CPP uptake.

Approaches for evaluation of novel CPP-based cargo delivery systems

Cell penetrating peptides (CPPs) can be broadly defined as relatively short synthetic, protein derived or chimeric peptides. Their most remarkable property is their ability to cross cell barriers and facilitate the translocation of cargo, such as drugs, nucleic acids, peptides, small molecules, dyes, and many others across the plasma membrane. Over the years there have been several approaches used, adapted, and developed for the evaluation of CPP efficacies as delivery systems, with the fluorophore attachment as the most widely used approach. It has become progressively evident, that the evaluation method, in order to lead to successful outcome, should concede with the specialties of the delivery. For characterization and assessment of CPP-cargo a combination of research tools of chemistry, physics, molecular biology, engineering, and other fields have been applied. In this review, we summarize the diverse, in silico, in vitro and in vivo approaches used for evaluation and characterization of CPP-based cargo delivery systems.

Biological Membrane-Penetrating Peptides: Computational Prediction and Applications

Peptides comprise a versatile class of biomolecules that present a unique chemical space with diverse physicochemical and structural properties. Some classes of peptides are able to naturally cross the biological membranes, such as cell membrane and blood-brain barrier (BBB). Cell-penetrating peptides (CPPs) and blood-brain barrier-penetrating peptides (B3PPs) have been explored by the biotechnological and pharmaceutical industries to develop new therapeutic molecules and carrier systems. The computational prediction of peptides’ penetration into biological membranes has been emerged as an interesting strategy due to their high throughput and low-cost screening of large chemical libraries. Structure- and sequence-based information of peptides, as well as atomistic biophysical models, have been explored in computer-assisted discovery strategies to classify and identify new structures with pharmacokinetic properties related to the translocation through biomembranes. Computational strategies to predict the permeability into biomembranes include cheminformatic filters, molecular dynamics simulations, artificial intelligence algorithms, and statistical models, and the choice of the most adequate method depends on the purposes of the computational investigation. Here, we exhibit and discuss some principles and applications of these computational methods widely used to predict the permeability of peptides into biomembranes, exhibiting some of their pharmaceutical and biotechnological applications.

Improvement of Transfection with PepFects Using Organic and Inorganic Materials

Cell-penetrating peptides (CPPs) are a promising non-viral vector for gene and drug delivery. CPPs exhibit high cell transfection, and are biocompatible. They can be also conjugated with organic and inorganic nanomaterials, such as magnetic nanoparticles (MNPs), graphene oxide (GO), metal-organic frameworks (MOFs), and chitosan. Nanomaterials offered a high specific surface area and provided relatively straightforward methods to be modified with biomolecules including CPPs and oligonucleotides (ONs). Novel nanomaterials conjugates with CPP/ONs complexes are therefore of interest for cell transfection with high efficiency. In this chapter, we described a summary of the non-viral vectors consisting of CPPs and nanomaterials. The book chapter also included a protocol to generate hybrid biomaterials consisting of CPPs and nanoparticles (NPs) for the delivery of oligonucleotides. The conjugation of NPs with CPPs serves as an effective platform for gene therapy with high cell transfection efficiency. The protocol is simple, offers high cell transfection compared to the CPPs-ONs complexes, and can be used for further improvements using external stimuli.

A novel peptide dendrimer LTP efficiently facilitates transfection of mammalian cells

One of the urgent problems of gene therapy is the search for effective transfection methods. Synthetic cationic peptides (CPs) are considered to be one of the most promising approaches for intracellular transport of oligonucleotides. Almost unlimited possibilities of the architectural design of CPs (linear and cyclic structures with a variation of chirality as well as dendrimers) make CPs an effective tunable carrier in this field. Cationic peptide dendrimers (PDs), as a relatively new direction, have significant advantages as gene delivery vehicles by virtue of non-natural ε-amide bonds that significantly increase their resistance to proteolysis. Moreover they also possess much lower cytotoxicity than linear peptides, which is crucial for the potential clinical application of CPs. In a further development of oligonucleotide delivery systems, we have synthesized a collection of 14 CPs, including linear peptides, lipopeptides and PDs. Their activity was evaluated by transfection of 293T cells with plasmids containing reporter genes encoding luciferase or a green fluorescent protein. The obtained results demonstrated that the greatest activity was exhibited by PDs, particularly LTP, an arginine-rich peptide dendrimer, which possesses low cytotoxic and hemolytic activity. The peptide exhibited high cell-penetrating activity, confirmed by fast dissipation of the membrane potential of cells probed by dis-C3-(5). The quantitative analysis of labelled LTP in tissue samples of mice revealed that the Cy5-LTP/siRNA complexes have a reasonable tropism to lung tissues.

Role of autophagy in cell-penetrating peptide transfection model

Cell-penetrating peptides (CPPs) uptake mechanism is still in need of more clarification to have a better understanding of their action in the mediation of oligonucleotide transfection. In this study, the effect on early events (1 h treatment) in transfection by PepFect14 (PF14), with or without oligonucleotide cargo on gene expression, in HeLa cells, have been investigated. The RNA expression profile was characterized by RNA sequencing and confirmed by qPCR analysis. The gene regulations were then related to the biological processes by the study of signaling pathways that showed the induction of autophagy-related genes in early transfection. A ligand library interfering with the detected intracellular pathways showed concentration-dependent effects on the transfection efficiency of splice correction oligonucleotide complexed with PepFect14, proving that the autophagy process is induced upon the uptake of complexes. Finally, the autophagy induction and colocalization with autophagosomes have been confirmed by confocal microscopy and transmission electron microscopy. We conclude that autophagy, an inherent cellular response process, is triggered by the cellular uptake of CPP-based transfection system. This finding opens novel possibilities to use autophagy modifiers in future gene therapy.

Magnetic Nanoparticle Assisted Self-assembly of Cell Penetrating Peptides-Oligonucleotides Complexes for Gene Delivery

Magnetic nanoparticles (MNPs, Fe3O4) incorporated into the complexes of cell penetrating peptides (CPPs)-oligonucleotides (ONs) promoted the cell transfection for plasmid transfection, splice correction, and gene silencing efficiencies. Six types of cell penetrating peptides (CPPs; PeptFect220 (denoted PF220), PF221, PF222, PF223, PF224 and PF14) and three types of gene therapeutic agents (plasmid (pGL3), splicing correcting oligonucleotides (SCO), and small interfering RNA (siRNA) were investigated. Magnetic nanoparticles incorporated into the complexes of CPPs-pGL3, CPPs-SCO, and CPPs-siRNA showed high cell biocompatibility and efficiently transfected the investigated cells with pGL3, SCO, and siRNA, respectively. Gene transfer vectors formed among PF14, SCO, and MNPs (PF14-SCO-MNPs) showed a superior transfection efficiency (up to 4-fold) compared to the noncovalent PF14-SCO complex, which was previously reported with a higher efficiency compared to commercial vector called Lipofectamine™2000. The high transfection efficiency of the new complexes (CPPs-SCO-MNPs) may be attributed to the morphology, low cytotoxicity, and the synergistic effect of MNPs and CPPs. PF14-pDNA-MNPs is an efficient complex for in vivo gene delivery upon systemic administration. The conjugation of CPPs-ONs with inorganic magnetic nanoparticles (Fe3O4) may open new venues for selective and efficient gene therapy.