Polypharmacy through Phage Display: Selection of Glucagon and GLP-1 Receptor Co-agonists from a Phage-Displayed Peptide Library

Phage Display Technology in Biomarker Identification with Emphasis on Non-Cancerous Diseases

In recent years, phage display technology has become vital in clinical research. It helps create antibodies that can specifically bind to complex antigens, which is crucial for identifying biomarkers and improving diagnostics and treatments. However, existing reviews often overlook its importance in areas outside cancer research. This review aims to fill that gap by explaining the basics of phage display and its applications in detecting and treating various non-cancerous diseases. We focus especially on its role in degenerative diseases, inflammatory and autoimmune diseases, and chronic non-communicable diseases, showing how it is changing the way we diagnose and treat illnesses. By highlighting important discoveries and future possibilities, we hope to emphasize the significance of phage display in modern healthcare.

A Model Study to Assess Fibrillation and Product Stability to Support Peptide Drug Design

The fibrillation of therapeutic peptides can present significant quality concerns and poses challenges for manufacturing and storage. A fundamental understanding of the mechanisms of fibrillation is critical for the rational design of fibrillation-resistant peptide drugs and can accelerate product development by guiding the selection of solution-stable candidates and formulations. The studies reported here investigated the effects of structural modifications on the fibrillation of a 29-residue peptide (PepA) and two sequence modified variants (PepB, PepC). The C-terminus of PepA was amidated, whereas both PepB and PepC retained the carboxylate, and Ser16 in PepA and PepB was substituted with a helix-stabilizing residue, α-aminoisobutyric acid (Aib), in PepC. In thermal denaturation studies by far-UV CD spectroscopy and fibrillation kinetic studies by fluorescence and turbidity measurements, PepA and PepB showed heat-induced conformational changes and were found to form fibrils, whereas PepC did not fibrillate and showed only minor changes in the CD signal. Pulsed hydrogen-deuterium exchange mass spectrometry (HDX-MS) showed a high degree of protection from HD exchange in mature PepA fibrils and its proteolytic fragments, indicating that most of the sequence had been incorporated into the fibril structure and occurred nearly simultaneously throughout the sequence. The effects of the net peptide charge and formulation pH on fibrillation kinetics were investigated. In real-time stability studies of two formulations of PepA at pH's 7.4 and 8.0, analytical methods detected significant changes in the stability of the formulations at different time points during the study, which were not observed during accelerated studies. Additionally, PepA samples were withdrawn from real-time stability and subjected to additional stress (40 °C, continuous shaking) to induce fibrillation; an approach that successfully amplified oligomers or prefibrillar species previously undetected in a thioflavin T assay. Taken together, these studies present an approach to differentiate and characterize fibrillation risk in structurally related peptides under accelerated and real-time conditions, providing a model for rapid, iterative structural design to optimize the stability of therapeutic peptides.

Computational Peptide Design Cotargeting Glucagon and Glucagon-like Peptide-1 Receptors

Peptides are sustainable alternatives to conventional therapeutics for G protein-coupled receptor (GPCR) linked disorders, promising biocompatible and tailorable next-generation therapeutics for metabolic disorders including type-2 diabetes, as agonists of the glucagon receptor (GCGR) and the glucagon-like peptide-1 receptor (GLP-1R). However, single agonist peptides activating GLP-1R to stimulate insulin secretion also suppress obesity-linked glucagon release. Hence, bioactive peptides cotargeting GCGR and GLP-1R may remediate the blood glucose and fatty acid metabolism imbalance, tackling both diabetes and obesity to supersede current monoagonist therapy. Here, we design and model optimized peptide sequences starting from peptide sequences derived from earlier phage-displayed library screening, identifying those with predicted molecular binding profiles for dual agonism of GCGR and GLP-1R. We derive design rules from extensive molecular dynamics simulations based on peptide-receptor binding. Our newly designed coagonist peptide exhibits improved predicted coupled binding affinity for GCGR and GLP-1R relative to endogenous ligands and could in the future be tested experimentally, which may provide superior glycemic and weight loss control.

An integrated platform approach enables discovery of potent, selective and ligand-competitive cyclic peptides targeting the GIP receptor

In any drug discovery effort, the identification of hits for further optimisation is of crucial importance. For peptide therapeutics, display technologies such as mRNA display have emerged as powerful methodologies to identify these desired de novo hit ligands against targets of interest. The diverse peptide libraries are genetically encoded in these technologies, allowing for next-generation sequencing to be used to efficiently identify the binding ligands. Despite the vast datasets that can be generated, current downstream methodologies, however, are limited by low throughput validation processes, including hit prioritisation, peptide synthesis, biochemical and biophysical assays. In this work we report a highly efficient strategy that combines bioinformatic analysis with state-of-the-art high throughput peptide synthesis to identify nanomolar cyclic peptide (CP) ligands of the human glucose-dependent insulinotropic peptide receptor (hGIP-R). Furthermore, our workflow is able to discriminate between functional and remote binding non-functional ligands. Efficient structure-activity relationship analysis (SAR) combined with advanced in silico structural studies allow deduction of a thorough and holistic binding model which informs further chemical optimisation, including efficient half-life extension. We report the identification and design of the first de novo, GIP-competitive, incretin receptor family-selective CPs, which exhibit an in vivo half-life up to 10.7 h in rats. The workflow should be generally applicable to any selection target, improving and accelerating hit identification, validation, characterisation, and prioritisation for therapeutic development.

Highly paralleled emulsion droplets for efficient isolation, amplification, and screening of cancer biomarker binding phages

Based on the linkage of genotype and phenotype, display technology has been widely used to generate specific ligands for profiling, imaging, diagnosis and therapy applications. However, due to the lack of effective monoclonal manipulation and affinity evaluation methods, traditional display technology has to undergo tedious steps of selection, clone isolation, amplification, sequencing, synthesis and characterization to obtain the binding sequences. To directly acquire high-affinity clones, we propose a double monoclonal display approach (dm-Display) for peptide screening based on highly paralleled monoclonal manipulation in emulsion droplets. dm-Display can monoclonally link the genotype, phenotype and affinity to realize integrated monoclonal separation, amplification, recognition and staining in one droplet so that discrete high-affinity clones can be quickly extracted. Monoclonal manipulations highly-parallelly occur in millions of droplets so that molecular screening of a highly diverse phage library is achieved. We have screened specific peptide ligands against CD71 and GPC1, proving the feasibility and generality of dm-Display. As a highly efficient ligand screening platform, dm-Display will promote the further development of molecular screening.

High-dimensionality Data Analysis of Pharmacological Systems Associated with Complex Diseases

It is widely accepted that molecular reductionist views of highly complex human physiologic activity, e.g., the aging process, as well as therapeutic drug efficacy are largely oversimplifications. Currently some of the most effective appreciation of biologic disease and drug response complexity is achieved using high-dimensionality (H-D) data streams from transcriptomic, proteomic, metabolomics, or epigenomic pipelines. Multiple H-D data sets are now common and freely accessible for complex diseases such as metabolic syndrome, cardiovascular disease, and neurodegenerative conditions such as Alzheimer's disease. Over the last decade our ability to interrogate these high-dimensionality data streams has been profoundly enhanced through the development and implementation of highly effective bioinformatic platforms. Employing these computational approaches to understand the complexity of age-related diseases provides a facile mechanism to then synergize this pathologic appreciation with a similar level of understanding of therapeutic-mediated signaling. For informative pathology and drug-based analytics that are able to generate meaningful therapeutic insight across diverse data streams, novel informatics processes such as latent semantic indexing and topological data analyses will likely be important. Elucidation of H-D molecular disease signatures from diverse data streams will likely generate and refine new therapeutic strategies that will be designed with a cognizance of a realistic appreciation of the complexity of human age-related disease and drug effects. We contend that informatic platforms should be synergistic with more advanced chemical/drug and phenotypic cellular/tissue-based analytical predictive models to assist in either de novo drug prioritization or effective repurposing for the intervention of aging-related diseases. SIGNIFICANCE STATEMENT: All diseases, as well as pharmacological mechanisms, are far more complex than previously thought a decade ago. With the advent of commonplace access to technologies that produce large volumes of high-dimensionality data (e.g., transcriptomics, proteomics, metabolomics), it is now imperative that effective tools to appreciate this highly nuanced data are developed. Being able to appreciate the subtleties of high-dimensionality data will allow molecular pharmacologists to develop the most effective multidimensional therapeutics with effectively engineered efficacy profiles.

Type 2 Diabetes Mellitus Associated with Obesity (Diabesity). The Central Role of Gut Microbiota and Its Translational Applications

Obesity is a condition of rising prevalence worldwide, with important socioeconomic implications, being considered as a growing public health concern. Frequently, obesity brings other complications in addition to itself—like Type 2 Diabetes Mellitus (T2DM)—sharing origin, risk factors and pathophysiological mechanisms. In this context, some authors have decided to include both conditions as a unique entity known as “diabesity”. In fact, understanding diabesity as a single disease is possible to maximise the benefits from therapies received in these patients. Gut microbiota plays a key role in individual’s health, and their alterations, either in its composition or derived products are related to a wide range of metabolic disorders like T2DM and obesity. The present work aims to collect the different changes reported in gut microbiota in patients with T2DM associated with obesity and their possible role in the onset, development, and establishment of the disease. Moreover, current research lines to modulate gut microbiota and the potential clinical translation derived from the knowledge of this system will also be reviewed, which may provide support for a better clinical management of such a complex condition.

Peptide Conjugates with Small Molecules Designed to Enhance Efficacy and Safety

Peptides constitute molecular diversity with unique molecular mechanisms of action that are proven indispensable in the management of many human diseases, but of only a mere fraction relative to more traditional small molecule-based medicines. The integration of these two therapeutic modalities offers the potential to enhance and broaden pharmacology while minimizing dose-dependent toxicology. This review summarizes numerous advances in drug design, synthesis and development that provide direction for next-generation research endeavors in this field. Medicinal studies in this area have largely focused upon the application of peptides to selectively enhance small molecule cytotoxicity to more effectively treat multiple oncologic diseases. To a lesser and steadily emerging extent peptides are being therapeutically employed to complement and diversify the pharmacology of small molecule drugs in diseases other than just cancer. No matter the disease, the purpose of the molecular integration remains constant and it is to achieve superior therapeutic outcomes with diminished adverse effects. We review linker technology and conjugation chemistries that have enabled integrated and targeted pharmacology with controlled release. Finally, we offer our perspective on opportunities and obstacles in the field.