Molecular modeling and rational design of hydrocarbon-stapled/halogenated helical peptides targeting CETP self-binding site: Therapeutic implication for atherosclerosis

Stapled peptides as potential therapeutics for diabetes and other metabolic diseases

The field of peptide drug research has experienced notable progress, with stapled peptides featuring stabilized α-helical conformation, emerging as a promising field. These peptides offer enhanced stability, cellular permeability, and binding affinity and exhibit potential in the treatment of diabetes and metabolic disorders. Stapled peptides, through the disruption of protein-protein interactions, present varied functionalities encompassing agonism, antagonism, and dual-agonism. This comprehensive review offers insight into the technology of peptide stapling and targeting of crucial molecular pathways associated with glucose metabolism, insulin secretion, and food intake. Additionally, we address the challenges in developing stapled peptides, including concerns pertaining to structural stability, peptide helicity, isomer mixture, and potential side effects.

Therapeutic peptides for coronary artery diseases: in silico methods and current perspectives

Many drug formulations containing small active molecules are used for the treatment of coronary artery disease, which affects a significant part of the world's population. However, the inadequate profile of these molecules in terms of therapeutic efficacy has led to the therapeutic use of protein and peptide-based biomolecules with superior properties, such as target-specific affinity and low immunogenicity, in critical diseases. Protein‒protein interactions, as a consequence of advances in molecular techniques with strategies involving the combined use of in silico methods, have enabled the design of therapeutic peptides to reach an advanced dimension. In particular, with the advantages provided by protein/peptide structural modeling, molecular docking for the study of their interactions, molecular dynamics simulations for their interactions under physiological conditions and machine learning techniques that can work in combination with all these, significant progress has been made in approaches to developing therapeutic peptides that can modulate the development and progression of coronary artery diseases. In this scope, this review discusses in silico methods for the development of peptide therapeutics for the treatment of coronary artery disease and strategies for identifying the molecular mechanisms that can be modulated by these designs and provides a comprehensive perspective for future studies.

Computational Tools and Strategies to Develop Peptide-Based Inhibitors of Protein-Protein Interactions

Protein-protein interactions play crucial and subtle roles in many biological processes and modifications of their fine mechanisms generally result in severe diseases. Peptide derivatives are very promising therapeutic agents for modulating protein-protein associations with sizes and specificities between those of small compounds and antibodies. For the same reasons, rational design of peptide-based inhibitors naturally borrows and combines computational methods from both protein-ligand and protein-protein research fields. In this chapter, we aim to provide an overview of computational tools and approaches used for identifying and optimizing peptides that target protein-protein interfaces with high affinity and specificity. We hope that this review will help to implement appropriate in silico strategies for peptide-based drug design that builds on available information for the systems of interest.