Jul 2026· International Journal of Molecular Sciences· Vol 27, pp. 6067· 0 citations· 194 references
Medicine
TL;DR
This review provides an updated overview of cyclic peptides as modulators of PPIs, outlining current opportunities, methodological advances, and remaining challenges in the development of cyclic peptide-based PPI modulators.
Abstract
Protein–protein interactions (PPIs) represent a vast and largely underexplored landscape of therapeutic targets, yet their structural features—including large, flat, and dynamic interfaces—have historically limited their druggability. In this context, cyclic peptides have emerged as a powerful class of PPI modulators, sitting at the interface between biologics and small molecules, and thus garnering key advantages of both classes. Their conformational constraint enhances binding affinity, proteolytic stability and, in some instances, cell permeability, thus enabling access to intracellular targets. This review provides an updated overview of cyclic peptides as modulators of PPIs, focusing on both conceptual foundations and practical strategies for their discovery and optimization. The main discovery approaches include natural sources, de novo design based on secondary structure mimetics, high-throughput screening, and computational approaches. Integration of these complementary strategies is crucial to enhance success rates in the discovery of effective and developable cyclic peptides. Accordingly, the present review aims to provide a practical guide for researchers entering this rapidly growing field, outlining current opportunities, methodological advances, and remaining challenges in the development of cyclic peptide-based PPI modulators.
Protein–protein interactions (PPIs) orchestrate cellular function yet remain largely underexploited as therapeutic targets. Although the human interactome is estimated to contain more than 650 000 PPIs, only 117 interactions (∼0.02%) have reported inhibitors. Here, we review human PPIs with peptide, peptidomimetic, small-molecule and antibody inhibitors, and classify them according to the dominant secondary structure at the interaction interface. This framework separates PPIs into α-helix-, β-strand- and disordered/loop-mediated interactions, revealing clear links between interface topology and inhibitor discovery strategies. α-Helical interfaces account for most reported inhibitors, whereas β-strand-mediated and dynamic interactions remain comparatively underexplored despite their biological importance. Across structural classes, successful inhibitor discovery has been enabled by structure-guided approaches, including rational peptide design, macrocyclisation, fragment-based screening and peptide-directed ligand design. However, progress remains slow for challenging targets, particularly coiled-coil interactions and intrinsically disordered regions. Emerging technologies, including cryo-electron microscopy and machine learning-guided structure prediction, are rapidly expanding access to these targets. By connecting interface architecture with optimal inhibitor modality and discovery strategy, this review provides a framework for accelerating the development of next-generation PPI therapeutics.
Ellie Hyde, A. Beekman· RSC Medicinal Chemistry· 0 citations
Natural cyclic peptides have long served as a rich reservoir of bioactivity, occupying a unique region of the drug space that bridges the gap between small molecules and large biologics. Evolution has perfected the macrocyclic architecture to achieve exceptional target specificity and metabolic stability, providing a structural blueprint that allows these molecules to engage extended protein surfaces often inaccessible to conventional drugs. While early landmarks like cyclosporin A demonstrated the power of chameleonicity, the ability to adapt conformations to different environments - the field is currently undergoing a paradigm shift. Nature is no longer viewed merely as a source of lead compounds to be mined, but as a conceptual framework for de novo design. By integrating natural principles such as conformational constraint and amide-masking with cutting-edge technologies like mRNA display (e.g. RaPID) and artificial intelligence, researchers are now rationally engineering next-generation macrocycles, positioning them at the frontier of modern drug development.
Greta Bergamaschi, Giulia Lodigiani, Stefano Gandolfi et al.· Current Opinion in Chemical...· 0 citations
Cyclic peptides have emerged as a compelling class of bioactive scaffolds, but de novo design of target-binding cyclic peptides from protein structures remains challenging. Here, we present HighMorph, an interaction-guided framework that combines protein–protein interaction information with artificial intelligence for rational cyclic peptide design. HighMorph integrates Monte Carlo tree search with a Transformer-based policy-value network to efficiently explore cyclic peptide sequence space, while incorporating explicit atomic-level hydrogen bond constraints extracted from reference protein–protein complexes to guide sequence optimization. The framework is systematically validated on two clinically relevant targets, programmed death-ligand 1 (PD-L1) and kallikrein-related peptidase 4 (KLK4). Notably, 33.3% and 40% of the generated candidates are active against PD-L1 and KLK4, respectively, with active cyclic peptides exhibiting micromolar binding affinities (approximately 10–6 M). These results validate our approach for cyclic peptide design. Additionally, interaction analysis provides insights for developing therapeutics targeting challenging protein interfaces.
Minhui Lan, Chengyun Zhang, Wentong Wang et al.· Journal of Medicinal Chemist...· 0 citations
Peptide therapeutics are an important drug modality due to their high specificity, favorable safety, and expanding design potential. Among them, cyclic peptides occupy a space between small molecules and biologics, offering improved rigidity, stability, and target engagement. This report analyzes trends in cyclic peptide research using data from the CAS Content Collection over the past two decades. Results show a steady rise in academic publications and patents, reflecting growing interest across discovery and development. Notably, oral administration is gaining attention, indicating progress toward addressing long-standing bioavailability challenges. Beyond delivery, we examine how peptide and cyclization types, along with specific chemical modifications, relate to administration routes, therapeutic indications, and molecular targets. We also assess physicochemical properties to understand how molecular features influence developability. Together, these insights provide a comprehensive view of the evolving cyclic peptide landscape and emerging principles guiding their future development.
T. Thite, Kavita A. Iyer, Preeti Jain et al.· Journal of Medicinal Chemist...· 0 citations
Protein kinases are central regulators of cellular signaling and remain a major target class in precision medicine. While ATP-competitive inhibitors-including conformation-selective and covalent agents-have delivered substantial clinical benefit, durable responses are frequently limited by the conservation of the ATP pocket and the emergence of resistance mutations (e.g. gatekeeper and solvent-front substitutions), as well as kinase noncatalytic functions that are not addressed by enzymatic inhibition alone. Consequently, kinase drug discovery is expanding beyond orthosteric occupancy toward modalities that reprogram kinase conformations or eliminate the target protein. This Review summarizes the structural and medicinal chemistry principles underlying (i) allosteric inhibition and (ii) proximity-induced degradation, with an emphasis on design logic, structure-activity relationships, and key liabilities in the beyond rule of five space. We further highlight enabling technologies-including structural biology, chemical proteomics, and AI/ML-assisted modeling-that support allosteric site identification, ternary complex engineering, and multi-parameter optimization. Finally, we discuss translational challenges for bifunctional molecules, including permeability, exposure-response relationships, off-target degradation, and safety, and propose practical considerations for developing next-generation selective kinase therapeutics.
Mei Zhou, Linshan Li, Xiaojuan Tang et al.· Future Medicinal Chemistry· 0 citations