Aug 2026· RSC Medicinal Chemistry· 0 citations· 3 references
Medicine
TL;DR
A framework for accelerating the development of next-generation PPI therapeutics is provided by connecting interface architecture with optimal inhibitor modality and discovery strategy, revealing clear links between interface topology and inhibitor discovery strategies.
Abstract
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.
The dysregulation of protein–protein interactions (PPIs) in disease states is well established, yet they are challenging to target, owing to the large surface area and featureless nature of protein binding interfaces. For targeting helix-mediated interactions, α-helix mimetics present a promising strategy. These are versatile small molecule scaffolds, capable of mimicking the hotspot residues on an α-helix. A wide range of such scaffolds have been reported, yet their target protein selectivity in the context of a whole proteome requires further exploration. Here, we report the affinity-based protein profiling of three structurally distinct classes of α-helix mimetics, N-substituted oligobenzamides, pyrrolopyrimidines, and oxopiperazines. This represents the first direct cross-comparison of different helix mimetic scaffolds, revealing significant differences in proteome-wide selectivity.
Amrita Date, Archie Wall, Hannah Kiely-Collins et al.· RSC Chemical Biology· 0 citations
Macrocyclic peptides and peptidomimetics (MPPs) have emerged as a powerful therapeutic class in peptide-based drug discovery, uniquely positioned to modulate challenging protein-protein interactions (PPIs). While dysregulated PPIs drive diverse human pathologies, including cancer, metabolic disorders, neurodegenerative proteinopathies, inflammatory conditions, and microbial infections, targeting them remains difficult. Traditional small molecules lack the surface area to bind large, flat PPI interfaces, whereas linear peptides suffer from rapid proteolytic degradation and poor cell permeability. MPPs overcome these limitations by bridging the gap between small molecules and biologics. Their cyclic architecture provides conformational rigidity minimizing entropic penalties and maximizing binding affinity and selectivity. This structural pre-organization also enhances metabolic robustness, protease resistance, and cellular permeability. This review comprehensively examines the biological significance of PPIs in human disease and details how MPPs effectively modulate historically undruggable targets. We highlight current synthetic strategies, peptide engineering platforms, and the clinical and preclinical status of leading MPP candidates, while weighing their operational advantages and limitations. Finally, we analyze the contemporary market trajectory and emerging commercial opportunities, positioning MPPs as next-generation, PPI-targeting therapeutics.
The fragment molecular orbital (FMO) quantum mechanics method offers a comprehensive and computationally inexpensive means of identifying the strength and the chemical nature of the molecular interactions taking place at the protein-protein interface of large biomolecular systems.
Dustin C. Woods, Stefania Monteleone, Stéphanie Labouille· Methods in molecular biology· 0 citations
Whether binding specificity and partner selection in protein-protein interactions (PPIs) can be reliably inferred from static structures or require more dynamic, pathway-resolved energetic analyses remains an open question. To explore this, we focus on the ornithine decarboxylase (ODC)-antizyme isoform 1 (Az1)-antizyme inhibitor (AzIN) system, a well-characterized competitive PPI network that plays a critical role in regulating polyamine homeostasis. By combining extensive all-atom molecular dynamics simulations with biochemical experiments and the development of a new tool, we uncover key dynamic features of the static and recognition pathway interaction. Based on these, we designed novel antizyme isoforms (NAZs). Our analysis, using residue-resolved energetic landscapes, reveals critical determinants of binding specificity and partner selection that static structures alone cannot capture. These insights guide the engineering of NAZs that either directly engage ODC or modulate Az1 availability. This work provides a new perspective, demonstrating that dynamic energetic landscapes, rather than static structures, are key to understanding and modulating competitive protein recognition. Additionally, our DyResEL tool enables broader, more detailed analyses of energetic contributions, offering a versatile approach for exploring PPIs in various biological contexts.
Baolin Guo, Qian Xue, Fan Yang et al.· Journal of Chemical Informat...· 0 citations
Protein phosphorylation regulates nearly every cellular process, yet most of the hundreds of thousands of human phosphosites remain functionally uncharacterized. Rather than prioritising phosphosites by conservation or structural features, here we use the abundance of an interaction partner as a readout of whether a phosphosite affects that interaction. This idea exploits the fact that subunits of stable complexes are often degraded when unbound. Here, we apply a nested linear regression model to pan-cancer data from 1,006 tumours, while controlling for transcriptional and other covariates. We identified 6,160 associations between 3,038 phosphosites and the abundance of interacting proteins, including several known interaction-regulating sites. Mapping these onto AlphaFold-predicted complexes placed 239 sites at interaction interfaces, while another 402 were linked to compartment-specific localisation, indicating that phosphorylation can also tune interactions by relocating proteins between compartments. Affinity-purification mass spectrometry of NKAP and NUF2 phosphosite mutants experimentally supported some of these predictions. Together, this framework reveals a widespread coupling between phosphorylation and interaction-dependent protein abundance and provides a prioritized, structure-informed resource for characterizing the human phosphoproteome
Protein-protein interactions (PPIs) are crucial for the regulation of a majority of, if not every fundamental cellular process. Despite their role in regular biological processes, dysregulated and/or aberrant protein-protein interactions (aPPIs) are often related to the onset of disease including cancer, viral infection, and amyloid diseases. aPPIs have historically been deemed ‘undruggable’ due to their large surface area and lack of a binding cavity; however, today, more than 40 disease-related aPPIs have been targeted with small molecules and several of those have reached clinical trials.
A class of synthetic protein mimetics called oligopyridylamides (OPs) has been shown to inhibit disease-related aPPIs by mimicking the α-helical secondary structure of proteins. These molecules, constrained by intramolecular hydrogen bonding, project their functional groups in the exact spacing to interact with the i, i + 3/4, and i + 7 residues on one-face of an α-helical protein. These molecules have been shown to disrupt aPPIs related to Alzheimer’s disease, HIV, cancer, and diabetes though libraries of OPs have been severely limited by their tedious synthetic pathway and lack systematic optimization.
To address this, we developed a 2-Dimensional Fragment-Assisted Structure-based Technique (2D-FAST) for the OP synthetic protein mimetic scaffold and applied it to the discovery of a potential therapeutic for Parkinson’s disease (PD). In this technique, we simplified the synthesis of OPs and optimized the activity of the mono-, di-, and tri-pyridyl against the aggregation of α-Synuclein (αS), the hallmark of PD. We anticipated that the carboxylic acid functional group of the most post potent tripyridyl antagonist (NS132) would limit its cell permeability. By synthetically modifying the carboxylic acid to its more lipophilic hydroxamic acid isostere, we optimized the permeability which enhanced its activity towards αS aggregation in human embryonic kidney (HEK) cells and the rescue of PD phenotypes in pre- and post-disease onset C. elegans models. We further showed that NS132 and SK-129 (a previously discovered oligoquinoline inhibitor of αS aggregation) inhibited the aggregation of αS that is phosphorylated at S-129, a common post-translational modification abundant in Lewy bodies and Lewy neurites present in synucleinopathies. This work successfully demonstrates the ability of the 2D-FAST to discover potent antagonists of pathological proteins related to a wide range of diseases.
Given that the treatment of diseases of the central nervous system is severely limited by the difficulty of discovering therapeutics which are able to penetrate the blood-brain barrier (BBB), we further developed an innovative, OP-based nanoparticle drug delivery system called nano-Foldamers. The advantage of our nano-Foldamers is the ability to synthetically modify and tune the size and specificity of the nanoparticle for the specific therapeutic cargo and drug target. There is accumulating evidence to support the therapeutic strategy of reducing Tau expression in the brains of Alzheimer’s disease patients to reduce the neuron loss and memory deficits associated with the disease. In this work, we used nano-Foldamers to deliver a functional antisense oligonucleotide (ASO) to reduce Tau expression in HEK cells as shown by confocal imaging and flow cytometry experiments. We further demonstrated the therapeutic potential of our nano-Foldamers by showing that delivery of the ASO significantly limited the puncta formation in the cells when transfected with pre-formed fibrils of the protein. We envision the nano-Foldamers drug delivery system being applicable to an array of diseases involving the central nervous system, from neurodegeneration to infectious diseases and cancer.
Nicholas H. Stillman· 0 citations
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