Macrocycles as protein-protein interaction inhibitors

E3 Ligase Ligands for PROTACs: How They Were Found and How to Discover New Ones

Bifunctional degrader molecules, also called proteolysis-targeting chimeras (PROTACs), are a new modality of chemical tools and potential therapeutics to understand and treat human disease. A required PROTAC component is a ligand binding to an E3 ubiquitin ligase, which is then joined to another ligand binding to a protein to be degraded via the ubiquitin-proteasome system. The advent of nonpeptidic small-molecule E3 ligase ligands, notably for von Hippel-Lindau (VHL) and cereblon (CRBN), revolutionized the field and ushered in the design of drug-like PROTACs with potent and selective degradation activity. A first wave of PROTAC drugs are now undergoing clinical development in cancer, and the field is seeking to extend the repertoire of chemistries that allow hijacking new E3 ligases to improve the scope of targeted protein degradation.Here, we briefly review how traditional E3 ligase ligands were discovered, and then outline approaches and ligands that have been recently used to discover new E3 ligases for PROTACs. We will then take an outlook at current and future strategies undertaken that invoke either target-based screening or phenotypic-based approaches, including the use of DNA-encoded libraries (DELs), display technologies and cyclic peptides, smaller molecular glue degraders, and covalent warhead ligands. These approaches are ripe for expanding the chemical space of PROTACs and usher in the advent of other emerging bifunctional modalities of proximity-based pharmacology.

The Development of a Fluorescence-Based Competitive Assay Enabled the Discovery of Dimeric Cyclic Peptide Modulators of Ubiquitin Chains

Development of modulators targeting specific interactions of ubiquitin-based conjugates with their partners is a formidable task since it requires a suitable screening assay and homogeneous ubiquitin conjugates. We developed a novel high-throughput strategy for screening ligands for Lys48-linked tetraubiquitin chain in a relatively simple, fast, and affordable manner. This approach combined with a state-of-the-art toolbox of chemical protein synthesis and a specially optimized Cys deprotection protocol enabled us to design highly potent, Lys48-linked tetraubiquitin chain selective "next generation" dimeric peptide modulators. The dimeric peptide exhibited cancer cell permeability and induced cell death with higher efficiency compared to its monocyclic analogue. These features make our dimeric peptide a promising candidate for further studies using in vivo models. Our assay can be adopted for other various ubiquitin chains in their free or anchored forms as well as conjugates for Ub-like modifiers.

Modulation of the Passive Permeability of Semipeptidic Macrocycles: N- and C-Methylations Fine-Tune Conformation and Properties

Incorporating small modifications to peptidic macrocycles can have a major influence on their properties. For instance, N-methylation has been shown to impact permeability. A better understanding of the relationship between permeability and structure is of key importance as peptidic drugs are often associated with unfavorable pharmacokinetic profiles. Starting from a semipeptidic macrocycle backbone composed of a tripeptide tethered head-to-tail with an alkyl linker, we investigated two small changes: peptide-to-peptoid substitution and various methyl placements on the nonpeptidic linker. Implementing these changes in parallel, we created a collection of 36 compounds. Their permeability was then assessed in parallel artificial membrane permeability assay (PAMPA) and Caco-2 assays. Our results show a systematic improvement in permeability associated with one peptoid position in the cycle, while the influence of methyl substitution varies on a case-by-case basis. Using a combination of molecular dynamics simulations and NMR measurements, we offer hypotheses to explain such behavior.

Converting peptides into drugs targeting intracellular protein-protein interactions

Peptides are gaining increasing attention as therapeutics to target intracellular protein-protein interactions that are involved in disease progression. In this review, we discuss how peptides that are able to bind and inhibit a therapeutic target can be translated into drug leads. We discuss the advantages of using peptides as therapeutics to target intracellular protein-protein interactions, chemical strategies to generate macrocyclic peptides that are resistant to proteolytic enzymes, high-throughput screening approaches to identify peptides that have high affinity for therapeutic targets, strategies that permit these peptides to cross cell membranes and so reach intracellular targets, and the importance of investigating their mode-of-action in guiding the development of novel therapeutics.

Structure Based Design of Bicyclic Peptide Inhibitors of RbAp48

The scaffolding protein RbAp48 is part of several epigenetic regulation complexes and is overexpressed in a variety of cancers. In order to develop tool compounds for the study of RbAp48 function, we have developed peptide inhibitors targeting the protein-protein interaction interface between RbAp48 and the scaffold protein MTA1. Based on a MTA1-derived linear peptide with low micromolar affinity and informed by crystallographic analysis, a bicyclic peptide was developed that inhibits the RbAp48/MTA1 interaction with a very low nanomolar KD value of 8.56 nM, and which showed appreciable stability against cellular proteases. Design included exchange of a polar amide cyclization strategy to hydrophobic aromatic linkers enabling mono- and bicyclization by means of cysteine alkylation, which improved affinity by direct interaction of the linkers with a hydrophobic residue on RbAp48. Our results demonstrate that stepwise evolution of a structure-based design is a suitable strategy for inhibitor development targeting PPIs.

Modulating Protein-Protein Interactions by Cyclic and Macrocyclic Peptides. Prominent Strategies and Examples

Cyclic and macrocyclic peptides constitute advanced molecules for modulating protein-protein interactions (PPIs). Although still peptide derivatives, they are metabolically more stable than linear counterparts, and should have a lower degree of flexibility, with more defined secondary structure conformations that can be adapted to imitate protein interfaces. In this review, we analyze recent progress on the main methods to access cyclic/macrocyclic peptide derivatives, with emphasis in a few selected examples designed to interfere within PPIs. These types of peptides can be from natural origin, or prepared by biochemical or synthetic methodologies, and their design could be aided by computational approaches. Some advances to facilitate the permeability of these quite big molecules by conjugation with cell penetrating peptides, and the incorporation of β-amino acid and peptoid structures to improve metabolic stability, are also commented. It is predicted that this field of research could have an important future mission, running in parallel to the discovery of new, relevant PPIs involved in pathological processes.

Alternative Sigma Factor of Staphylococcus aureus Interacts with the Cognate Antisigma Factor Primarily Using Its Domain 3

σ^B, an alternative sigma factor, is usually employed to tackle the general stress response in Staphylococcus aureus and other Gram-positive bacteria. This protein, involved in S. aureus-mediated pathogenesis, is typically blocked by RsbW, an antisigma factor having serine kinase activity. σ^B, a σ⁷⁰-like sigma factor, harbors three conserved domains designated σ^B2, σ^B3, and σ^B4. To better understand the interaction between RsbW and σ^B or its domains, we have studied their recombinant forms, rRsbW, rσ^B, rσ^B2, rσ^B3, and rσ^B4, using different probes. The results show that none of the rσ^B domains, unlike rσ^B, showed binding to a cognate DNA in the presence of a core RNA polymerase. However, both rσ^B2 and rσ^B3, like rσ^B, interacted with rRsbW, and the order of their rRsbW binding affinity looks like rσ^B > rσ^B3 > rσ^B2. Furthermore, the reaction between rRsbW and rσ^B or rσ^B3 was exothermic and occurred spontaneously. rRsbW and rσ^B3 also associate with each other at a stoichiometry of 2:1, and different types of noncovalent bonds might be responsible for their interaction. A structural model of the RsbW-σ^B3 complex that has supported our experimental results indicated the binding of rσ^B3 at the putative dimeric interface of RsbW. A genetic study shows that the tentative dimer-forming region of RsbW is crucial for preserving its rσ^B binding ability, serine kinase activity, and dimerization ability. Additionally, a urea-induced equilibrium unfolding study indicated a notable thermodynamic stabilization of σ^B3 in the presence of RsbW. Possible implications of the stabilization data in drug discovery were discussed at length.

Diversity-orientated synthesis of macrocyclic heterocycles using a double SNAr approach

An efficient macrocyclisation approach based on the double aromatic nucleophilic substitution (SNACK) was developed. This methodology allows a facile incorporation of heterocyclic motifs into macrocyclic rings and rapid synthesis of a significant number of structurally diverse macrocycles. SNACK macrocyclisation enables preparation of stable diastereoisomers of conformationally restricted macrocycles (atropisomers). Practical application of SNACK macrocyclisation in a drug discovery project was exemplified by the identification of high affinity macrocyclic binders of B-cell lymphoma 6 (BCL6).

Benchmark of Generic Shapes for Macrocycles

Macrocycles target proteins that are otherwise considered undruggable because of a lack of hydrophobic cavities and the presence of extended featureless surfaces. Increasing efforts by computational chemists have developed effective software to overcome the restrictions of torsional and conformational freedom that arise as a consequence of macrocyclization. Moloc is an efficient algorithm, with an emphasis on high interactivity, and has been constantly updated since 1986 by drug designers and crystallographers of the Roche biostructural community. In this work, we have benchmarked the shape-guided algorithm using a dataset of 208 macrocycles, carefully selected on the basis of structural complexity. We have quantified the accuracy, diversity, speed, exhaustiveness, and sampling efficiency in an automated fashion and we compared them with four commercial (Prime, MacroModel, molecular operating environment, and molecular dynamics) and four open-access (experimental-torsion distance geometry with additional “basic knowledge” alone and with Merck molecular force field minimization or universal force field minimization, Cambridge Crystallographic Data Centre conformer generator, and conformator) packages. With three-quarters of the database processed below the threshold of high ring accuracy, Moloc was identified as having the highest sampling efficiency and exhaustiveness without producing thousands of conformations, random ring splitting into two half-loops, and possibility to interactively produce globular or flat conformations with diversity similar to Prime, MacroModel, and molecular dynamics. The algorithm and the Python scripts for full automatization of these parameters are freely available for academic use.

Cyclic Peptide-Based Biologics Regulating HGF-MET

Using a random non-standard peptide integrated discovery system, we obtained cyclic peptides that bind to hepatocyte growth factor (HGF) or mesenchymal-epithelial transition factor. (MET) HGF-inhibitory peptide-8 (HiP-8) selectively bound to two-chain active HGF, but not to single-chain precursor HGF. HGF showed a dynamic change in its molecular shape in atomic force microscopy, but HiP-8 inhibited dynamic change in the molecular shape into a static status. The inhibition of the molecular dynamics of HGF by HiP-8 was associated with the loss of the ability to bind MET. HiP-8 could selectively detect active HGF in cancer tissues, and active HGF probed by HiP-8 showed co-localization with activated MET. Using HiP-8, cancer tissues with active HGF could be detected by positron emission tomography. HiP-8 seems to be applicable for the diagnosis and treatment of cancers. In contrast, based on the receptor dimerization as an essential process for activation, the cross-linking of the cyclic peptides that bind to the extracellular region of MET successfully generated an artificial ligand to MET. The synthetic MET agonists activated MET and exhibited biological activities which were indistinguishable from the effects of HGF. MET agonists composed of cyclic peptides can be manufactured by chemical synthesis but not recombinant protein expression, and thus are expected to be new biologics that are applicable to therapeutics and regenerative medicine.

Automated Design of Macrocycles for Therapeutic Applications: From Small Molecules to Peptides and Proteins

Macrocycles and cyclic peptides are increasingly attractive therapeutic modalities as they often have improved affinity, are able to bind to extended protein surfaces, and otherwise have favorable properties. Macrocyclization of a known binder may stabilize its bioactive conformation and improve its metabolic stability, cell permeability, and in certain cases oral bioavailability. Herein, we present implementation and application of an approach that automatically generates, evaluates, and proposes cyclizations utilizing a library of well-established chemical reactions and reagents. Using the three-dimensional (3D) conformation of the linear molecule in complex with a target protein as the starting point, this approach identifies attachment points, generates linkers, evaluates their geometric compatibility, and ranks the resulting molecules with respect to their predicted conformational stability and interactions with the target protein. As we show here with prospective and retrospective case studies, this procedure can be applied for the macrocyclization of small molecules and peptides and even PROteolysis TArgeting Chimeras (PROTACs) and proteins.

Cyclic Peptide-Gadolinium Nanoparticles for Enhanced Intracellular Delivery

A cyclic peptide containing one cysteine and five alternating tryptophan and arginine amino acids [(WR)₅C] was synthesized using Fmoc/tBu solid-phase methodology. The ability of the synthesized cyclic peptide to produce gadolinium nanoparticles through an in situ one-pot mixing of an aqueous solution of GdCl₃ with [(WR)₅C] peptide solution was evaluated. Transmission electron microscopy showed the formed peptide-Gd nanoparticles in star-shape morphology with a size of ~250 nm. Flow cytometry investigation showed that the cellular uptake of a cell-impermeable fluorescence-labeled phosphopeptide (F′-GpYEEI, where F′ = fluorescein) was approximately six times higher in the presence of [(WR)₅C]-Gd nanoparticles than those of F′-GpYEEI alone in human leukemia adenocarcinoma (CCRF-CEM) cells after 2 h incubation. The antiproliferative activities of cisplatin and carboplatin (5 µM) were increased in the presence of [(WR)₅C]-GdNPs (50 μM) by 41% and 18%, respectively, after 72-h incubation in CCRF-CEM cells. The intracellular release of epirubicin, an anticancer drug, from the complex showed that 15% and 60% of the drug was released intracellularly within 12 and 48 h, respectively. This report provides insight about using a non-toxic MRI agent, gadolinium nanoparticles, for the delivery of various types of molecular cargos.

A Macrocyclic Peptide Library with a Structurally Constrained Cyclopropane-containing Building Block Leads to Thiol-independent Inhibitors of Phosphoglycerate Mutase

Here we report the construction of an mRNA-encoded library of thioether-closed macrocyclic peptides by using an N-chloroacetyl-cyclopropane-containing exotic initiator whose structure is more constrained than the ordinary N-chloroacetyl-α-amino acid initiators. The use of such an initiator has led to a macrocycle library with significantly suppressed population of lariat-shaped species compared with the conventional libraries. We previously used a conventional library and identified a small lariat thioether-macrocycle with a tail peptide with a C-terminal free Cys whose sidechain plays an essential role in potent inhibitory activity against a parasitic model enzyme, phosphoglycerate mutase. On the other hand, the cyclopropane-containing macrocycle library has yielded a larger thioether-macrocycle lacking a free Cys residue, which exhibits potent inhibitory activity to the same enzyme with a different mode of action. This result indicates that such a cyclopropane-containing macrocycle library would allow us to access mechanistically distinct macrocycles.

Inhibiting Matrix Metalloproteinase-2 Activation by Perturbing Protein-Protein Interactions Using a Cyclic Peptide

We report on a cyclic peptide that inhibits matrix metalloproteinase-2 (MMP2) activation with a low-nM-level potency. This inhibitor specifically binds to the D₅₇₀-A₅₈₃ epitope on proMMP2 and interferes with the protein-protein interaction (PPI) between proMMP2 and tissue inhibitor of metalloproteinases-2 (TIMP2), thereby preventing the TIMP2-assisted proMMP2 activation process. We developed this cyclic peptide inhibitor through an epitope-targeted library screening process and validated its binding to proMMP2. Using a human melanoma cell line, we demonstrated the cyclic peptide's ability to modulate cellular MMP2 activities and inhibit cell migration. These results provide the first successful example of targeting the PPI between proMMP2 and TIMP2, confirming the feasibility of an MMP2 inhibition strategy that has been sought after for 2 decades.

Macrocyclization via C-H functionalization: a new paradigm in macrocycle synthesis

The growing emphasis on macrocycles in engaging difficult therapeutic targets such as protein-protein interactions and GPCRs via preferential adaptation of bioactive and cell penetrating conformations has provided impetus to the search for de novo macrocyclization strategies that are efficient, chemically robust and amenable to diversity creation. An emerging macrocyclization paradigm based on the C-H activation logic, of particular promise in the macrocyclization of complex peptides, has added a new dimension to this pursuit, enabling efficacious access to macrocycles of various sizes and topologies with high atom and step economy. Significant achievements in macrocyclization methodologies and their applications in the synthesis of bioactive natural products and drug-like molecules, employing strategic variations of C-H activation are captured in this review. It is expected that this timely account will foster interest in newer ways of macrocycle construction among practitioners of organic synthesis and chemical biology to advance the field.

Link Between Diabetes and Alzheimer's Disease due to the Shared Amyloid Aggregation and Deposition Involving both Neurodegenerative Changes and Neurovascular Damages

Diabetes and Alzheimer’s disease are two highly prevalent diseases among the aging population and have become major public health concerns in the 21st century, with a significant risk to each other. Both of these diseases are increasingly recognized to be multifactorial conditions. The terms “diabetes type 3” or “brain diabetes” have been proposed in recent years to provide a complete view of the potential common pathogenic mechanisms between these diseases. While insulin resistance or deficiency remains the salient hallmarks of diabetes, cognitive decline and non-cognitive abnormalities such as impairments in visuospatial function, attention, cognitive flexibility, and psychomotor speed are also present. Furthermore, amyloid aggregation and deposition may also be drivers for diabetes pathology. Here, we offer a brief appraisal of social impact and economic burden of these chronic diseases and provide insight into amyloidogenesis through considering recent advances of amyloid-β aggregates on diabetes pathology and islet amyloid polypeptide on Alzheimer’s disease. Exploring the detailed knowledge of molecular interaction between these two amyloidogenic proteins opens new opportunities for therapies and biomarker development.

Peptide-Based Molecular Strategies To Interfere with Protein Misfolding, Aggregation, and Cell Degeneration

Protein misfolding into amyloid fibrils is linked to more than 40 as yet incurable cell- and neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, and type 2 diabetes. So far, however, only one of the numerous anti-amyloid molecules has reached patients. This Minireview gives an overview of molecular strategies and peptide chemistry "tools" to design, develop, and discover peptide-based molecules as anti-amyloid drug candidates. We focus on two major inhibitor rational design strategies: 1) the oldest and most common strategy, based on molecular recognition elements of amyloid self-assembly, and 2) a more recent approach, based on cross-amyloid interactions. We discuss why peptide-based amyloid inhibitors, in particular their advanced generations, can be promising leads or candidates for anti-amyloid drugs as well as valuable tools for deciphering amyloid-mediated cell damage and its link to disease pathogenesis.

Conformational analysis of macrocycles: comparing general and specialized methods

Abstract

Macrocycles represent an important class of medicinally relevant small molecules due to their interesting biological properties. Therefore, a firm understanding of their conformational preferences is important for drug design. Given the importance of macrocycle-protein modelling in drug discovery, we envisaged that a systematic study of both classical and recent specialized methods would provide guidance for other practitioners within the field. In this study we compare the performance of the general, well established conformational analysis methods Monte Carlo Multiple Minimum (MCMM) and Mixed Torsional/Low-Mode sampling (MTLMOD) with two more recent and specialized macrocycle sampling techniques: MacroModel macrocycle Baseline Search (MD/LLMOD) and Prime macrocycle conformational sampling (PRIME-MCS). Using macrocycles extracted from 44 macrocycle-protein X-ray crystallography complexes, we evaluated each method based on their ability to (i) generate unique conformers, (ii) generate unique macrocycle ring conformations, (iii) identify the global energy minimum, (iv) identify conformers similar to the X-ray ligand conformation after Protein Preparation Wizard treatment (X-ray_ppw), and (v) to the X-ray_ppw ring conformation. Computational speed was also considered. In addition, conformational coverage, as defined by the number of conformations identified, was studied. In order to study the relative energies of the bioactive conformations, the energy differences between the global energy minima and the energy minimized X-ray_ppw structures and, the global energy minima and the MCMM-Exhaustive (1,000,000 search steps) generated conformers closest to the X-ray_ppw structure, were calculated and analysed. All searches were performed using relatively short run times (10,000 steps for MCMM, MTLMOD and MD/LLMOD). To assess the performance of the methods, they were compared to an exhaustive MCMM search using 1,000,000 search steps for each of the 44 macrocycles (requiring ca 200 times more CPU time). Prior to our analysis, we also investigated if the general search methods MCMM and MTLMOD could also be optimized for macrocycle conformational sampling. Taken together, our work concludes that the more general methods can be optimized for macrocycle modelling by slightly adjusting the settings around the ring closure bond. In most cases, MCMM and MTLMOD with either standard or enhanced settings performed well in comparison to the more specialized macrocycle sampling methods MD/LLMOD and PRIME-MCS. When using enhanced settings for MCMM and MTLMOD, the X-ray_ppw conformation was regenerated with the greatest accuracy. The, MD/LLMOD emerged as the most efficient method for generating the global energy minima.

Graphic abstract

Electronic supplementary material

The online version of this article (10.1007/s10822-020-00277-2) contains supplementary material, which is available to authorized users.

Efficient syntheses of macrocycles ranging from 22-28 atoms through spontaneous dimerization to yield bis-hydrazones

Acid treatment of a triazine displaying both a tethered acetal and BOC-protected hydrazine group leads to spontaneous condensation to yield macrocyclic dimers in excellent yields and purity. The bis-triazinyl hydrazones that form are characterized by ¹H-NMR, ¹³C-NMR, ¹H-COSY spectroscopy, X-ray diffraction, and mass spectrometry. By varying the length of the tether-the condensation product of an amino acid and amino acetal-rings comprising 22-28 atoms can be accessed. Glycine and β-alanine were used for the amino acid. The amino acetal comprised 2, 3 or 4 carbon atoms in the backbone. High-performance liquid chromatography (HPLC) was employed to assess purity as well as to fingerprint the six homodimeric products. By combining the protected monomers and subjecting them to acid, mixtures of homodimers and heterodimers are obtained. When all six protected monomers are combined, at least 14 of the 21 theoretical dimeric products are observed by HPLC. Single crystal X-ray diffraction and solution NMR studies reveal the diversity of shapes available to these molecules.

DeepMalaria: Artificial Intelligence Driven Discovery of Potent Antiplasmodials

Antimalarial drugs are becoming less effective due to the emergence of drug resistance. Resistance has been reported for all available malaria drugs, including artemisinin, thus creating a perpetual need for alternative drug candidates. The traditional drug discovery approach of high throughput screening (HTS) of large compound libraries for identification of new drug leads is time-consuming and resource intensive. While virtual in silico screening is a solution to this problem, however, the generalization of the models is not ideal. Artificial intelligence (AI), utilizing either structure-based or ligand-based approaches, has demonstrated highly accurate performances in the field of chemical property prediction. Leveraging the existing data, AI would be a suitable alternative to blind-search HTS or fingerprint-based virtual screening. The AI model would learn patterns within the data and help to search for hit compounds efficiently. In this work, we introduce DeepMalaria, a deep-learning based process capable of predicting the anti-Plasmodium falciparum inhibitory properties of compounds using their SMILES. A graph-based model is trained on 13,446 publicly available antiplasmodial hit compounds from GlaxoSmithKline (GSK) dataset that are currently being used to find novel drug candidates for malaria. We validated this model by predicting hit compounds from a macrocyclic compound library and already approved drugs that are used for repurposing. We have chosen macrocyclic compounds as these ligand-binding structures are underexplored in malaria drug discovery. The in silico pipeline for this process also consists of additional validation of an in-house independent dataset consisting mostly of natural product compounds. Transfer learning from a large dataset was leveraged to improve the performance of the deep learning model. To validate the DeepMalaria generated hits, we used a commonly used SYBR Green I fluorescence assay based phenotypic screening. DeepMalaria was able to detect all the compounds with nanomolar activity and 87.5% of the compounds with greater than 50% inhibition. Further experiments to reveal the compounds’ mechanism of action have shown that not only does one of the hit compounds, DC-9237, inhibits all asexual stages of Plasmodium falciparum, but is a fast-acting compound which makes it a strong candidate for further optimization.

Mechanisms Inspired Targeting Peptides

Peptides, as a large group of molecules, are composed of amino acid residues and can be divided into linear or cyclic peptides according to the structure. Over 13,000 molecules of natural peptides have been found and many of them have been well studied. In artificial peptide libraries, the number of peptide diversity could be up to 1 × 10¹³. Peptides have more complex structures and higher affinity to target proteins comparing with small molecular compounds. Recently, the development of targeting cancer immune checkpoint (CIP) inhibitors is having a very important role in tumor therapy. Peptides targeting ligands or receptors in CIP have been designed based on three-dimensional structures of target proteins or directly selected by random peptide libraries in biological display systems. Most of these targeting peptides work as inhibitors of protein-protein interaction and improve CD8+ cytotoxic T-lymphocyte (CTL) activation in the tumor microenvironment, for example, PKHB1, Ar5Y4 and TPP1. Peptides could be designed to regulate CIP protein degradation in vivo, such as PD-LYSO and PD-PALM. Besides its use in developing therapeutic drugs for targeting CIP, targeting peptides could be used in drug's targeted delivery and diagnosis in tumor immune therapy.

A Perspective on the Development of TGF-β Inhibitors for Cancer Treatment

Transforming growth factor (TGF)-β is a secreted multifunctional cytokine that signals via plasma membrane TGF-β type I and type II receptors and intercellular SMAD transcriptional effectors. Aberrant inter- and intracellular TGF-β signaling can contribute to cancer progression. In normal cells and early stages of cancer, TGF-β can stimulate epithelial growth arrest and elicit a tumor suppressor function. However, in late stages of cancer, when the cytostatic effects of TGF-β in cancer cells are blocked, TGF-β signaling can act as tumor promoter by its ability to stimulate epithelial-to-mesenchymal transition of cancer cells, by stimulating angiogenesis, and by promoting evasion of immune responses. In this review, we will discuss the rationale and challenges of targeting TGF-β signaling in cancer and summarize the clinical status of TGF-β signaling inhibitors that interfere with TGFβ bioavailability, TGF-βreceptor interaction, or TGF-β receptor kinase function. Moreover, we will discuss targeting of TGF-β signaling modulators and downstream effectors as well as alternative approaches by using promising technologies that may lead to entirely new classes of drugs.

A Perspective on the Development of TGF-β Inhibitors for Cancer Treatment

Transforming growth factor (TGF)-β is a secreted multifunctional cytokine that signals via plasma membrane TGF-β type I and type II receptors and intercellular SMAD transcriptional effectors. Aberrant inter- and intracellular TGF-β signaling can contribute to cancer progression. In normal cells and early stages of cancer, TGF-β can stimulate epithelial growth arrest and elicit a tumor suppressor function. However, in late stages of cancer, when the cytostatic effects of TGF-β in cancer cells are blocked, TGF-β signaling can act as tumor promoter by its ability to stimulate epithelial-to-mesenchymal transition of cancer cells, by stimulating angiogenesis, and by promoting evasion of immune responses. In this review, we will discuss the rationale and challenges of targeting TGF-β signaling in cancer and summarize the clinical status of TGF-β signaling inhibitors that interfere with TGF−β bioavailability, TGF-β/receptor interaction, or TGF-β receptor kinase function. Moreover, we will discuss targeting of TGF-β signaling modulators and downstream effectors as well as alternative approaches by using promising technologies that may lead to entirely new classes of drugs.

Modelling the binding mode of macrocycles: Docking and conformational sampling

Drug discovery is increasingly tackling challenging protein binding sites regarding molecular recognition and druggability, including shallow and solvent-exposed protein-protein interaction interfaces. Macrocycles are emerging as promising chemotypes to modulate such sites. Despite their chemical complexity, macrocycles comprise important drugs and offer advantages compared to non-cyclic analogs, hence the recent impetus in the medicinal chemistry of macrocycles. Elaboration of macrocycles, or constituent fragments, can strongly benefit from knowledge of their binding mode to a target. When such information from X-ray crystallography is elusive, computational docking can provide working models. However, few studies have explored docking protocols for macrocycles, since conventional docking methods struggle with the conformational complexity of macrocycles, and also potentially with the shallower topology of their binding sites. Indeed, macrocycle binding mode prediction with the mainstream docking software GOLD has hardly been explored. Here, we present an in-depth study of macrocycle docking with GOLD and the ChemPLP scores. First, we summarize the thorough curation of a test set of 41 protein-macrocycle X-ray structures, raising the issue of lattice contacts with such systems. Rigid docking of the known bioactive conformers was successful (three top ranked poses) for 92.7% of the systems, in absence of crystallographic waters. Thus, without conformational search issues, scoring performed well. However, docking success dropped to 29.3% with the GOLD built-in conformational search. Yet, the success rate doubled to 58.5% when GOLD was supplied with extensive conformer ensembles docked rigidly. The reasons for failure, sampling or scoring, were analyzed, exemplified with particular cases. Overall, binding mode prediction of macrocycles remains challenging, but can be much improved with tailored protocols. The analysis of the interplay between conformational sampling and docking will be relevant to the prospective modelling of macrocycles in general.

Multi-targeting protein-protein interaction inhibitors: Evolution of macrocyclic ligands with embedded carbohydrates (MECs) to improve selectivity

Compounds targeting multiple proteins can have synergistic effects and are therefore of interest in medicinal chemistry. At the same time, inhibiting protein-protein interactions (PPI) is increasingly desired in the treatment of disorders or diseases. The development of non-peptidomimetic inhibitors is still a challenge. Herein we investigate macrocyclic scaffolds with one or two embedded carbohydrates (MECs) that present amino acid side chains, or related isosteres, as pharmacophoric groups. Firstly, retroscreening of the previously reported eannaphane-40 (E40, 40), a MEC presenting two pharmacophoric groups, against a set of 55 receptor-subtypes led to a finding of sub-micromolar inhibitory activity for E40 against three serotonergic isoforms (5HT_1A/_2A/2B) as well as the Na⁺ channel and the NK-2 receptor. We synthesised MECs with an additional pharmacophoric group compared to E40, with a view to identifying compounds where the selectivity profile was altered among the protein hits from the retroscreening. MECs were produced based on scaffolds with two monosaccharide residues, leading to the incorporation of a third pharmacophoric group. Later, homology models were prepared for four proteins (5HT_1A, 5HT_2A, NK₂ and site-2 of the sodium channel) whose 3D structure is unknown. Inverse docking of the synthesised compounds led to the selection of a new MEC (MEC-B) for protein binding assays. MEC-B was found to have its selectivity profile modulated, in line with docking prediction, compared to E40. MEC-B is dual inhibitor of both 5-HT_1A and the sodium channel with improved selectivity for these proteins compared to 5-HT_2A/2B/2C, 5-HT transporter and NK₂ receptor. Thus, a new multitargeting compound, with an improved selectivity profile was identified, based on a MEC peptidomimetic scaffold.

Cyclic Cell-Penetrating Peptides as Efficient Intracellular Drug Delivery Tools

Cyclic cell-penetrating peptides are relatively a newer class of peptides that have a huge potential for the intracellular delivery of therapeutic agents aimed at treating challenging ailments like multidrug-resistant bacterial diseases, cancer, and HIV infection. Cell-penetrating peptides (CPPs) have been extensively explored as intracellular delivery vehicles; however, they have some inherent limitations like poor stability, endosomal entrapment, toxicity, and suboptimal cell penetration. Owing to their favorable properties that avoid these limitations, cyclic CPPs can provide a good alternative to linear CPPs. Several Reviews have been published in the past decade that cover CPPs and cyclic peptides independently. To the best of our knowledge, this is one of the first Reviews that covers cyclic CPPs comprehensively in the light of studies published so far. In this Review, we have detailed examples of cyclic CPPs, their structures, and cyclization strategies followed by a detailed account of their advantages over their linear counterparts. A hot area in cyclic CPPs is the exploration of cell-penetration mechanisms; this Review highlights this topic in detail. Finally, we will review the applications of cyclic CPPs, followed by conclusions and future prospects.

The 1,3-diyne linker as a rigid "i,i+7" staple for α-helix stabilization: Stereochemistry at work

Short alphahelical peptide sequences were stabilized through Glaser-Hay couplings of propargylated l- and/or d-serine residues at positions i and i+7. NMR analysis confirmed a full stabilization of the helical structure when a d-Ser (i), l-Ser (i+7) combination was applied. In case two l-Ser residues were involved in the cyclization, the helical conformation is disrupted outside the peptide's macrocycle.

Photoredox Ni-catalyzed peptide C(sp2)-O cross-coupling: from intermolecular reactions to side chain-to-tail macrocyclization

Ni/photoredox (4DPAIPN) dual catalysis enabled challenging peptide C(sp2)-O coupling reactions. Successful cross-coupling reactions were demonstrated with highly functionalized alcohols including side chains of amino acids (i.e., serine, threonine, tyrosine), trans-4-hydroxy-l-proline, alkyl alcohols, alkynylated alcohols, and carbohydrates. Coupling reactions between bromobenzoyl-capped peptides containing various side chains and either a protected serine building block or a serine-containing dipeptide also proceeded efficiently. Chemoselective C-O coupling (over C-N) was achieved in intermolecular reactions in the presence of a C-terminal primary amide. Furthermore, by judicious structural design in combination with computational modeling, we demonstrated side chain-to-tail macrocyclization of peptides containing a β-turn motif via C-O coupling. The methodology developed in this work brings new opportunities for late-stage diversification of complex linear and macrocyclic peptides.

Overcoming Endosomal Entrapment in Drug Delivery

Intracellular delivery of biological agents such as peptides, proteins, and nucleic acids generally rely on the endocytic pathway as the major uptake mechanism, resulting in their entrapment inside the endosome and lysosome. The recent discovery of cell-penetrating molecules of exceptionally high endosomal escape and cytosolic delivery efficiencies and elucidation of their mechanism of action represent major breakthroughs in this field. In this Topical Review, we provide an overview of the recent progress in understanding and enhancing the endosomal escape process and the new opportunities opened up by these recent findings.

Conformator: A Novel Method for the Generation of Conformer Ensembles

Computer-aided drug design methods such as docking, pharmacophore searching, 3D database searching, and the creation of 3D-QSAR models need conformational ensembles to handle the flexibility of small molecules. Here, we present Conformator, an accurate and effective knowledge-based algorithm for generating conformer ensembles. With 99.9% of all test molecules processed, Conformator stands out by its robustness with respect to input formats, molecular geometries, and the handling of macrocycles. With an extended set of rules for sampling torsion angles, a novel algorithm for macrocycle conformer generation, and a new clustering algorithm for the assembly of conformer ensembles, Conformator reaches a median minimum root-mean-square deviation (measured between protein-bound ligand conformations and ensembles of a maximum of 250 conformers) of 0.47 Å with no significant difference to the highest-ranked commercial algorithm OMEGA and significantly higher accuracy than seven free algorithms, including the RDKit DG algorithm. Conformator is freely available for noncommercial use and academic research.

Bioluminescence Resonance Energy Transfer as a Method to Study Protein-Protein Interactions: Application to G Protein Coupled Receptor Biology

The bioluminescence resonance energy transfer (BRET) approach involves resonance energy transfer between a light-emitting enzyme and fluorescent acceptors. The major advantage of this technique over biochemical methods is that protein-protein interactions (PPI) can be monitored without disrupting the natural environment, frequently altered by detergents and membrane preparations. Thus, it is considered as one of the most versatile technique for studying molecular interactions in living cells at "physiological" expression levels. BRET analysis has been applied to study many transmembrane receptor classes including G-protein coupled receptors (GPCR). It is well established that these receptors may function as dimeric/oligomeric forms and interact with multiple effectors to transduce the signal. Therefore, they are considered as attractive targets to identify PPI modulators. In this review, we present an overview of the different BRET systems developed up to now and their relevance to identify inhibitors/modulators of protein⁻protein interaction. Then, we introduce the different classes of agents that have been recently developed to target PPI, and provide some examples illustrating the use of BRET-based assays to identify and characterize innovative PPI modulators in the field of GPCRs biology. Finally, we discuss the main advantages and the limits of BRET approach to characterize PPI modulators.

Macrocyclisation of small peptides enabled by oxetane incorporation

Cyclic peptides are an important source of new drugs but are challenging to produce synthetically. We show that head-to-tail peptide macrocyclisations are greatly improved, as measured by isolated yields, reaction rates and product distribution, by substitution of one of the backbone amide C[double bond, length as m-dash]O bonds with an oxetane ring. The cyclisation precursors are easily made by standard solution- or solid-phase peptide synthesis techniques. Macrocyclisations across a range of challenging ring sizes (tetra-, penta- and hexapeptides) are enabled by incorporation of this turn-inducing element. Oxetane incorporation is shown to be superior to other established amino acid modifications such as N-methylation. The positional dependence of the modification on cyclisation efficiency is mapped using a cyclic peptide of sequence LAGAY. We provide the first direct experimental evidence that oxetane modification induces a turn in linear peptide backbones, through the observation of d _NN (i, i + 2) and d _αN (i, i + 2) NOEs, which offers an explanation for these improvements. For cyclic peptide, cLAGAY, a combination of NMR derived distance restraints and molecular dynamics simulations are used to show that this modification alters the backbone conformation in proximity to the oxetane, with the flexibility of the ring reduced and a new intramolecular H-bond established. Finally, we incorporated an oxetane into a cyclic pentapeptide inhibitor of Aminopeptidase N, a transmembrane metalloprotease overexpressed on the surface of cancer cells. The inhibitor, cCNGRC, displayed similar IC₅₀ values in the presence or absence of an oxetane at the glycine residue, indicating that bioactivity is fully retained upon amide C[double bond, length as m-dash]O bond replacement.

Designing Cell-Permeable Macrocyclic Peptides

Peptides provide an attractive modality for targeting challenging drug targets such as intracellular protein-protein interactions. Unfortunately, peptides are generally impermeable to the cell membrane and inherently susceptible to proteolytic degradation in vivo. Macrocyclization of peptides greatly increases their proteolytic stability and in some cases the cell-penetrating activity. Conjugation of peptidyl cargoes to cyclic cell-penetrating peptides has resulted in potent, cell-permeable, and metabolically stable macrocyclic peptides against intracellular protein targets. Proper conjugation/integration of a peptidyl cargo with a cyclic cell-penetrating peptide is critical to retain the activity of each component and generate a biologically active macrocyclic peptide. This chapter describes the different conjugation strategies that have been developed (including endocyclic, bicyclic, and reversible cyclization methods) and the detailed protocols for their preparation.

Cell-Permeable Bicyclic Peptidyl Inhibitors against NEMO-IκB Kinase Interaction Directly from a Combinatorial Library

Macrocyclic peptides are capable of binding to flat protein surfaces such as the interfaces of protein-protein interactions with antibody-like affinity and specificity, but generally lack cell permeability in order to access intracellular targets. In this work, we designed and synthesized a large combinatorial library of cell-permeable bicyclic peptides, in which the first ring consisted of randomized peptide sequences for potential binding to a target of interest, while the second ring featured a family of different cell-penetrating motifs, for both cell penetration and target binding. The library was screened against the IκB kinase α/β (IKKα/β)-binding domain of NF-κB essential modulator (NEMO), resulting in the discovery of several cell-permeable bicyclic peptides, which inhibited the NEMO-IKKβ interaction with low μM IC50 values. Further optimization of one of the hits led to a relatively potent and cell-permeable NEMO inhibitor (IC50 = 1.0 μM), which selectively inhibited canonical NF-κB signaling in mammalian cells and the proliferation of cisplatin-resistant ovarian cancer cells. The inhibitor provides a useful tool for investigating the biological functions of NEMO/NF-κB and a potential lead for further development of a novel class of anti-inflammatory and anticancer drugs.

Inhibitors and chemical probes for molecular chaperone networks

The molecular chaperones are central mediators of protein homeostasis. In that role, they engage in widespread protein-protein interactions (PPIs) with each other and with their "client" proteins. Together, these PPIs form the backbone of a network that ensures proper vigilance over the processes of protein folding, trafficking, quality control, and degradation. The core chaperones, such as the heat shock proteins Hsp60, Hsp70, and Hsp90, are widely expressed in most tissues, yet there is growing evidence that the PPIs among them may be re-wired in disease conditions. This possibility suggests that these PPIs, and perhaps not the individual chaperones themselves, could be compelling drug targets. Indeed, recent efforts have yielded small molecules that inhibit (or promote) a subset of inter-chaperone PPIs. These chemical probes are being used to study chaperone networks in a range of models, and the successes with these approaches have inspired a community-wide objective to produce inhibitors for a broader set of targets. In this Review, we discuss progress toward that goal and point out some of the challenges ahead.

Designed Macrocyclic Peptides as Nanomolar Amyloid Inhibitors Based on Minimal Recognition Elements

Amyloid self-assembly is linked to the pathogenesis of Alzheimer's disease (AD) and type 2 diabetes (T2D), but so far, no anti-amyloid compound has reached the clinic. Macrocyclic peptides belong to the most attractive drug candidates. Herein we present macrocyclic peptides (MCIPs) designed using minimal IAPP-derived recognition elements as a novel class of nanomolar amyloid inhibitors of both Aβ40(42) and IAPP or Aβ40(42) alone and show that chirality controls inhibitor selectivity. Sequence optimization led to the discovery of an Aβ40(42)-selective MCIP exhibiting high proteolytic stability in human plasma and human blood-brain barrier (BBB) crossing ability in a cell model, two highly desirable properties for anti-amyloid AD drugs. Owing to their favorable properties, MCIPs should serve as leads for macrocyclic peptide-based anti-amyloid drugs and scaffolds for the design of small-molecule peptidomimetics for targeting amyloidogenesis in AD or in both AD and T2D.

Inhibitors of protein-protein interactions (PPIs): an analysis of scaffold choices and buried surface area

Protein-protein interactions (PPI) were once considered 'undruggable', but clinical successes, driven by advanced methods in drug discovery, have challenged that notion. Here, we review the last three years of literature on PPI inhibitors to understand what is working and why. From the 66 recently reported PPI inhibitors, we found that the average molecular weight was significantly greater than 500Da, but that this trend was driven, in large part, by the contribution of peptide-based compounds. Despite differences in average molecular weight, we found that compounds based on small molecules or peptides were almost equally likely to be potent inhibitors (K_D<1μM). Finally, we found PPIs with buried surface area (BSA) less than 2000Ų were more likely to be inhibited by small molecules, while PPIs with larger BSA values were typically inhibited by peptides. PPIs with BSA values over 4000Ų seemed to create a particular challenge, especially for orthosteric small molecules. Thus, it seems important to choose the inhibitor scaffold based on the properties of the target interaction. Moreover, this survey suggests a (more nuanced) conclusion to the question of whether PPIs are good drug targets; namely, that some PPIs are readily 'druggable' given the right choice of scaffold, while others still seem to deserve the 'undruggable' moniker.

Non-competitive cyclic peptides for targeting enzyme-substrate complexes

Affinity reagents are of central importance for selectively identifying proteins and investigating their interactions. We report on the development and use of cyclic peptides, identified by mRNA display-based RaPID methodology, that are selective for, and tight binders of, the human hypoxia inducible factor prolyl hydroxylases (PHDs) - enzymes crucial in hypoxia sensing. Biophysical analyses reveal the cyclic peptides to bind in a distinct site, away from the enzyme active site pocket, enabling conservation of substrate binding and catalysis. A biotinylated cyclic peptide captures not only the PHDs, but also their primary substrate hypoxia inducible factor HIF1-α. Our work highlights the potential for tight, non-active site binding cyclic peptides to act as promising affinity reagents for studying protein-protein interactions.

A structural study of the complex between neuroepithelial cell transforming gene 1 (Net1) and RhoA reveals a potential anticancer drug hot spot

The GTPase RhoA is a major player in many different regulatory pathways. RhoA catalyzes GTP hydrolysis, and its catalysis is accelerated when RhoA forms heterodimers with proteins of the guanine nucleotide exchange factor (GEF) family. Neuroepithelial cell transforming gene 1 (Net1) is a RhoA-interacting GEF implicated in cancer, but the structural features supporting the RhoA/Net1 interaction are unknown. Taking advantage of a simple production and purification process, here we solved the structure of a RhoA/Net1 heterodimer with X-ray crystallography at 2-Å resolution. Using a panel of several techniques, including molecular dynamics simulations, we characterized the RhoA/Net1 interface. Moreover, deploying an extremely simple peptide-based scanning approach, we found that short peptides (penta- to nonapeptides) derived from the protein/protein interaction region of RhoA could disrupt the RhoA/Net1 interaction and thereby diminish the rate of nucleotide exchange. The most inhibitory peptide, EVKHF, spanning residues 102-106 in the RhoA sequence, displayed an IC₅₀ of ∼100 μm without further modifications. The peptides identified here could be useful in further investigations of the RhoA/Net1 interaction region. We propose that our structural and functional insights might inform chemical approaches for transforming the pentapeptide into an optimized pseudopeptide that antagonizes Net1-mediated RhoA activation with therapeutic anticancer potential.

Using Peptidomimetics and Constrained Peptides as Valuable Tools for Inhibiting Protein⁻Protein Interactions

Protein–protein interactions (PPIs) are tremendously important for the function of many biological processes. However, because of the structure of many protein–protein interfaces (flat, featureless and relatively large), they have largely been overlooked as potential drug targets. In this review, we highlight the current tools used to study the molecular recognition of PPIs through the use of different peptidomimetics, from small molecules and scaffolds to peptides. Then, we focus on constrained peptides, and in particular, ways to constrain α-helices through stapling using both one- and two-component techniques.