Crystal Structures of Protein-Bound Cyclic Peptides

PepExplainer: An explainable deep learning model for selection-based macrocyclic peptide bioactivity prediction and optimization

Macrocyclic peptides possess unique features, making them highly promising as a drug modality. However, evaluating their bioactivity through wet lab experiments is generally resource-intensive and time-consuming. Despite advancements in artificial intelligence (AI) for bioactivity prediction, challenges remain due to limited data availability and the interpretability issues in deep learning models, often leading to less-than-ideal predictions. To address these challenges, we developed PepExplainer, an explainable graph neural network based on substructure mask explanation (SME). This model excels at deciphering amino acid substructures, translating macrocyclic peptides into detailed molecular graphs at the atomic level, and efficiently handling non-canonical amino acids and complex macrocyclic peptide structures. PepExplainer's effectiveness is enhanced by utilizing the correlation between peptide enrichment data from selection-based focused library and bioactivity data, and employing transfer learning to improve bioactivity predictions of macrocyclic peptides against IL-17C/IL-17 RE interaction. Additionally, PepExplainer underwent further validation for bioactivity prediction using an additional set of thirteen newly synthesized macrocyclic peptides. Moreover, it enabled the optimization of the IC50 of a macrocyclic peptide, reducing it from 15 nM to 5.6 nM based on the contribution score provided by PepExplainer. This achievement underscores PepExplainer's skill in deciphering complex molecular patterns, highlighting its potential to accelerate the discovery and optimization of macrocyclic peptides.

An N-ortho-nitrobenzylated benzanilide amino acid enables control of the conformation and membrane permeability of cyclic peptides

We designed and synthesized an N-ortho-nitrobenzylated benzanilide-based amino acid having a cis-amide structure that facilitates cyclization of peptides containing it. Photo-induced removal of the nitrobenzyl group from this residue in the resulting cyclized peptides dramatically alters their conformation and passive membrane permeability via complete cis-amide to trans-amide conversion.

Molecular Mechanism of P53 Peptide Permeation through Lipid Membranes from Solid-State NMR Spectroscopy and Molecular Dynamics Simulations

Macrocyclic peptides show promise in targeting high-value therapeutically relevant binding sites due to their high affinity and specificity. However, their clinical application is often hindered by low membrane permeability, which limits their effectiveness against intracellular targets. Previous studies focused on peptide conformations in various solvents, leaving a gap in understanding their interactions with and translocation through lipid bilayers. Addressing this, our study explores the membrane interactions of stapled peptides, a subclass of macrocyclic peptides, using solid-state nuclear magnetic resonance (ssNMR) spectroscopy and molecular dynamics (MD) simulations. We conducted ssNMR measurements on ATSP-7041M, a prototypical stapled peptide, to understand its interaction with lipid membranes, leading to an MD-informed model for peptide membrane permeation. Our findings reveal that ATSP-7041M adopts a stable α-helical structure upon membrane binding, facilitated by a cation-π interaction between its phenylalanine side chain and the lipid headgroup. This interaction makes the membrane-bound state energetically favorable, facilitating membrane affinity and insertion. The bound peptide displayed asymmetric insertion depths, with the C-terminus penetrating deeper (approximately 9 Å) than the N-terminus (approximately 4.3 Å) relative to the lipid headgroups. Contrary to expectations, peptide dynamics was not hindered by membrane binding and exhibited rapid motions similar to cell-penetrating peptides. These dynamic interactions and peptide-lipid affinity appear to be crucial for membrane permeation. MD simulations indicated a thermodynamically stable transmembrane conformation of ATSP-7041M, reducing the energy barrier for translocation. Our study offers an in silico view of ATSP-7041M's translocation from the extracellular to the intracellular region, highlighting the significance of peptide-lipid interactions and dynamics in enabling peptide transit through membranes.

A facile strategy for the construction of a phage display cyclic peptide library for the selection of functional macrocycles

Cyclic peptides represent invaluable scaffolds in biological affinity, providing diverse collections for discovering functional molecules targeting challenging biological entities and protein-protein interactions. The field increasingly focuses on developing cyclization strategies and chemically modified combinatorial libraries in conjunction with M13 phage display, to identify macrocyclic peptide inhibitors for traditionally challenging targets. Here, we introduce a cyclization strategy utilizing ortho-phthalaldehyde (OPA) for the discovery of active macrocycles characterized by asymmetric scaffolds with side-chain cyclization. Through this approach, aldehyde groups attached to free molecules sequentially attack the ε-amine of lysine and the thiol of cysteine, facilitating the rapid cyclization of genetically encoded linear precursor libraries displayed on phage particles. The construction of a 109-member library and subsequent screening successfully identified cyclic peptide binders targeting three therapeutically relevant proteins: PTP1B, NEK7, and hKeap1. The results confirm the efficacy in rapidly obtaining active ligands with micromolar potency. This work provides a fast and efficient operable high-throughput platform for screening functional peptide macrocycles, which hold promise for broad application in therapeutics, chemically biological probes, and disease diagnosis.

Harnessing antimicrobial peptides in endodontics

Endodontic therapy includes various procedures such as vital pulp therapy, root canal treatment and retreatment, surgical endodontic treatment and regenerative endodontic procedures. Disinfection and tissue repair are crucial for the success of these therapies, necessitating the development of therapeutics that can effectively target microbiota, eliminate biofilms, modulate inflammation and promote tissue repair. However, no current endodontic agents can achieve these goals. Antimicrobial peptides (AMPs), which are sequences of amino acids, have gained attention due to their unique advantages, including reduced susceptibility to drug resistance, broad-spectrum antibacterial properties and the ability to modulate the immune response of the organism effectively. This review systematically discusses the structure, mechanisms of action, novel designs and limitations of AMPs. Additionally, it highlights the efforts made by researchers to overcome peptide shortcomings and emphasizes the potential applications of AMPs in endodontic treatments.

Selection of Peptide-Bismuth Bicycles Using Phage Display

Cysteine conjugation is widely used to constrain phage displayed peptides for the selection of cyclic peptides against specific targets. In this study, the nontoxic Bi3+ ion was used as a cysteine conjugation reagent to cross-link peptide libraries without compromising phage infectivity. We constructed a randomized 3-cysteine peptide library and cyclized it with Bi3+, followed by a selection against the maltose-binding protein as a model target. Next-generation sequencing of selection samples revealed the enrichment of peptides containing clear consensus sequences. Chemically synthesized linear and Bi3+ cyclized peptides were used for affinity validation. The cyclized peptide showed a hundred-fold better affinity (0.31 ± 0.04 μM) than the linear form (39 ± 6 μM). Overall, our study proved the feasibility of developing Bi3+ constrained bicyclic peptides against a specific target using phage display, which would potentially accelerate the development of new peptide-bismuth bicycles for therapeutic or diagnostic applications.

Asparaginyl Endopeptidase-Mediated Peptide Cyclization for Phage Display

We report here an enzymatic strategy for asparaginyl endopeptidase-mediated peptide cyclization. Incorporation of chloroacetyl groups into the recognition sequence of OaAEP1 enabled intramolecular cyclization with Cys residues. Combining this strategy and phage display, we identified nanomolar macrocyclic peptide ligands targeting TEAD4. One of the bicyclic peptides binds to TEAD4 with a KD value of 139 nM, 16 times lower than its linear analogue, demonstrating the utility of this platform in discovering high-affinity macrocyclic peptide ligands.

Comprehensive Evaluation of 10 Docking Programs on a Diverse Set of Protein-Cyclic Peptide Complexes

Cyclic peptides have emerged as a highly promising class of therapeutic molecules owing to their favorable pharmacokinetic properties, including stability and permeability. Currently, many clinically approved cyclic peptides are derived from natural products or their derivatives, and the development of molecular docking techniques for cyclic peptide discovery holds great promise for expanding the applications and potential of this class of molecules. Given the availability of numerous docking programs, there is a pressing need for a systematic evaluation of their performance, specifically on protein-cyclic peptide systems. In this study, we constructed an extensive benchmark data set called CPSet, consisting of 493 protein-cyclic peptide complexes. Based on this data set, we conducted a comprehensive evaluation of 10 docking programs, including Rosetta, AutoDock CrankPep, and eight protein-small molecule docking programs (i.e., AutoDock, AudoDock Vina, Glide, GOLD, LeDock, rDock, MOE, and Surflex). The evaluation encompassed the assessment of the sampling power, docking power, and scoring power of these programs. The results revealed that all of the tested protein-small molecule docking programs successfully sampled the binding conformations when using the crystal conformations as the initial structures. Among them, rDock exhibited outstanding performance, achieving a remarkable 94.3% top-100 sampling success rate. However, few programs achieved successful predictions of the binding conformations using tLEaP-generated conformations as the initial structures. Within this scheme, AutoDock CrankPep yielded the highest top-100 sampling success rate of 29.6%. Rosetta's scoring function outperformed the others in selecting optimal conformations, resulting in an impressive top-1 docking success rate of 87.6%. Nevertheless, all the tested scoring functions displayed limited performance in predicting binding affinity, with MOE@Affinity dG exhibiting the highest Pearson's correlation coefficient of 0.378. It is therefore suggested to use an appropriate combination of different docking programs for given tasks in real applications. We expect that this work will offer valuable insights into selecting the appropriate docking programs for protein-cyclic peptide complexes.

Mechanism of RGD-conjugated nanodevice binding to its target protein integrin αVβ3 by atomistic molecular dynamics and machine learning

Active targeting strategies have been proposed to enhance the selective uptake of nanoparticles (NPs) by diseased cells, and recent experimental findings have proven the effectiveness of this approach. However, no mechanistic studies have yet revealed the atomistic details of the interactions between ligand-activated NPs and integrins. As a case study, here we investigate, by means of advanced molecular dynamics simulations (MD) and machine learning methods (namely equilibrium MD, binding free energy calculations and training of self-organized maps), the interaction of a cyclic-RGD-conjugated PEGylated TiO2 NP (the nanodevice) with the extracellular segment of integrin αVβ3 (the target), the latter experimentally well-known to be over-expressed in several solid tumors. Firstly, we proved that the cyclic-RGD ligand binding to the integrin pocket is established and kept stable even in the presence of the cumbersome realistic model of the nanodevice. In this respect, the unsupervised machine learning analysis allowed a detailed comparison of the ligand/integrin binding in the presence and in the absence of the nanodevice, which unveiled differences in the chemical features. Then, we discovered that unbound cyclic RGDs conjugated to the NP largely contribute to the interactions between the nanodevice and the integrin. Finally, by increasing the density of cyclic RGDs on the PEGylated TiO2 NP, we observed a proportional enhancement of the nanodevice/target binding. All these findings can be exploited to achieve an improved targeting selectivity and cellular uptake, and thus a more successful clinical outcome.

Discovery and Development of Cyclic Peptide Proteasome Stimulators

The proteasome degrades proteins, which is essential for cellular homeostasis. Ubiquitin independent proteolysis degrades highly disordered and misfolded proteins. A decline of proteasomal activity has been associated with multiple neurodegenerative diseases due to the accumulation of misfolded proteins. In this work, cyclic peptide proteasome stimulators (CyPPSs) that enhance the clearance of misfolded proteins were discovered. In the initial screen of predicted natural products (pNPs), several cyclic peptides were found to stimulate the 20S core particle (20S CP). Development of a robust structural activity relationship led to the identification of potent, cell permeable CyPPSs. In vitro assays revealed that CyPPSs stimulate degradation of highly disordered and misfolded proteins without affecting ordered proteins. Furthermore, using a novel flow-based assay for proteasome activity, several CyPPSs were found to stimulate the 20S CP in cellulo. Overall, this work describes the development of CyPPSs as chemical tools capable of stimulating the proteasome and provides strong support for proteasome stimulation as a therapeutic strategy for neurodegenerative diseases.

Unlocking novel therapies: cyclic peptide design for amyloidogenic targets through synergies of experiments, simulations, and machine learning

Existing therapies for neurodegenerative diseases like Parkinson's and Alzheimer's address only their symptoms and do not prevent disease onset. Common therapeutic agents, such as small molecules and antibodies struggle with insufficient selectivity, stability and bioavailability, leading to poor performance in clinical trials. Peptide-based therapeutics are emerging as promising candidates, with successful applications for cardiovascular diseases and cancers due to their high bioavailability, good efficacy and specificity. In particular, cyclic peptides have a long in vivo stability, while maintaining a robust antibody-like binding affinity. However, the de novo design of cyclic peptides is challenging due to the lack of long-lived druggable pockets of the target polypeptide, absence of exhaustive conformational distributions of the target and/or the binder, unknown binding site, methodological limitations, associated constraints (failed trials, time, money) and the vast combinatorial sequence space. Hence, efficient alignment and cooperation between disciplines, and synergies between experiments and simulations complemented by popular techniques like machine-learning can significantly speed up the therapeutic cyclic-peptide development for neurodegenerative diseases. We review the latest advancements in cyclic peptide design against amyloidogenic targets from a computational perspective in light of recent advancements and potential of machine learning to optimize the design process. We discuss the difficulties encountered when designing novel peptide-based inhibitors and we propose new strategies incorporating experiments, simulations and machine learning to design cyclic peptides to inhibit the toxic propagation of amyloidogenic polypeptides. Importantly, these strategies extend beyond the mere design of cyclic peptides and serve as template for the de novo generation of (bio)materials with programmable properties.

Cyclic Peptides for Drug Development

Cyclic peptides are fascinating molecules abundantly found in nature and exploited as molecular format for drug development as well as other applications, ranging from research tools to food additives. Advances in peptide technologies made over many years through improved methods for synthesis and drug development have resulted in a steady stream of new drugs, with an average of around one cyclic peptide drug approved per year. Powerful technologies for screening random peptide libraries, and de novo generating ligands, have enabled the development of cyclic peptide drugs independent of naturally derived molecules and now offer virtually unlimited development opportunities. In this review, we feature therapeutically relevant cyclic peptides derived from nature and discuss the unique properties of cyclic peptides, the enormous technological advances in peptide ligand development in recent years, and current challenges and opportunities for developing cyclic peptides that address unmet medical needs.

Biocatalytic cyclization of small macrolactams by a penicillin-binding protein-type thioesterase

Macrocyclic peptides represent promising scaffolds for chemical tools and potential therapeutics. Synthetic methods for peptide macrocyclization are often hampered by C-terminal epimerization and oligomerization, leading to difficult scalability. While chemical strategies to circumvent this issue exist, they often require specific amino acids to be present in the peptide sequence. Herein, we report the characterization of Ulm16, a peptide cyclase belonging to the penicillin-binding protein-type class of thioesterases that catalyze head-to-tail macrolactamization of nonribosmal peptides. Ulm16 efficiently cyclizes various nonnative peptides ranging from 4 to 6 amino acids with catalytic efficiencies of up to 3 × 106 M-1 s-1. Unlike many previously described homologs, Ulm16 tolerates a variety of C- and N-terminal amino acids. The crystal structure of Ulm16, along with modeling of its substrates and site-directed mutagenesis, allows for rationalization of this wide substrate scope. Overall, Ulm16 represents a promising tool for the biocatalytic production of macrocyclic peptides.

Development and Challenges of Cyclic Peptides for Immunomodulation

Cyclic peptides are polypeptide chains formed by cyclic sequences of amide bonds between protein-derived or non-protein-derived amino acids. Compared to linear peptides, cyclic peptides offer several unique advantages, such as increased stability, stronger affinity, improved selectivity, and reduced toxicity. Cyclic peptide has been proved to have a promising application prospect in the medical field. In addition, this paper mainly describes that cyclic peptides play an important role in anti-cancer, anti-inflammatory, anti-virus, treatment of multiple sclerosis and membranous nephropathy through immunomodulation. In order to know more useful information about cyclic peptides in clinical research and drug application, this paper also summarizes cyclic peptides currently in the clinical trial stage and cyclic peptide drugs approved for marketing in the recent five years. Cyclic peptides have many advantages and great potential in treating various diseases, but there are still many challenges to be solved in the development process of cyclic peptides.

Streamlined Protein-Protein Interface Loop Mimicry

Cyclic peptides comprising endocyclic organic fragments, "cyclo-organopeptides", can be probes for perturbing protein-protein interactions (PPIs). Finding loop mimics is difficult because of high conformational variability amongst targets. Backbone Matching (BM), introduced here, helps solve this problem in the illustrative cases by facilitating efficient evaluation of virtual cyclo-organopeptide core-structure libraries. Thus, 86 rigid organic fragments were selected to build a library of 602 cyclo-organopeptides comprising Ala and organic parts: "cyclo-{-(Ala)n -organo-}". The central hypothesis is "hit" library members have accessible low energy conformers corresponding to backbone structures of target protein loops, while library members which cannot attain this conformation are probably unworthy of further evaluation. BM thereby prioritizes candidate loop mimics, so that less than 10 cyclo-organopeptides are needed to be prepared to find leads for two illustrative PPIs: iNOS ⋅ SPSB2, and uPA ⋅ uPAR.

Addressing Challenges of Macrocyclic Conformational Sampling in Polar and Apolar Solvents: Lessons for Chameleonicity

We evaluated a workflow to reliably sample the conformational space of a set of 47 peptidic macrocycles. Starting from SMILES strings, we use accelerated molecular dynamics simulations to overcome high energy barriers, in particular, the cis-trans isomerization of peptide bonds. We find that our approach performs very well in polar solvents like water and dimethyl sulfoxide. Interestingly, the protonation state of a secondary amine in the ring only slightly influences the conformational ensembles of our test systems. For several of the macrocycles, determining the conformational distribution in chloroform turns out to be considerably more challenging. Especially, the choice of partial charges crucially influences the ensembles in chloroform. We address these challenges by modifying initial structures and the choice of partial charges. Our results suggest that special care has to be taken to understand the configurational distribution in apolar solvents, which is a key step toward a reliable prediction of membrane permeation of macrocycles and their chameleonic properties.

A macrocyclic peptide inhibitor traps MRP1 in a catalytically incompetent conformation

Adenosine triphosphate-binding cassette (ABC) transporters, such as multidrug resistance protein 1 (MRP1), protect against cellular toxicity by exporting xenobiotic compounds across the plasma membrane. However, constitutive MRP1 function hinders drug delivery across the blood-brain barrier, and MRP1 overexpression in certain cancers leads to acquired multidrug resistance and chemotherapy failure. Small-molecule inhibitors have the potential to block substrate transport, but few show specificity for MRP1. Here we identify a macrocyclic peptide, named CPI1, which inhibits MRP1 with nanomolar potency but shows minimal inhibition of a related multidrug transporter P-glycoprotein. A cryoelectron microscopy (cryo-EM) structure at 3.27 Å resolution shows that CPI1 binds MRP1 at the same location as the physiological substrate leukotriene C4 (LTC4). Residues that interact with both ligands contain large, flexible sidechains that can form a variety of interactions, revealing how MRP1 recognizes multiple structurally unrelated molecules. CPI1 binding prevents the conformational changes necessary for adenosine triphosphate (ATP) hydrolysis and substrate transport, suggesting it may have potential as a therapeutic candidate.

Rational Strategy for Designing Peptidomimetic Small Molecules Based on Cyclic Peptides Targeting Protein-Protein Interaction between CTLA-4 and B7-1

Currently, various pharmaceutical modalities are being developed rapidly. Targeting protein-protein interactions (PPIs) is an important objective in such development. Cyclic peptides, because they have good specificity and activity, have been attracting much attention as an alternative to antibody drugs. However, cyclic peptides involve some difficulties, such as oral availability and cell permeability. Therefore, while small-molecule drugs still present many benefits, the screening of functional small-molecule compounds targeting PPIs requires a great deal of time and effort, including structural analysis of targets and hits. In this study, we investigated a rational two-step strategy to design small-molecule compounds targeting PPIs. First, we obtained inhibitory cyclic peptides that bind to cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) by ribosomal display using PUREfrex^® (PUREfrex^®RD) to get structure-activity relation (SAR) information. Based on that information, we converted cyclic peptides to small molecules using PepMetics^® scaffolds that can mimic the α-helix or β-turn of the peptide. Finally, we succeeded in generating small-molecule compounds with good IC₅₀ (single-digit μM values) against CTLA-4. This strategy is expected to be a useful approach for small-molecule design targeting PPIs, even without having structural information such as that associated with X-ray crystal structures.

A backbone-dependent rotamer library with high (ϕ, ψ) coverage using metadynamics simulations

Backbone-dependent rotamer libraries are commonly used to assign the side chain dihedral angles of amino acids when modeling protein structures. Most rotamer libraries are created by curating protein crystal structure data and using various methods to extrapolate the existing data to cover all possible backbone conformations. However, these rotamer libraries may not be suitable for modeling the structures of cyclic peptides and other constrained peptides because these molecules frequently sample backbone conformations rarely seen in the crystal structures of linear proteins. To provide backbone-dependent side chain information beyond the α-helix, β-sheet, and PPII regions, we used explicit-solvent metadynamics simulations of model dipeptides to create a new rotamer library that has high coverage in the (ϕ, ψ) space. Furthermore, this approach can be applied to build high-coverage rotamer libraries for noncanonical amino acids. The resulting Metadynamics of Dipeptides for Rotamer Distribution (MEDFORD) rotamer library predicts the side chain conformations of high-resolution protein crystal structures with similar accuracy (~80%) to a state-of-the-art rotamer library. Our ability to test the accuracy of MEDFORD at predicting the side chain dihedral angles of amino acids in noncanonical backbone conformation is restricted by the limited structural data available for cyclic peptides. For the cyclic peptide data that are currently available, MEDFORD and the state-of-the-art rotamer library perform comparably. However, the two rotamer libraries indeed make different rotamer predictions in noncanonical (ϕ, ψ) regions. For noncanonical amino acids, the MEDFORD rotamer library predicts the χ1 values with approximately 75% accuracy.

Peptide-to-Small Molecule: A Pharmacophore-Guided Small Molecule Lead Generation Strategy from High-Affinity Macrocyclic Peptides

Recent technological innovations have led to the development of methods for the rapid identification of high-affinity macrocyclic peptides for a wide range of targets; however, it is still challenging to achieve the desired activity and membrane permeability at the same time. Here, we propose a novel small molecule lead discovery strategy, ″Peptide-to-Small Molecule″, which is a combination of rapid identification of high-affinity macrocyclic peptides via peptide display screening followed by pharmacophore-guided de novo design of small molecules, and demonstrate the applicability using nicotinamide N-methyltransferase (NNMT) as a target. Affinity selection by peptide display technology identified macrocyclic peptide 1 that exhibited good enzymatic inhibitory activity but no cell-based activity. Thereafter, a peptide pharmacophore-guided de novo design and further structure-based optimization resulted in highly potent and cell-active small molecule 14 (cell-free IC₅₀ = 0.0011 μM, cell-based IC₅₀ = 0.40 μM), indicating that this strategy could be a new option for drug discovery.

Design of Protein Segments and Peptides for Binding to Protein Targets

Recent years have witnessed a rise in methods for accurate prediction of structure and design of novel functional proteins. Design of functional protein fragments and peptides occupy a small, albeit unique, space within the general field of protein design. While the smaller size of these peptides allows for more exhaustive computational methods, flexibility in their structure and sparsity of data compared to proteins, as well as presence of noncanonical building blocks, add additional challenges to their design. This review summarizes the current advances in the design of protein fragments and peptides for binding to targets and discusses the challenges in the field, with an eye toward future directions.

Leveraging self-assembled nanobiomaterials for improved cancer immunotherapy

Nanomaterials and targeted drug delivery vehicles improve the therapeutic index of drugs and permit greater control over their pharmacokinetics, biodistribution, and bioavailability. Here, nanotechnologies applied to cancer immunotherapy are discussed with a focus on current and next generation self-assembling drug delivery systems composed of lipids and/or polymers. Topics covered include the fundamental design, suitability, and inherent properties of nanomaterials that induce anti-tumor immune responses and support anti-cancer vaccination. Established active and passive targeting strategies as well as newer "indirect" methods are presented together with insights into how nanocarrier structure and surface chemistry can be leveraged for controlled delivery to the tumor microenvironment while minimizing off-target effects.

A Strategy to Select Macrocyclic Peptides Featuring Asymmetric Molecular Scaffolds as Cyclization Units by Phage Display

Macrocyclic peptides (MPs) have positioned themselves as a privileged class of compounds for the discovery of therapeutics and development of chemical probes. Aided by the development of powerful selection strategies, high-affinity binders against biomolecular targets can readily be elicited from massive, genetically encoded libraries by affinity selection. For example, in phage display, MPs are accessed on the surface of whole bacteriophages via disulfide formation, the use of (symmetric) crosslinkers, or the incorporation of non-canonical amino acids. To facilitate a straightforward cyclization of linear precursors with asymmetric molecular scaffolds, which are often found at the core of naturally occurring MPs, we report an efficient two-step strategy to access MPs via the programmed modification of a unique cysteine residue and an N-terminal amine. We demonstrate that this approach yields MPs featuring asymmetric cyclization units from both synthetic peptides and when linear precursors are appended onto a phage-coat protein. Finally, we showcase that our cyclization strategy is compatible with traditional phage-display protocols and enables the selection of MP binders against a model target protein from naïve libraries. By enabling the incorporation of non-peptidic moieties that (1) can serve as cyclization units, (2) provide interactions for binding, and/or (3) tailor pharmacological properties, our head-to-side-chain cyclization strategy provides access to a currently under-explored chemical space for the development of chemical probes and therapeutics.

Performance evaluation of flexible macrocycle docking in AutoDock

Macrocycles represent an important class of ligands, both in natural products and designed drugs. In drug design, macrocyclizations can impart specific ligand conformations and contribute to passive permeation by encouraging intramolecular H-bonds. AutoDock-GPU and Vina can model macrocyclic ligands flexibly, without requiring the enumeration of macrocyclic conformers before docking. Here, we characterize the performance of the method for handling macrocyclic compounds, which is implemented and the default behaviour for ligand preparation with our ligand preparation pipeline, Meeko. A pseudoatom is used to encode bond geometry and produce an anisotropic closure force for macrocyclic rings. This method is evaluated on a diverse set of small molecule and peptide macrocycles, ranging from 7- to 33-membered rings, showing little accuracy loss compared to rigid redocking of the X-ray macrocycle conformers. This suggests that for conformationally flexible macrocycles with unknown binding modes, this method can be effectively used to predict the macrocycle conformation.

Macrocyclic Inhibitors of HGF-Activating Serine Proteases Overcome Resistance to Receptor Tyrosine Kinase Inhibitors and Block Lung Cancer Progression

Hepatocyte growth factor (HGF), the ligand for the MET receptor tyrosine kinase, is a tumor-promoting factor that is abundant in the tumor microenvironment. Proteolytic activation of inactive pro-HGF by one or more of the serine endopeptidases matriptase, hepsin, and HGF activator is the rate-limiting step in HGF/MET signaling. Herein, we have rationally designed a novel class of side chain cyclized macrocyclic peptide inhibitors. The new series of cyclic tripeptides has superior metabolic stability and significantly improved pharmacokinetics in mice relative to the corresponding linear peptides. We identified the lead compound VD2173 that potently inhibits matriptase and hepsin, which was tested in parallel alongside the acyclic inhibitor ZFH7116 using both in vitro and in vivo models of lung cancer. We demonstrated that both compounds block pro-HGF activation, abrogate HGF-mediated wound healing, and overcome resistance to EGFR- and MET-targeted therapy in lung cancer models. Furthermore, VD2173 inhibited HGF-dependent growth of lung cancer tumors in mice.

Protease-Resistant Peptides for Targeting and Intracellular Delivery of Therapeutics

Peptides show high promise in the targeting and intracellular delivery of next-generation bio- and nano-therapeutics. However, the proteolytic susceptibility of peptides is one of the major limitations of their activity in biological environments. Numerous strategies have been devised to chemically enhance the resistance of peptides to proteolysis, ranging from N- and C-termini protection to cyclization, and including backbone modification, incorporation of amino acids with non-canonical side chains and conjugation. Since conjugation of nanocarriers or other cargoes to peptides for targeting and cell penetration may already provide some degree of shielding, the question arises about the relevance of using protease-resistant sequences for these applications. Aiming to answer this question, here we provide a critical review on protease-resistant targeting peptides and cell-penetrating peptides (CPPs). Two main approaches have been used on these classes of peptides: enantio/retro-enantio isomerization and cyclization. On one hand, enantio/retro-enantio isomerization has been shown to provide a clear enhancement in peptide efficiency with respect to parent L-amino acid peptides, especially when applied to peptides for drug delivery to the brain. On the other hand, cyclization also clearly increases peptide transport capacity, although contribution from enhanced protease resistance or affinity is often not dissected. Overall, we conclude that although conjugation often offers some degree of protection to proteolysis in targeting peptides and CPPs, modification of peptide sequences to further enhance protease resistance can greatly increase homing and transport efficiency.

Computational Design of Structured and Functional Peptide Macrocycles

Structure-based computational design methods have been developed to create proteins in silico with diverse shapes and sizes that accurately fold in vitro, from 7-residue macrocycles to megadalton-scale self-assembling nanomaterials. Precise control over protein shape has further enabled design and optimization of functional therapeutic proteins, including agonists, antagonists, enzymes, and vaccines. Computational design of functional peptides of smaller size presents a persistent challenge, with few successful examples to date. Herein we describe validated general methods for computational design of peptides using the Rosetta molecular modeling suite and discuss outstanding challenges and future directions.

Semisynthetic head-to-tail cyclized peptides obtained by combining protein trans-splicing and intramolecular expressed protein ligation

A dual-intein approach for the preparation of head-to-tail macrocyclic peptides is reported, where synthetic and genetically encoded fragments are ligated by two native peptide bonds. A split intein ligates the synthetic and genetically encoded peptides via protein trans-splicing and is followed by intramolecular cyclization through an expressed protein ligation step mediated with a cis-intein. We identified a suitable pair of orthogonal inteins and optimized the conditions for a one-pot cyclization protocol. We report the semisynthesis of model macrocyles with various ring sizes and of the natural product sunflower trypsin inhibitor (SFTI) along with its ornithine analog.

Cyclisation strategies for stabilising peptides with irregular conformations

Cyclisation is a common synthetic strategy for enhancing the therapeutic potential of peptide-based molecules. While there are extensive studies on peptide cyclisation for reinforcing regular secondary structures such as α-helices and β-sheets, there are remarkably few reports of cyclising peptides which adopt irregular conformations in their bioactive target-bound state. In this review, we highlight examples where cyclisation techniques have been successful in stabilising irregular conformations, then discuss how the design of cyclic constraints for irregularly structured peptides can be informed by existing β-strand stabilisation approaches, new computational design techniques, and structural principles extracted from cyclic peptide library screening hits. Through this analysis, we demonstrate how existing peptide cyclisation techniques can be adapted to address the synthetic design challenge of stabilising irregularly structured binding motifs.

Anchor extension: a structure-guided approach to design cyclic peptides targeting enzyme active sites

Despite recent success in computational design of structured cyclic peptides, de novo design of cyclic peptides that bind to any protein functional site remains difficult. To address this challenge, we develop a computational "anchor extension" methodology for targeting protein interfaces by extending a peptide chain around a non-canonical amino acid residue anchor. To test our approach using a well characterized model system, we design cyclic peptides that inhibit histone deacetylases 2 and 6 (HDAC2 and HDAC6) with enhanced potency compared to the original anchor (IC₅₀ values of 9.1 and 4.4 nM for the best binders compared to 5.4 and 0.6 µM for the anchor, respectively). The HDAC6 inhibitor is among the most potent reported so far. These results highlight the potential for de novo design of high-affinity protein-peptide interfaces, as well as the challenges that remain.

Solution-State Preorganization of Cyclic β-Hairpin Ligands Determines Binding Mechanism and Affinities for MDM2

Understanding mechanisms of protein folding and binding is crucial to designing their molecular function. Molecular dynamics (MD) simulations and Markov state model (MSM) approaches provide a powerful way to understand complex conformational change that occurs over long time scales. Such dynamics are important for the design of therapeutic peptidomimetic ligands, whose affinity and binding mechanism are dictated by a combination of folding and binding. To examine the role of preorganization in peptide binding to protein targets, we performed massively parallel explicit-solvent MD simulations of cyclic β-hairpin ligands designed to mimic the p53 transactivation domain and competitively bind mouse double minute 2 homologue (MDM2). Disrupting the MDM2-p53 interaction is a therapeutic strategy to prevent degradation of the p53 tumor suppressor in cancer cells. MSM analysis of over 3 ms of aggregate trajectory data enabled us to build a detailed mechanistic model of coupled folding and binding of four cyclic peptides which we compare to experimental binding affinities and rates. The results show a striking relationship between the relative preorganization of each ligand in solution and its affinity for MDM2. Specifically, changes in peptide conformational populations predicted by the MSMs suggest that entropy loss upon binding is the main factor influencing affinity. The MSMs also enable detailed examination of non-native interactions which lead to misfolded states and comparison of structural ensembles with experimental NMR measurements. In contrast to an MSM study of p53 transactivation domain (TAD) binding to MDM2, MSMs of cyclic β-hairpin binding show a conformational selection mechanism. Finally, we make progress toward predicting accurate off rates of cyclic peptides using multiensemble Markov models (MEMMs) constructed from unbiased and biased simulated trajectories.

Targeting of extracellular protein-protein interactions with macrocyclic peptides

Targeting of extracellular protein-protein interactions (PPI) is emerging as a major application for de novo discovered macrocyclic peptides. Modern discovery platforms can routinely identify macrocyclic peptide ligands capable of highly selective modulation of extracellular signaling pathways; amenability to chemical synthesis and natural modularity of peptides additionally provides an avenue for their further structural elaboration, while the challenge of cell internalization can be minimized. Here, we discuss the recent progress in targeting extracellular PPIs with macrocyclic peptides by focusing on a number of recent case studies. We analyze the scope and potential limitations of the discovery systems in identifying functional macrocyclic ligands. We also highlight the recent technical advancements allowing for a more streamlined discovery pipeline and our brief perspective in this field.

Genetic Fusion of Transacting Activator of Transcription Peptide to Cyclized Green Fluorescence Protein Improves Stability, Intracellular Delivery, and Tumor Retention

Therapeutic proteins such as enzymes, hormones, and cytokines suffer from poor stability, inefficient cellular penetration, and rapid clearance from circulation. Conjugation with polymers (such as poly(ethylene glycol)) and fusion with long-acting proteins (such as albumin and Fc fragments) have been utilized to partially address the delivery issues, but these strategies require the introduction of new macromolecular substances, resulting in potential immunogenicity and toxicity. Herein, we report an easy strategy to increase the intracellular delivery efficiency and stability of proteins by combining of sortase-mediated protein cyclization and cell-penetrating peptide (CPP)-mediated intracellular delivery. We, for the first time, genetically constructed a green fluorescence protein (GFP) fused with a CPP, a transacting activator of transcription (TAT) peptide, at its C-terminus for intracellular internalization, and two sortase recognition sequences, pentaglycine and LPETG, at its N- and C-termini for cyclization. Notably, the cyclized GFP-TAT (cGFP-TAT) not only highly retained the photophysical properties of the protein but also significantly improved the in vitro stability compared with the native linear GFP (lGFP) and linear TAT peptide-fused GFP (lGFP-TAT).Moreover, cGFP-TAT showed better cellular internalization ability compared with lGFP. In C26 tumor-inoculated mice, cGFP-TAT exhibited enhanced in vivo tumor retention, with increases of 7.79- and 6.52-fold relative to lGFP and lGFP-TAT in tumor retention 3 h after intratumor administration. This proof-of-concept study has provided an easy strategy to increase the in vitro stability, intracellular delivery efficiency, and in vivo tumor retention of GFP, which would be applicable to numerous therapeutic proteins and peptides for clinical practice.

Discovery of De Novo Macrocyclic Peptides by Messenger RNA Display

Macrocyclic peptides are a promising class of compounds that can often engage challenging therapeutic targets. Display technologies, such as mRNA display, allow for the efficient discovery of macrocyclic peptides. This article reviews the current approaches for generating macrocyclic peptide libraries using mRNA display and highlights some recent examples of ribosomal incorporation of nonproteinogenic amino acids into macrocyclic peptides.

Conformational Strain of Macrocyclic Peptides in Ligand-Receptor Complexes Based on Advanced Refinement of Bound-State Conformers

Macrocyclic peptides are an important modality in drug discovery, but molecular design is limited due to the complexity of their conformational landscape. To better understand conformational propensities, global strain energies were estimated for 156 protein-macrocyclic peptide cocrystal structures. Unexpectedly large strain energies were observed when the bound-state conformations were modeled with positional restraints. Instead, low-energy conformer ensembles were generated using xGen that fit experimental X-ray electron density maps and gave reasonable strain energy estimates. The ensembles featured significant conformational adjustments while still fitting the electron density as well or better than the original coordinates. Strain estimates suggest the interaction energy in protein-ligand complexes can offset a greater amount of strain for macrocyclic peptides than for small molecules and non-peptidic macrocycles. Across all molecular classes, the approximate upper bound on global strain energies had the same relationship with molecular size, and bound-state ensembles from xGen yielded favorable binding energy estimates.

Illuminating the dark conformational space of macrocycles using dominant rotors

Three-dimensional conformation is the primary determinant of molecular properties. The thermal energy available at room temperature typically equilibrates the accessible conformational states. Here, we introduce a method for isolating unique and previously understudied conformations of macrocycles. The observation of unusual conformations of 16- to 22-membered rings has been made possible by controlling their interconversion using dominant rotors, which represent tunable atropisomeric constituents with relatively high rotational barriers. Density functional theory and in situ NMR measurements suggest that dominant rotor candidates for the amino-acid-based structures considered here should possess a rotational energy barrier of at least 25 kcal mol^-1. Notable differences in the geometries of the macrocycle conformations were identified by NMR spectroscopy and X-ray crystallography. There is evidence that amino acid residues can be forced into rare turn motifs not observed in the corresponding linear counterparts and homodetic rings. These findings should unlock new avenues for studying the conformation-activity relationships of bioactive molecules.

Elucidating Solution Structures of Cyclic Peptides Using Molecular Dynamics Simulations

Protein-protein interactions are vital to biological processes, but the shape and size of their interfaces make them hard to target using small molecules. Cyclic peptides have shown promise as protein-protein interaction modulators, as they can bind protein surfaces with high affinity and specificity. Dozens of cyclic peptides are already FDA approved, and many more are in various stages of development as immunosuppressants, antibiotics, antivirals, or anticancer drugs. However, most cyclic peptide drugs so far have been natural products or derivatives thereof, with de novo design having proven challenging. A key obstacle is structural characterization: cyclic peptides frequently adopt multiple conformations in solution, which are difficult to resolve using techniques like NMR spectroscopy. The lack of solution structural information prevents a thorough understanding of cyclic peptides' sequence-structure-function relationship. Here we review recent development and application of molecular dynamics simulations with enhanced sampling to studying the solution structures of cyclic peptides. We describe novel computational methods capable of sampling cyclic peptides' conformational space and provide examples of computational studies that relate peptides' sequence and structure to biological activity. We demonstrate that molecular dynamics simulations have grown from an explanatory technique to a full-fledged tool for systematic studies at the forefront of cyclic peptide therapeutic design.

The allosteric modulation of complement C5 by knob domain peptides

Bovines have evolved a subset of antibodies with ultra-long heavy chain complementarity determining regions that harbour cysteine-rich knob domains. To produce high-affinity peptides, we previously isolated autonomous 3–6 kDa knob domains from bovine antibodies. Here, we show that binding of four knob domain peptides elicits a range of effects on the clinically validated drug target complement C5. Allosteric mechanisms predominated, with one peptide selectively inhibiting C5 cleavage by the alternative pathway C5 convertase, revealing a targetable mechanistic difference between the classical and alternative pathway C5 convertases. Taking a hybrid biophysical approach, we present C5-knob domain co-crystal structures and, by solution methods, observed allosteric effects propagating >50 Å from the binding sites. This study expands the therapeutic scope of C5, presents new inhibitors, and introduces knob domains as new, low molecular weight antibody fragments, with therapeutic potential.

Antibodies are proteins produced by the immune system that can selectively bind to other molecules and modify their behaviour. Cows are highly equipped at fighting-off disease-causing microbes due to the unique shape of some of their antibodies. Unlike other jawed vertebrates, cows’ antibodies contain an ultra-long loop region that contains a ‘knob domain’ which sticks out from the rest of the antibody. Recent research has shown that when detached, the knob domain behaves like an antibody fragment, and can independently bind to a range of different proteins.

Antibody fragments are commonly developed in the laboratory to target proteins associated with certain diseases, such as arthritis and cancer. But it was unclear whether the knob domains from cows’ antibodies could also have therapeutic potential. To investigate this, Macpherson et al. studied how knob domains attach to complement C5, a protein in the inflammatory pathway which is a drug target for various diseases, including severe COVID-19.

The experiments identified various knob domains that bind to complement C5 and inhibits its activity by altering its structure or movement. Further tests studying the structure of these interactions, led to the discovery of a common mechanism by which inhibitors can modify the behaviour of this inflammatory protein.

Complement C5 is involved in numerous molecular pathways in the immune system, which means many of the drugs developed to inhibit its activity can also leave patients vulnerable to infection. However, one of the knob domains identified by Macpherson et al. was found to reduce the activity of complement C5 in some pathways, whilst leaving other pathways intact. This could potentially reduce the risk of bacterial infections which sometimes arise following treatment with these types of inhibitors.

These findings highlight a new approach for developing drug inhibitors for complement C5. Furthermore, the ability of knob domains to bind to multiple sites of complement C5 suggests that this fragment could be used to target proteins associated with other diseases.

Engineering of new-to-nature ribosomally synthesized and post-translationally modified peptide natural products

Natural products have historically been important lead sources for drug development, particularly to combat infectious diseases. Increasingly, their structurally complex scaffolds are also envisioned as leads for applications for which they did not evolve, an approach aided by engineering of new-to-nature analogs. Ribosomally synthesized and post-translationally modified peptides (RiPPs) are promising candidates for bioengineering because they are genetically encoded and their biosynthetic enzymes display significant substrate tolerance. This review highlights recent advances in the discovery of highly unusual new reactions by genome mining and the application of engineering approaches to generate and screen novel RiPP variants. Furthermore, through the use of synthetic biology approaches, hybrid molecules with enhanced or completely new activities have been identified, which opens the door for future advancement of RiPPs as potential next-generation therapeutics.

Use of cyclic peptides to induce crystallization: case study with prolyl hydroxylase domain 2

Crystallization is the bottleneck in macromolecular crystallography; even when a protein crystallises, crystal packing often influences ligand-binding and protein-protein interaction interfaces, which are the key points of interest for functional and drug discovery studies. The human hypoxia-inducible factor prolyl hydroxylase 2 (PHD2) readily crystallises as a homotrimer, but with a sterically blocked active site. We explored strategies aimed at altering PHD2 crystal packing by protein modification and molecules that bind at its active site and elsewhere. Following the observation that, despite weak inhibition/binding in solution, succinamic acid derivatives readily enable PHD2 crystallization, we explored methods to induce crystallization without active site binding. Cyclic peptides obtained via mRNA display bind PHD2 tightly away from the active site. They efficiently enable PHD2 crystallization in different forms, both with/without substrates, apparently by promoting oligomerization involving binding to the C-terminal region. Although our work involves a specific case study, together with those of others, the results suggest that mRNA display-derived cyclic peptides may be useful in challenging protein crystallization cases.

Drug-Like Properties in Macrocycles above MW 1000: Backbone Rigidity versus Side-Chain Lipophilicity

Large macrocyclic peptides can achieve surprisingly high membrane permeability, although the properties that govern permeability in this chemical space are only beginning to come into focus. We generated two libraries of cyclic decapeptides with stable cross-β conformations, and found that peptoid substitutions within the β-turns of the macrocycle preserved the rigidity of the parent scaffold, whereas peptoid substitutions in the opposing β-strands led to "chameleonic" species that were rigid in nonpolar media but highly flexible in water. Both rigid and chameleonic compounds showed high permeability over a wide lipophilicity range, with peak permeabilities differing significantly depending on scaffold rigidity. Our findings indicate that modulating lipophilicity can be used to engineer favorable ADME properties into both rigid and flexible macrocyclic peptides, and that scaffold rigidity can be used to tune optimal lipophilicity.

The role of NMR in leveraging dynamics and entropy in drug design

Nuclear magnetic resonance (NMR) spectroscopy has contributed to structure-based drug development (SBDD) in a unique way compared to the other biophysical methods. The potency of a ligand binding to a protein is dictated by the binding free energy, which is an intricate interplay between entropy and enthalpy. In addition to providing the atomic resolution structural information, NMR can help to identify protein-ligand interactions that potentially contribute to the enthalpic component of the free energy. NMR can also illuminate dynamic aspects of the interaction, which correspond to the entropic term of the free energy. The ability of NMR to access both terms in the free energy equation stems from the suite of experiments developed to shed light on various aspects that contribute to both entropy and enthalpy, deepening our understanding of the biological function of macromolecules and assisting to target them in physiological conditions. Here we provide a brief account of the contribution of NMR to SBDD, highlighting hallmark examples and discussing the challenges that demand further method development. In the era of integrated biology, the unique ability of NMR to directly ascertain structural and dynamical aspects of macromolecule and monitor changes in these properties upon engaging a ligand can be combined with computational and other structural and biophysical methods to provide a more complete picture of the energetics of drug engagement with the target. Such efforts can be used to engineer better drugs.

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.

Systemic delivery of peptides by the oral route: Formulation and medicinal chemistry approaches

In its 33 years, ADDR has published regularly on the po5tential of oral delivery of biologics especially peptides and proteins. In the intervening period, analysis of the preclinical and clinical trial failures of many purported platform technologies has led to reflection on the true status of the field and reigning in of expectations. Oral formulations of semaglutide, octreotide, and salmon calcitonin have completed Phase III trials, with oral semaglutide being approved by the FDA in 2019. The progress made with oral peptide formulations based on traditional permeation enhancers is against a background of low and variable oral bioavailability values of ~1%, leading to a current perception that only potent peptides with a viable cost of synthesis can be realistically considered. Desirable features of candidates should include a large therapeutic index, some stability in the GI tract, a long elimination half-life, and a relatively low clearance rate. Administration in nanoparticle formats have largely disappointed, with few prototypes reaching clinical trials: insufficient particle loading, lack of controlled release, low epithelial particle uptake, and lack of scalable synthesis being the main reasons for discontinuation. Disruptive technologies based on engineered devices promise improvements, but scale-up and toxicology aspects are issues to address. In parallel, medicinal chemists are synthesizing stable hydrophobic macrocyclic candidate peptides of lower molecular weight and with potential for greater oral bioavailability than linear peptides, but perhaps without the same requirement for elaborate drug delivery systems. In summary, while there have been advances in understanding the limitations of peptides for oral delivery, low membrane permeability, metabolism, and high clearance rates continue to hamper progress.