Exploring experimental and computational markers of cyclic peptides: Charting islands of permeability

Synthesis and bioactivity of cyclic peptide GG-8-6 analogues as anti-hepatocellular carcinoma agents

GG-8-6, a cyclic peptide with effective anti-hepatocellular carcinoma activity in vitro and in vivo, was synthesized based on the lead compound Grifficyclocin B, which was isolated from the plants of Goniothalamus species (Annonaceae family). Based on the previous study, we synthesized 17 analogues of GG-8-6 to find better potential and higher-yield cyclopeptides. Among these analogues, nine increased their yield compared to GG-8-6, and compound 1 reached a high yield of 14.7 %. In addition, the bioassay results showed that ten analogues exhibited significant anti-hepatocellular carcinoma activities in vitro, which promoted cell apoptosis and reduced intracellular ATP levels. Among them, the activity of compounds 1, 2 and 3 was significantly better than GG-8-6, while the yield of compounds 1 and 3 reached nearly five times that of GG-8-6. Compound 17 was obtained by deprotection from compound 1, which preserved antitumor activity, and more new derivatives could be synthesized based on the hydroxyl group in its structure. A subcutaneous xenografted mice model confirmed the in vivo antitumor activity of compounds 1 and 17. The results indicated that both compounds significantly inhibited the growth of tumours. At 10 mg/kg and 15 mg/kg doses for compounds 1 and 17, the inhibition rates reached 84.3 % and 58.39 %, respectively. Furthermore, the potential mechanism of compounds 1 and 17 was analyzed by transcriptomic analysis. Our results indicated that GG-8-6 analogues as new cyclic peptides might be potential candidates for developing new drugs treating hepatocellular carcinoma.

Heterophyllin B: Combining Isotropic and Anisotropic NMR for the Conformational Analysis of a Natural Occurring Cyclic Peptide

Heterophyllin B is a natural occurring cyclic peptide with diverse attributed bioactivities. NMR-based conformational analysis of cyclic peptides often poses a challenge due to limited isotropic solution-state NMR data. In this study, we combined isotropic and anisotropic NMR observables including J-coupling, NOEs, amide proton temperature coefficients, and residual dipolar couplings (RDCs), which enabled the determination of a minimal conformational ensemble of heterophyllin B in methanol at density functional theory (DFT) accuracy. For conformational sampling of a cyclic peptide with a high degree of conformational freedom, we proposed a computational strategy that combines the Conformer-Rotamer Ensemble Sampling Tool (CREST) with the Commandline Energetic SOrting (CENSO). This combined computational and NMR-based approach offers a robust framework for the conformational analysis of cyclic peptides.

StaPep: An Open-Source Toolkit for Structure Prediction, Feature Extraction, and Rational Design of Hydrocarbon-Stapled Peptides

All-hydrocarbon stapled peptides, with their covalent side-chain constraints, provide enhanced proteolytic stability and membrane permeability, making them superior to linear peptides. However, tools for extracting structural and physicochemical descriptors to predict the properties of hydrocarbon-stapled peptides are lacking. To address this, we present StaPep, a Python-based toolkit for generating 3D structures and calculating 21 features for hydrocarbon-stapled peptides. StaPep supports peptides containing two non-standard amino acids (norleucine and 2-aminoisobutyric acid) and six non-natural anchoring residues (S3, S5, S8, R3, R5, and R8), with customization options for other non-standard amino acids. We showcase StaPep's utility through three case studies. The first generates 3D structures of these peptides with a mean RMSD of 1.62 ± 0.86, offering essential structural insights for drug design and biological activity prediction. The second develops machine learning models based on calculated molecular features to differentiate between membrane-permeable and non-permeable stapled peptides, achieving an AUC of 0.93. The third constructs regression models to predict the antimicrobial activity of stapled peptides against Escherichia coli, with a Pearson correlation of 0.84. StaPep's pipeline spans data retrieval, structure generation, feature calculation, and machine learning modeling for hydrocarbon-stapled peptides. The source codes and data set are freely available on Github: https://github.com/dahuilangda/stapep_package.

Chromatographic Determination of Permeability-Relevant Lipophilicity Facilitates Rapid Analysis of Macrocyclic Peptide Scaffolds

Hydrocarbon-determined shake-flask measurements have demonstrated great utility for optimizing lipophilicity during early drug discovery. Alternatively, chromatographic methods confer reduced experimental error and improved handling of complex mixtures. In this study, we developed a chromatographic approach for estimating hydrocarbon-water shake-flask partition coefficients for a variety of macrocyclic peptides and other bRo5 molecules including PROTACs. The model accurately predicts experimental shake-flask measurements with high reproducibility across a wide range of lipophilicities. The chromatographic retention times revealed subtle conformational effects and correlated with the ability to sequester hydrogen bond donors in low dielectric media. Estimations of shake-flask lipophilicity from our model also accurately predicted trends in MDCK passive cell permeability for a variety of thioether-cyclized decapeptides. This method provides a convenient, high-throughput approach for measuring lipophilic permeability efficiency and predicting passive cell permeability in bRo5 compounds that is suitable for multiplexing pure compounds or investigating the properties of complex library mixtures.

CycPeptMP: enhancing membrane permeability prediction of cyclic peptides with multi-level molecular features and data augmentation

Cyclic peptides are versatile therapeutic agents that boast high binding affinity, minimal toxicity, and the potential to engage challenging protein targets. However, the pharmaceutical utility of cyclic peptides is limited by their low membrane permeability-an essential indicator of oral bioavailability and intracellular targeting. Current machine learning-based models of cyclic peptide permeability show variable performance owing to the limitations of experimental data. Furthermore, these methods use features derived from the whole molecule that have traditionally been used to predict small molecules and ignore the unique structural properties of cyclic peptides. This study presents CycPeptMP: an accurate and efficient method to predict cyclic peptide membrane permeability. We designed features for cyclic peptides at the atom-, monomer-, and peptide-levels and seamlessly integrated these into a fusion model using deep learning technology. Additionally, we applied various data augmentation techniques to enhance model training efficiency using the latest data. The fusion model exhibited excellent prediction performance for the logarithm of permeability, with a mean absolute error of $0.355$ and correlation coefficient of $0.883$. Ablation studies demonstrated that all feature levels contributed and were relatively essential to predicting membrane permeability, confirming the effectiveness of augmentation to improve prediction accuracy. A comparison with a molecular dynamics-based method showed that CycPeptMP accurately predicted peptide permeability, which is otherwise difficult to predict using simulations.

Deep learning for advancing peptide drug development: Tools and methods in structure prediction and design

Peptides can bind challenging disease targets with high affinity and specificity, offering enormous opportunities for addressing unmet medical needs. However, peptides' unique features, including smaller size, increased structural flexibility, and limited data availability, pose additional challenges to the design process compared to proteins. This review explores the dynamic field of peptide therapeutics, leveraging deep learning to enhance structure prediction and design. Our exploration encompasses various facets of peptide research, ranging from dataset curation handling to model development. As deep learning technologies become more refined, we channel our efforts into peptide structure prediction and design, aligning with the fundamental principles of structure-activity relationships in drug development. To guide researchers in harnessing the potential of deep learning to advance peptide drug development, our insights comprehensively explore current challenges and future directions of peptide therapeutics.

Targeted Protein Degraders- The Druggability Perspective

Targeted Protein degraders (TPDs) show promise in harnessing cellular machinery to eliminate disease-causing proteins, even those previously considered undruggable. Especially if protein turnover is low, targeted protein removal bestows lasting therapeutic effect over typical inhibition. The demonstrated safety and efficacy profile of clinical candidates has fueled the surge in the number of potential candidates across different therapeutic areas. As TPDs often do not comply with Lipinski's rule of five, developing novel TPDs and unlocking their full potential requires overcoming solubility, permeability and oral bioavailability challenges. Tailored in-vitro assays are key to precise profiling and optimization, propelling breakthroughs in targeted protein degradation.

Membrane Permeability in a Large Macrocyclic Peptide Driven by a Saddle-Shaped Conformation

The effort to modulate challenging protein targets has stimulated interest in ligands that are larger and more complex than typical small-molecule drugs. While combinatorial techniques such as mRNA display routinely produce high-affinity macrocyclic peptides against classically undruggable targets, poor membrane permeability has limited their use toward primarily extracellular targets. Understanding the passive membrane permeability of macrocyclic peptides would, in principle, improve our ability to design libraries whose leads can be more readily optimized against intracellular targets. Here, we investigate the permeabilities of over 200 macrocyclic 10-mers using the thioether cyclization motif commonly found in mRNA display macrocycle libraries. We identified the optimal lipophilicity range for achieving permeability in thioether-cyclized 10-mer cyclic peptide-peptoid hybrid scaffolds and showed that permeability could be maintained upon extensive permutation in the backbone. In one case, changing a single amino acid from d-Pro to d-NMe-Ala, representing the loss of a single methylene group in the side chain, resulted in a highly permeable scaffold in which the low-dielectric conformation shifted from the canonical cross-beta geometry of the parent compounds into a novel saddle-shaped fold in which all four backbone NH groups were sequestered from the solvent. This work provides an example by which pre-existing physicochemical knowledge of a scaffold can benefit the design of macrocyclic peptide mRNA display libraries, pointing toward an approach for biasing libraries toward permeability by design. Moreover, the compounds described herein are a further demonstration that geometrically diverse, highly permeable scaffolds exist well beyond conventional drug-like chemical space.

Multi_CycGT: A Deep Learning-Based Multimodal Model for Predicting the Membrane Permeability of Cyclic Peptides

Cyclic peptides are gaining attention for their strong binding affinity, low toxicity, and ability to target "undruggable" proteins; however, their therapeutic potential against intracellular targets is constrained by their limited membrane permeability, and researchers need much time and money to test this property in the laboratory. Herein, we propose an innovative multimodal model called Multi_CycGT, which combines a graph convolutional network (GCN) and a transformer to extract one- and two-dimensional features for predicting cyclic peptide permeability. The extensive benchmarking experiments show that our Multi_CycGT model can attain state-of-the-art performance, with an average accuracy of 0.8206 and an area under the curve of 0.8650, and demonstrates satisfactory generalization ability on several external data sets. To the best of our knowledge, it is the first deep learning-based attempt to predict the membrane permeability of cyclic peptides, which is beneficial in accelerating the design of cyclic peptide active drugs in medicinal chemistry and chemical biology applications.

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.

An amide to thioamide substitution improves the permeability and bioavailability of macrocyclic peptides

Solvent shielding of the amide hydrogen bond donor (NH groups) through chemical modification or conformational control has been successfully utilized to impart membrane permeability to macrocyclic peptides. We demonstrate that passive membrane permeability can also be conferred by masking the amide hydrogen bond acceptor (>C = O) through a thioamide substitution (>C = S). The membrane permeability is a consequence of the lower desolvation penalty of the macrocycle resulting from a concerted effect of conformational restriction, local desolvation of the thioamide bond, and solvent shielding of the amide NH groups. The enhanced permeability and metabolic stability on thioamidation improve the bioavailability of a macrocyclic peptide composed of hydrophobic amino acids when administered through the oral route in rats. Thioamidation of a bioactive macrocyclic peptide composed of polar amino acids results in analogs with longer duration of action in rats when delivered subcutaneously. These results highlight the potential of O to S substitution as a stable backbone modification in improving the pharmacological properties of peptide macrocycles.

Cell-permeable chameleonic peptides: Exploiting conformational dynamics in de novo cyclic peptide design

Membrane-traversing peptides offer opportunities for targeting intracellular proteins and oral delivery. Despite progress in understanding the mechanisms underlying membrane traversal in natural cell-permeable peptides, there are still several challenges to designing membrane-traversing peptides with diverse shapes and sizes. Conformational flexibility appears to be a key determinant of membrane permeability of large macrocycles. We review recent developments in the design and validation of chameleonic cyclic peptides, which can switch between alternative conformations to enable improved permeability through cell membranes, while still maintaining reasonable solubility and exposed polar functional groups for target protein binding. Finally, we discuss the principles, strategies, and practical considerations for rational design, discovery, and validation of permeable chameleonic peptides.

Targeting the Epidermal Growth Factor Receptor with Molecular Degraders: State-of-the-Art and Future Opportunities

Epidermal growth factor receptor (EGFR) is an oncogenic drug target and plays a critical role in several cellular functions including cancer cell growth, survival, proliferation, differentiation, and motility. Several small-molecule tyrosine kinase inhibitors (TKIs) and monoclonal antibodies (mAbs) have been approved for targeting intracellular and extracellular domains of EGFR, respectively. However, cancer heterogeneity, mutations in the catalytic domain of EGFR, and persistent drug resistance limited their use. Different novel modalities are gaining a position in the limelight of anti-EGFR therapeutics to overcome such limitations. The current perspective reflects upon newer modalities, importantly the molecular degraders such as PROTACs, LYTACs, AUTECs, and ATTECs, etc., beginning with a snapshot of traditional and existing anti-EGFR therapies including small molecule inhibitors, mAbs, and antibody drug conjugates (ADCs). Further, a special emphasis has been made on the design, synthesis, successful applications, state-of-the-art, and emerging future opportunities of each discussed modality.

Commercially Available Cell-Free Permeability Tests for Industrial Drug Development: Increased Sustainability through Reduction of In Vivo Studies

Replacing in vivo with in vitro studies can increase sustainability in the development of medicines. This principle has already been applied in the biowaiver approach based on the biopharmaceutical classification system, BCS. A biowaiver is a regulatory process in which a drug is approved based on evidence of in vitro equivalence, i.e., a dissolution test, rather than on in vivo bioequivalence. Currently biowaivers can only be granted for highly water-soluble drugs, i.e., BCS class I/III drugs. When evaluating poorly soluble drugs, i.e., BCS class II/IV drugs, in vitro dissolution testing has proved to be inadequate for predicting in vivo drug performance due to the lack of permeability interpretation. The aim of this review was to provide solid proofs that at least two commercially available cell-free in vitro assays, namely, the parallel artificial membrane permeability assay, PAMPA, and the PermeaPad^® assay, PermeaPad, in different formats and set-ups, have the potential to reduce and replace in vivo testing to some extent, thus increasing sustainability in drug development. Based on the literature review presented here, we suggest that these assays should be implemented as alternatives to (1) more energy-intense in vitro methods, e.g., refining/replacing cell-based permeability assays, and (2) in vivo studies, e.g., reducing the number of pharmacokinetic studies conducted on animals and humans. For this to happen, a new and modern legislative framework for drug approval is required.

Free-Energy Profiles for Membrane Permeation of Compounds Calculated Using Rare-Event Sampling Methods

The free-energy profile of a compound is an essential measurement in evaluating the membrane permeation process by means of theoretical methods. Computationally, molecular dynamics (MD) simulation allows the free-energy profile calculation. However, MD simulations frequently fail to sample membrane permeation because they are rare events induced in longer timescales than the accessible timescale of MD, leading to an insufficient conformational search to calculate an incorrect free-energy profile. To achieve a sufficient conformational search, several enhanced sampling methods have been developed and elucidated the membrane permeation process. In addition to these enhanced sampling methods, we proposed a simple yet powerful free-energy calculation of a compound for the membrane permeation process based on originally rare-event sampling methods developed by us. Our methods have a weak dependency on external biases and their optimizations to promote the membrane permeation process. Based on distributed computing, our methods only require the selection of initial structures and their conformational resampling, whereas the enhanced sampling methods may be required to adjust external biases. Furthermore, our methods efficiently search membrane permeation processes with simple scripts without modifying any MD program. As demonstrations, we calculated the free-energy profiles of seven linear compounds for their membrane permeation based on a hybrid conformational search using two rare-event sampling methods, that is, (1) parallel cascade selection MD (PaCS-MD) and (2) outlier flooding method (OFLOOD), combined with a Markov state model (MSM) construction. In the first step, PaCS-MD generated initial membrane permeation paths of a compound. In the second step, OFLOOD expanded the unsearched conformational area around the initial paths, allowing for a broad conformational search. Finally, the trajectories were employed to construct reliable MSMs, enabling correct free-energy profile calculations. Furthermore, we estimated the membrane permeability coefficients of all compounds by constructing the reliable MSMs for their membrane permeation. In conclusion, the calculated coefficients were qualitatively correlated with the experimental measurements (correlation coefficient (R²) = 0.8689), indicating that the hybrid conformational search successfully calculated the free-energy profiles and membrane permeability coefficients of the seven compounds.

Membrane Permeating Macrocycles: Design Guidelines from Machine Learning

The ability to predict cell-permeable candidate molecules has great potential to assist drug discovery projects. Large molecules that lie beyond the Rule of Five (bRo5) are increasingly important as drug candidates and tool molecules for chemical biology. However, such large molecules usually do not cross cell membranes and cannot access intracellular targets or be developed as orally bioavailable drugs. Here, we describe a random forest (RF) machine learning model for the prediction of passive membrane permeation rates developed using a set of over 1000 bRo5 macrocyclic compounds. The model is based on easily calculated chemical features/descriptors as independent variables. Our random forest (RF) model substantially outperforms a multiple linear regression model based on the same features and achieves better performance metrics than previously reported models using the same underlying data. These features include: (1) polar surface area in water, (2) the octanol-water partitioning coefficient, (3) the number of hydrogen-bond donors, (4) the sum of the topological distances between nitrogen atoms, (5) the sum of the topological distances between nitrogen and oxygen atoms, and (6) the multiple molecular path count of order 2. The last three features represent molecular flexibility, the ability of the molecule to adopt different conformations in the aqueous and membrane interior phases, and the molecular "chameleonicity." Guided by the model, we propose design guidelines for membrane-permeating macrocycles. It is anticipated that this model will be useful in guiding the design of large, bioactive molecules for medicinal chemistry and chemical biology applications.

Accurate de novo design of membrane-traversing macrocycles

We use computational design coupled with experimental characterization to systematically investigate the design principles for macrocycle membrane permeability and oral bioavailability. We designed 184 6-12 residue macrocycles with a wide range of predicted structures containing noncanonical backbone modifications and experimentally determined structures of 35; 29 are very close to the computational models. With such control, we show that membrane permeability can be systematically achieved by ensuring all amide (NH) groups are engaged in internal hydrogen bonding interactions. 84 designs over the 6-12 residue size range cross membranes with an apparent permeability greater than 1 × 10-6 cm/s. Designs with exposed NH groups can be made membrane permeable through the design of an alternative isoenergetic fully hydrogen-bonded state favored in the lipid membrane. The ability to robustly design membrane-permeable and orally bioavailable peptides with high structural accuracy should contribute to the next generation of designed macrocycle therapeutics.

A story of peptides, lipophilicity and chromatography - back and forth in time

Peptides, as part of the beyond the rule of 5 (bRo5) chemical space, represent a unique class of pharmaceutical compounds. Because of their exceptional position in the chemical space between traditional small molecules (molecular weight (MW) < 500 Da) and large therapeutic proteins (MW > 5000 Da), peptides became promising candidates for targeting challenging binding sites, including even targets traditionally considered as undruggable - e.g. intracellular protein-protein interactions. However, basic knowledge about physicochemical properties that are important for a drug to be membrane permeable is missing but would enhance the drug discovery process of bRo5 molecules. Consequently, there is a demand for quick and simple lipophilicity determination methods for peptides. In comparison to the traditional lipophilicity determination methods via shake flask and in silico prediction, chromatography-based methods could have multiple benefits such as the requirement of low analyte amount, insensitivity to impurities and high throughput. Herein we elucidate the role of peptide lipophilicity and different lipophilicity values. Further, we summarize peptide analysis via common chromatographic techniques, in specific reversed phase liquid chromatography, hydrophilic interaction liquid chromatography and supercritical fluid chromatography and their role in drug discovery and development process.

Impact of Cyclization and Methylation on Peptide Penetration through Droplet Interface Bilayers

Cell-penetrating peptides enter cells via diverse mechanisms, such as endocytosis, active transport, or direct translocation. For the design of orally delivered cell-penetrating peptides, it is crucial to know the contribution of these different mechanisms. In particular, the ability of a peptide to translocate through a lipid bilayer remains a key parameter for the delivery of cargos. However, existing approaches used to assess translocation often provide discrepant results probably because they have different sensitivities to the distinct translocation mechanisms. Here, we focus on the passive permeation of a range of hydrophobic cyclic peptides inspired by somatostatin, a somatotropin release-inhibiting factor. Using droplet interface bilayers (DIB), we assess the passive membrane permeability of these peptides and study the impact of the peptide cyclization and backbone methylation on translocation rates. Cyclization systematically improved the permeability of the tested peptides while methylation did not. By studying the interaction of the peptides with the DIB interfaces, we found membrane insertion and peptide intrinsic diffusion to be two independent factors of permeability. Compared to the industrial gold standard Caco-2 and parallel artificial membrane permeability assay (PAMPA) models, DIBs provide intermediate membrane permeability values, closer to Caco-2. Even for conditions where Caco-2 and PAMPA are discrepant, the DIB approach also gives results closer to Caco-2. Thereupon, DIBs represent a robust alternative to the PAMPA approach for predicting the permeability of peptides, even if the latter present extremely small structural differences.

A New Amino Acid for Improving Permeability and Solubility in Macrocyclic Peptides through Side Chain-to-Backbone Hydrogen Bonding

Despite the notoriously poor membrane permeability of peptides, many cyclic peptide natural products show high passive membrane permeability and potently inhibit a variety of "undruggable" intracellular targets. A major impediment to the design of cyclic peptides with good permeability is the high desolvation energy associated with the peptide backbone amide NH groups. While several strategies have been proposed to mitigate this deleterious effect, only few studies have used polar side chains to sequester backbone NH groups. We investigated the ability of N,N-pyrrolidinylglutamine (Pye), whose side chain contains a powerful hydrogen-bond-accepting C═O amide group but no hydrogen-bond donors, to sequester exposed backbone NH groups in a series of cyclic hexapeptide diastereomers. Analyses revealed that specific Leu-to-Pye substitutions conferred dramatic improvements in aqueous solubility and permeability in a scaffold- and position-dependent manner. Therefore, this approach offers a complementary tool for improving membrane permeability and solubility in cyclic peptides.

Amide-to-Ester Substitution as a Strategy for Optimizing PROTAC Permeability and Cellular Activity

Criteria for predicting the druglike properties of "beyond Rule of 5" Proteolysis Targeting Chimeras (PROTAC) degraders are underdeveloped. PROTAC components are often combined via amide couplings due to their reliability. Amides, however, can give rise to poor absorption, distribution, metabolism, and excretion (ADME) properties. We hypothesized that a bioisosteric amide-to-ester substitution could lead to improvements in both physicochemical properties and bioactivity. Using model compounds, bearing either amides or esters, we identify parameters for optimal lipophilicity and permeability. We applied these learnings to design a set of novel amide-to-ester-substituted, VHL-based BET degraders with the goal to increase permeability. Our ester PROTACs retained intracellular stability, were overall more potent degraders than their amide counterparts, and showed an earlier onset of the hook effect. These enhancements were driven by greater cell permeability rather than improvements in ternary complex formation. This largely unexplored amide-to-ester substitution provides a simple strategy to enhance PROTAC permeability and bioactivity and may prove beneficial to other beyond Ro5 molecules.

A comprehensive study on the effect of backbone stereochemistry of a cyclic hexapeptide on membrane permeability and microsomal stability

Backbone stereochemistry of cyclic peptides has been reported to have a great influence on microsomal stability and membrane permeability, two important factors that determine oral bioavailability. Here, we comprehensively investigated the correlation between the backbone stereochemistry of cyclic hexapeptide stereoisomers and their stability in liver microsomes, as well as passive membrane permeability.

Effect of Flexibility, Lipophilicity, and the Location of Polar Residues on the Passive Membrane Permeability of a Series of Cyclic Decapeptides

Cyclic peptides have received increasing attention over the recent years as potential therapeutics for "undruggable" targets. One major obstacle is, however, their often relatively poor bioavailability. Here, we investigate the structure-permeability relationship of 24 cyclic decapeptides that share the same backbone N-methylation pattern but differ in their side chains. The peptides cover a large range of values for passive membrane permeability as well as lipophilicity and solubility. To rationalize the observed differences in permeability, we extracted for each peptide the population of the membrane-permeable conformation in water from extensive explicit-solvent molecular dynamics simulations and used this as a metric for conformational rigidity or "prefolding." The insights from the simulations together with lipophilicity measurements highlight the intricate interplay between polarity/lipophilicity and flexibility/rigidity and the possible compensating effects on permeability. The findings allow us to better understand the structure-permeability relationship of cyclic peptides and extract general guiding principles.

Large-Scale Membrane Permeability Prediction of Cyclic Peptides Crossing a Lipid Bilayer Based on Enhanced Sampling Molecular Dynamics Simulations

Membrane permeability is a significant obstacle facing the development of cyclic peptide drugs. However, membrane permeation mechanisms are poorly understood. To investigate common features of permeable (and nonpermeable) designs, it is necessary to reproduce the membrane permeation process of cyclic peptides through the lipid bilayer. We simulated the membrane permeation process of 100 six-residue cyclic peptides across the lipid bilayer based on steered molecular dynamics (MD) and replica-exchange umbrella sampling simulations and predicted membrane permeability using the inhomogeneous solubility-diffusion model and a modified version of it. Furthermore, we confirmed the effectiveness of this protocol by predicting the membrane permeability of 56 eight-residue cyclic peptides with diverse chemical structures, including some confidential designs from a pharmaceutical company. As a result, a reasonable correlation between experimentally assessed and calculated membrane permeability of cyclic peptides was observed for the peptide libraries, except for strongly hydrophobic peptides. Our analysis of the MD trajectory demonstrated that most peptides were stabilized in the boundary region between bulk water and membrane and that for most peptides, the process of crossing the center of the membrane is the main obstacle to membrane permeation. The height of this barrier is well correlated with the electrostatic interaction between the peptide and the surrounding media. The structural and energetic features of the representative peptide at each vertical position within the membrane were also analyzed, revealing that peptides permeate the membrane by changing their orientation and conformation according to the surrounding environment.

Permeability prediction in the beyond-Rule-of 5 chemical space: Focus on cyclic hexapeptides

Cyclic peptides (CPs) are gaining more and more relevance in drug discovery. Since one of their main drawbacks is poor permeability, the discovery of new orally available CP drugs requires computational tools that predict CP permeability in very early drug discovery. In this study we used a literature dataset of 62 cyclic hexapeptides to evaluate the performances of a number of in silico tools based on different computational theory to model and rationalize PAMPA and Caco-2 permeability values. In particular, we submitted the dataset to a) online calculators, b) QSPR strategies, c) a physics-based tool, d) a mixed approach and e) a kinetic method. This latter is an emergent strategy in which a few relevant conformations retrieved from a set of molecular dynamics (MD) simulations by the Markov State Model (MSM) are used to establish the compounds permeability. Both free and commercial software were used. Results were compared with a model based on experimental physicochemical descriptors. All the computational approaches but online calculators performed quite well and show that lipophilicity and not polarity is the main determinant of the investigated event. A second major outcome of the study is that the impact of flexibility on the permeability of the considered dataset cannot be unambiguously assessed. Finally, our comparative analysis, which also included not common applied strategies, allowed a sound evaluation of the pros and cons of the applied computational approaches.

From Conception to Development: Investigating PROTACs Features for Improved Cell Permeability and Successful Protein Degradation

Proteolysis Targeting Chimeras (PROTACs) are heterobifunctional degraders that specifically eliminate targeted proteins by hijacking the ubiquitin-proteasome system (UPS). This modality has emerged as an orthogonal approach to the use of small-molecule inhibitors for knocking down classic targets and disease-related proteins classified, until now, as "undruggable." In early 2019, the first targeted protein degraders reached the clinic, drawing attention to PROTACs as one of the most appealing technology in the drug discovery landscape. Despite these promising results, PROTACs are often affected by poor cellular permeability due to their high molecular weight (MW) and large exposed polar surface area (PSA). Herein, we report a comprehensive record of PROTAC design, pharmacology and thermodynamic challenges and solutions, as well as some of the available strategies to enhance cellular uptake, including suggestions of promising biological tools for the in vitro evaluation of PROTACs permeability toward successful protein degradation.

Structure, solubility, and permeability relationships in a diverse middle molecule library

To develop methodology to predict the potential druggability of middle molecules, we examined the structure, solubility, and permeability relationships of a diverse library (HKDL ver.1) consisting of 510 molecules (359 natural product derivatives, 76 non-natural products, 46 natural products, and 29 non-natural product derivatives). The library included peptides, depsipeptides, macrolides, and lignans, and 476 of the 510 compounds had a molecular weight in the range of 500-2000 Da. The solubility and passive diffusion velocity of the middle molecules were assessed using the parallel artificial membrane permeability assay (PAMPA). Quantitative values of solubility of 471 molecules and passive diffusion velocity of 287 molecules were obtained, and their correlations with the structural features of the molecules were examined. Based on the results, we propose a method to predict the passive diffusion characteristics of middle molecules from their three-dimensional structural features.

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.

Connecting Hydrophobic Surfaces in Cyclic Peptides Increases Membrane Permeability

N- or C-methylation in natural and synthetic cyclic peptides can increase membrane permeability, but it remains unclear why this happens in some cases but not others. Here we compare three-dimensional structures for cyclic peptides from six families, including isomers differing only in the location of an N- or Cα-methyl substituent. We show that a single methyl group only increases membrane permeability when it connects or expands hydrophobic surface patches. Positional isomers, with the same molecular weight, hydrogen bond donors/acceptors, rotatable bonds, calculated LogP, topological polar surface area, and total hydrophobic surface area, can have different membrane permeabilities that correlate with the size of the largest continuous hydrophobic surface patch. These results illuminate a key local molecular determinant of membrane permeability.

Geometrically Diverse Lariat Peptide Scaffolds Reveal an Untapped Chemical Space of High Membrane Permeability

Constrained, membrane-permeable peptides offer the possibility of engaging challenging intracellular targets. Structure-permeability relationships have been extensively studied in cyclic peptides whose backbones are cyclized from head to tail, like the membrane permeable and orally bioavailable natural product cyclosporine A. In contrast, the physicochemical properties of lariat peptides, which are cyclized from one of the termini onto a side chain, have received little attention. Many lariat peptide natural products exhibit interesting biological activities, and some, such as griselimycin and didemnin B, are membrane permeable and have intracellular targets. To investigate the structure-permeability relationships in the chemical space exemplified by these natural products, we generated a library of scaffolds using stable isotopes to encode stereochemistry and determined the passive membrane permeability of over 1000 novel lariat peptide scaffolds with molecular weights around 1000. Many lariats were surprisingly permeable, comparable to many known orally bioavailable drugs. Passive permeability was strongly dependent on N-methylation, stereochemistry, and ring topology. A variety of structure-permeability trends were observed including a relationship between alternating stereochemistry and high permeability, as well as a set of highly permeable consensus sequences. For the first time, robust structure-permeability relationships are established in synthetic lariat peptides exceeding 1000 compounds.

Development and Regulatory Challenges for Peptide Therapeutics

There has been an increased interest in and activity for the use of peptide therapeutics to treat a variety of human diseases. The number of peptide drugs entering clinical development and the market has increased significantly over the past decade despite inherent challenges of peptide therapeutic discovery, development, and patient-friendly delivery. Disparities in interpretation and application of existing regulatory guidances to innovative synthetic and conjugated peptide assets have resulted in challenges for both regulators and sponsors. The Symposium on Development and Regulatory Challenges for Peptide Therapeutics at the 40th Annual Meeting of the American College of Toxicology held in November of 2019 focused on the following specific topics: (1) peptide therapeutic progress and future directions, and approaches to discover, optimize, assess, and deliver combination peptide therapeutics for treatment of diseases; (2) toxicological considerations to advance peptide drug-device combination products for efficient development and optimal patient benefit and adherence; (3) industry and regulatory perspectives on the regulation of synthetic and conjugated peptide products, including exploration of regulatory classifications, interpretations, and application of the existing guidances International Council for Harmonisation (ICH) M3(R2) and ICH S6(R1) in determining nonclinical study recommendations; and (4) presentation of the 2016 Health and Environmental Sciences Institute's Genetic Toxicology Technical Committee working group assessment of genotoxicity testing requirements. Perspectives were shared from industry and regulatory scientists working in the peptide therapeutics field followed by an open forum panel discussion to discuss questions drafted for the peptide therapeutics scientific community, which will be discussed in more detail.

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.

Improving Membrane Permeation in the Beyond Rule-of-Five Space by Using Prodrugs to Mask Hydrogen Bond Donors

A wide range of drug targets can be effectively modulated by peptides and macrocycles. Unfortunately, the size and polarity of these compounds prevents them from crossing the cell membrane to reach target sites in the cell cytosol. As such, these compounds do not conform to standard measures of drug-likeness and exist in beyond the rule-of-five space. In this work, we investigate whether prodrug moieties that mask hydrogen bond donors can be applied in the beyond rule-of-five domain to improve the permeation of macrocyclic compounds. Using a cyclic peptide model, we show that masking hydrogen bond donors in the natural polar amino acid residues (His, Ser, Gln, Asn, Glu, Asp, Lys, and Arg) imparts membrane permeability to the otherwise impermeable parent molecules, even though the addition of the masking group increases the overall compound molecular weight and the number of hydrogen bond acceptors. We demonstrate this strategy in PAMPA and Caco2 membrane permeability assays and show that masking with groups that reduce the number of hydrogen-bond donors at the cost of additional mass and hydrogen bond acceptors, a donor-acceptor swap, is effective.

High Cell Permeability Does Not Predict Oral Bioavailability for Analogues of Cyclic Heptapeptide Sanguinamide A

The cyclic heptapeptide derivative, sanguinamide A, is a model scaffold for studying how component amino acids, heterocycles, and N-methylation influence membrane permeability and oral bioavailability. Membrane permeable sanguinamide A analogues have been reported, but there is limited data on their pharmacokinetic properties invivo. Here we report pharmacokinetic properties for highly cell and membrane permeable sanguinamide A analogues in rats and find that there is no correlation between reported permeability invitro and oral bioavailability invivo. We show that N-methylation of sanguinamide A analogues gives compounds with greater flexibility, greater susceptibility to degradation by rat liver microsomes, and lower oral bioavailability in rats.

Permeability of Cyclic Peptide Macrocycles and Cyclotides and Their Potential as Therapeutics

Macrocycles have emerged as a viable approach for the modulation of tough targets in drug discovery. In this Innovations article we discuss recent progress toward the design of cell permeable and orally bioavailable peptide macrocycles and cyclotides and provide a perspective for their potential as therapeutics. We highlight design concepts that may be broadly relevant to drug discovery efforts beyond the rule of five.

In Silico Prediction of PAMPA Effective Permeability Using a Two-QSAR Approach

Oral administration is the preferred and predominant route of choice for medication. As such, drug absorption is one of critical drug metabolism and pharmacokinetics (DM/PK) parameters that should be taken into consideration in the process of drug discovery and development. The cell-free in vitro parallel artificial membrane permeability assay (PAMPA) has been adopted as the primary screening to assess the passive diffusion of compounds in the practical applications. A classical quantitative structure–activity relationship (QSAR) model and a machine learning (ML)-based QSAR model were derived using the partial least square (PLS) scheme and hierarchical support vector regression (HSVR) scheme to elucidate the underlying passive diffusion mechanism and to predict the PAMPA effective permeability, respectively, in this study. It was observed that HSVR executed better than PLS as manifested by the predictions of the samples in the training set, test set, and outlier set as well as various statistical assessments. When applied to the mock test, which was designated to mimic real challenges, HSVR also showed better predictive performance. PLS, conversely, cannot cover some mechanistically interpretable relationships between descriptors and permeability. Accordingly, the synergy of predictive HSVR and interpretable PLS models can be greatly useful in facilitating drug discovery and development by predicting passive diffusion.

Cyclic Peptide Design Guided by Residual Dipolar Couplings, J-Couplings, and Intramolecular Hydrogen Bond Analysis

Cyclic peptides have long tantalized drug designers with their potential ability to combine the best attributes of antibodies and small molecules. An ideal cyclic peptide drug candidate would be able to recognize a protein surface like an antibody while achieving the oral bioavailability of a small molecule. It has been hypothesized that such cyclic peptides balance permeability and solubility using their solvent-dependent conformational flexibility. Herein we report a conformational deconvolution NMR methodology that combines residual dipolar couplings, J-couplings, and intramolecular hydrogen bond analysis along with conformational analysis using molecular dynamics simulations and density functional theory calculations for studying cyclic peptide conformations in both low-dielectric solvent (chloroform) and high-dielectric solvent (DMSO) to experimentally study the solvent-dependent conformational change hypothesis. Taken together, the combined experimental and computational approaches can illuminate conformational ensembles of cyclic peptides in solution and help identify design opportunities for better permeability.

Design Principles for Intestinal Permeability of Cyclic Peptides

One of the most exciting facets of cyclic peptides is that they have the potential to be orally bioavailable, despite having physical properties well beyond the traditional "Rule-of-5" chemistry space (Lipinski et al., Adv Drug Deliv Rev. 23(1): 3-25, 1997). An important component of meeting this challenge is to design cyclic peptides with good intestinal permeability. Here we discuss the design principles for intestinal permeability that have been developed in recent year. These principles can be subdivided into three regimes: physical property guidelines, design strategies for the macrocyclic ring, and design strategies for side chains. The most important overall aims are to minimize solvent-exposed polarity while keeping size, flexibility, and lipophilicity within favorable ranges, thereby allowing peptide chemists to achieve intestinal permeability in addition to other important properties for their compounds, such as solubility and binding affinity. Here we describe a variety of design strategies that have been developed to help peptide chemists in this endeavor.

Synthesis, Racemic X-ray Crystallographic, and Permeability Studies of Bioactive Orbitides from Jatropha Species

Orbitides are small cyclic peptides with a diverse range of therapeutic bioactivities. They are produced by many plant species, including those of the Jatropha genus. Here, the objective was to provide new structural information on orbitides to complement the growing knowledge base on orbitide sequences and activities by focusing on three Jatropha orbitides: ribifolin (1), pohlianin C (7), and jatrophidin (12). To determine three-dimensional structures, racemic crystallography, an emerging structural technique that enables rapid crystallization of biomolecules by combining equal amounts of the two enantiomers, was used. The high-resolution structure of ribifolin (0.99 Å) was elucidated from its racemate and showed it was identical to the structure crystallized from its l-enantiomer only (1.35 Å). Racemic crystallography was also used to elucidate high-resolution structures of pohlianin C (1.20 Å) and jatrophidin (1.03 Å), for which there was difficulty forming crystals without using racemic mixtures. The structures were used to interpret membrane permeability data in PAMPA and a Caco-2 cell assay, showing they had poor permeability. Overall, the results show racemic crystallography can be used to obtain high-resolution structures of orbitides and is useful when enantiopure samples are difficult to crystallize or solution structures from NMR are of low resolution.

Impact of Dynamically Exposed Polarity on Permeability and Solubility of Chameleonic Drugs Beyond the Rule of 5

Conformational flexibility has been proposed to significantly affect drug properties outside rule-of-5 (Ro5) chemical space. Here, we investigated the influence of dynamically exposed polarity on cell permeability and aqueous solubility for a structurally diverse set of drugs and clinical candidates far beyond the Ro5, all of which populated multiple distinct conformations as revealed by X-ray crystallography. Efflux-inhibited (passive) Caco-2 cell permeability correlated strongly with the compounds' minimum solvent-accessible 3D polar surface areas (PSA), whereas aqueous solubility depended less on the specific 3D conformation. Inspection of the crystal structures highlighted flexibly linked aromatic side chains and dynamically forming intramolecular hydrogen bonds as particularly effective in providing "chameleonic" properties that allow compounds to display both high cell permeability and aqueous solubility. These structural features, in combination with permeability predictions based on the correlation to solvent-accessible 3D PSA, should inspire drug design in the challenging chemical space far beyond the Ro5.

Macrocyclic α helical peptide therapeutic modality: A perspective of learnings and challenges

Macrocyclic α-helical peptides have emerged as a compelling new therapeutic modality to tackle targets confined to the intracellular compartment. Within the scope of hydrocarbon-stapling there has been significant progress to date, including the first stapled α-helical peptide to enter into clinical trials. The principal design concept of stapled α-helical peptides is to mimic a cognate (protein) ligand relative to binding its target via an α-helical interface. However, it was the proclivity of such stapled α-helical peptides to exhibit cell permeability and proteolytic stability that underscored their promise as unique macrocyclic peptide drugs for intracellular targets. This perspective highlights key learnings as well as challenges in basic research with respect to structure-based design, innovative chemistry, cell permeability and proteolytic stability that are essential to fulfill the promise of stapled α-helical peptide drug development.