Structural and conformational determinants of macrocycle cell permeability

Large Libraries of Structurally Diverse Macrocycles Suitable for Membrane Permeation

Macrocycles offer an attractive format for drug development due to their good binding properties and potential to cross cell membranes. To efficiently identify macrocyclic ligands for new targets, methods for the synthesis and screening of large combinatorial libraries of small cyclic peptides were developed, many of them using thiol groups for efficient peptide macrocyclization. However, a weakness of these libraries is that invariant thiol-containing building blocks such as cysteine are used, resulting in a region that does not contribute to library diversity but increases molecule size. Herein, we synthesized a series of structurally diverse thiol-containing elements and used them for the combinatorial synthesis of a 2,688-member library of small, structurally diverse peptidic macrocycles with unprecedented skeletal complexity. We then used this library to discover potent thrombin and plasma kallikrein inhibitors, some also demonstrating favorable membrane permeability. X-ray structure analysis of macrocycle-target complexes showed that the size and shape of the newly developed thiol elements are key for binding. The strategy and library format presented in this work significantly enhance structural diversity by allowing combinatorial modifications to a previously invariant region of peptide macrocycles, which may be broadly applied in the development of membrane permeable therapeutics.

Synthesis and Functionalization of Azetidine-Containing Small Macrocyclic Peptides

Cyclic peptides are increasingly important structures in drugs but their development can be impeded by difficulties associated with their synthesis. Here, we introduce the 3-aminoazetidine (3-AAz) subunit as a new turn-inducing element for the efficient synthesis of small head-to-tail cyclic peptides. Greatly improved cyclizations of tetra-, penta- and hexapeptides (28 examples) under standard reaction conditions are achieved by introduction of this element within the linear peptide precursor. Post-cyclization deprotection of the amino acid side chains with strong acid is realized without degradation of the strained four-membered azetidine. A special feature of this chemistry is that further late-stage modification of the resultant macrocyclic peptides can be achieved via the 3-AAz unit. This is done by: (i) chemoselective deprotection and substitution at the azetidine nitrogen, or by (ii) a click-based approach employing a 2-propynyl carbamate on the azetidine nitrogen. In this way, a range of dye and biotin tagged macrocycles are readily produced. Structural insights gained by XRD analysis of a cyclic tetrapeptide indicate that the azetidine ring encourages access to the less stable, all-trans conformation. Moreover, introduction of a 3-AAz into a representative cyclohexapeptide improves stability towards proteases compared to the homodetic macrocycle.

Metabolism-driven in vitro/in vivo disconnect of an oral ERɑ VHL-PROTAC

Targeting the estrogen receptor alpha (ERα) pathway is validated in the clinic as an effective means to treat ER+ breast cancers. Here we present the development of a VHL-targeting and orally bioavailable proteolysis-targeting chimera (PROTAC) degrader of ERα. In vitro studies with this PROTAC demonstrate excellent ERα degradation and ER antagonism in ER+ breast cancer cell lines. However, upon dosing the compound in vivo we observe an in vitro-in vivo disconnect. ERα degradation is lower in vivo than expected based on the in vitro data. Investigation into potential causes for the reduced maximal degradation reveals that metabolic instability of the PROTAC linker generates metabolites that compete for binding to ERα with the full PROTAC, limiting degradation. This observation highlights the requirement for metabolically stable PROTACs to ensure maximal efficacy and thus optimisation of the linker should be a key consideration when designing PROTACs.

De novo development of small cyclic peptides that are orally bioavailable

Cyclic peptides can bind challenging disease targets with high affinity and specificity, offering enormous opportunities for addressing unmet medical needs. However, as with biological drugs, most cyclic peptides cannot be applied orally because they are rapidly digested and/or display low absorption in the gastrointestinal tract, hampering their development as therapeutics. In this study, we developed a combinatorial synthesis and screening approach based on sequential cyclization and one-pot peptide acylation and screening, with the possibility of simultaneously interrogating activity and permeability. In a proof of concept, we synthesized a library of 8,448 cyclic peptides and screened them against the disease target thrombin. Our workflow allowed multiple iterative cycles of library synthesis and yielded cyclic peptides with nanomolar affinities, high stabilities and an oral bioavailability (%F) as high as 18% in rats. This method for generating orally available peptides is general and provides a promising push toward unlocking the full potential of peptides as therapeutics.

Beyond Rule of Five and PROTACs in Modern Drug Discovery: Polarity Reducers, Chameleonicity, and the Evolving Physicochemical Landscape

Developing orally bioavailable drugs demands an understanding of absorption in early drug development. Traditional methods and physicochemical properties optimize absorption for rule of five (Ro5) compounds; beyond rule of five (bRo5) drugs necessitate advanced tools like the experimental measure of exposed polarity (EPSA) and the AbbVie multiparametric score (AB-MPS). Analyzing AB-MPS and EPSA against ∼1000 compounds with human absorption data and ∼10,000 AbbVie tool compounds (∼1000 proteolysis targeting chimeras or PROTACs, ∼7000 Ro5s, and ∼2000 bRo5s) revealed new patterns of physicochemical trends. We introduced a high-throughput "polarity reduction" descriptor: ETR, the EPSA-to-topological polar surface area (TPSA) ratio, highlights unique bRo5 and PROTAC subsets for specialized drug design strategies for effective absorption. Our methods and guidelines refine drug design by providing innovative in vitro approaches, enhancing physicochemical property optimization, and enabling accurate predictions of intestinal absorption in the complex bRo5 domain.

Total Synthesis and Determination of the Absolute Configuration of Berkeleylactone I

Herein, we report the first total synthesis of berkeleylactone I and its 12S diastereomer. Consequently, this chemical synthesis allowed us to establish the unknown absolute stereochemistry at the C-12 center as 12R, which was unidentified by the isolation group. This synthetic approach includes several critical reactions, such as the Sharpless asymmetric dihydroxylation, Baran's Ni-catalyzed alkyl-alkyl cross-coupling reaction, Brown allylation, Mitsunobu reaction, and ring-closing metathesis, as key steps.

A new workflow for the effective curation of membrane permeability data from open ADME information

Membrane permeability is an in vitro parameter that represents the apparent permeability (Papp) of a compound, and is a key absorption, distribution, metabolism, and excretion parameter in drug development. Although the Caco-2 cell lines are the most used cell lines to measure Papp, other cell lines, such as the Madin-Darby Canine Kidney (MDCK), LLC-Pig Kidney 1 (LLC-PK1), and Ralph Russ Canine Kidney (RRCK) cell lines, can also be used to estimate Papp. Therefore, constructing in silico models for Papp estimation using the MDCK, LLC-PK1, and RRCK cell lines requires collecting extensive amounts of in vitro Papp data. An open database offers extensive measurements of various compounds covering a vast chemical space; however, concerns were reported on the use of data published in open databases without the appropriate accuracy and quality checks. Ensuring the quality of datasets for training in silico models is critical because artificial intelligence (AI, including deep learning) was used to develop models to predict various pharmacokinetic properties, and data quality affects the performance of these models. Hence, careful curation of the collected data is imperative. Herein, we developed a new workflow that supports automatic curation of Papp data measured in the MDCK, LLC-PK1, and RRCK cell lines collected from ChEMBL using KNIME. The workflow consisted of four main phases. Data were extracted from ChEMBL and filtered to identify the target protocols. A total of 1661 high-quality entries were retained after checking 436 articles. The workflow is freely available, can be updated, and has high reusability. Our study provides a novel approach for data quality analysis and accelerates the development of helpful in silico models for effective drug discovery. Scientific Contribution: The cost of building highly accurate predictive models can be significantly reduced by automating the collection of reliable measurement data. Our tool reduces the time and effort required for data collection and will enable researchers to focus on constructing high-performance in silico models for other types of analysis. To the best of our knowledge, no such tool is available in the literature.

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.

Evaluating physiochemical properties of FDA-approved orally administered drugs

INTRODUCTION

Analyses of orally administered FDA-approved drugs from 1990 to 1993 enabled the identification of a set of physiochemical properties known as Lipinski's Rule of Five (Ro5). The original Ro5 and extended versions still remain the reference criteria for drug development programs. Since many bioactive compounds do not conform to the Ro5, we validated the relevance of and adherence to these rulesets in a contemporary cohort of FDA-approved drugs.

AREAS COVERED

The authors noted that a significant proportion of FDA-approved orally administered parent compounds from 2011 to 2022 deviate from the original Ro5 criteria (~38%) or the Ro5 with extensions (~53%). They then evaluated if a contemporary Ro5 criteria (cRo5) could be devised to better predict oral bioavailability. Furthermore, they discuss many case studies showcasing the need for and benefit of increasing the size of certain compounds and cover several evolving strategies for improving oral bioavailability.

EXPERT OPINION

Despite many revisions to the Ro5, the authors find that no single proposed physiochemical rule has universal concordance with absolute oral bioavailability. Innovations in drug delivery and formulation have dramatically expanded the range of physicochemical properties and the chemical diversity for oral administration.

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.

Molecular chameleons in drug discovery

Molecular chameleons possess a flexibility that allows them to dynamically shield or expose polar functionalities in response to the properties of the environment. Although the concept of molecular chameleons was introduced already in 1970, interest in them has grown considerably since the 2010s, when drug discovery has focused to an increased extent on new chemical modalities. Such modalities include cyclic peptides, macrocycles and proteolysis-targeting chimeras, all of which reside in a chemical space far from that of traditional small-molecule drugs. Both cell permeability and aqueous solubility are required for the oral absorption of drugs. Engineering these properties, and potent target binding, into the larger new modalities is a more daunting task than for traditional small-molecule drugs. The ability of chameleons to adapt to different environments may be essential for success. In this Review, we provide both general and theoretical insights into the realm of molecular chameleons. We discuss why chameleons have come into fashion and provide a do-it-yourself toolbox for their design; we then provide a glimpse of how advanced in silico methods can support molecular chameleon design.

[Evaluation of Solubility and Membrane Permeability of Middle-Molecule Compounds Using Artificial Membranes and Living Cells]

In contrast to small molecules, middle molecules present a promising therapeutic modality owing to their elevated specificity, minimal adverse effects, capacity to target protein-protein interactions, and, unlike antibody-based drugs, their suitability for oral administration and intracellular target engagement. Post-oral administration, the paramount considerations encompass solubility and membrane permeability during the initial phase until the drug attains systemic circulation. Furthermore, penetration of the cell membrane is essential to accessing intracellular targets. We evaluated the solubility and membrane permeability of 965 compounds sourced from middle molecule libraries affiliated with Hokkaido University, Kitasato University, and the University of Tokyo. To gauge membrane permeability, we employed both the parallel artificial membrane permeability assay (PAMPA) and Caco-2 cell monolayers. Notably, while membrane permeability in Caco-2 cells exhibited an approximate threefold increase in comparison to PAMPA measurements, certain compounds demonstrated permeability levels less than one-third of those observed in Caco-2 cells. Recognizing the potential involvement of efflux transporters expressed in Caco-2 cells in these variations, we conducted additional assessments involving directional transport in the presence of a transporter inhibitor. Our findings suggest that nearly 80% of these compounds serve as substrates for efflux transporters. Considering the relevance of intracellular targets, we shifted our focus from membrane permeation to intracellular uptake, conducting simulations tailored to assess cellular uptake.

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.

Pharmaceutical Development Challenges in a Beyond Rule of Five Prodrug: Case Study of ABBV-167, Phosphate Prodrug of Venetoclax

ABBV-167, a phosphate prodrug of BCL-2 inhibitor venetoclax, was recently progressed into the clinic as an alternative means of reducing pill burden for patients in high-dose indications. The dramatically enhanced aqueous solubility of ABBV-167 allowed for high drug loading within a crystalline tablet and, when administered in phase I clinical study, conferred venetoclax exposure commensurate with the equivalent dose administered as an amorphous solid dispersion. In enabling the progression into the clinic, we performed a comprehensive evaluation of the CMC development aspects of this beyond the rule of five (bRo5) prodrug. Adding a phosphate moiety resulted in excessively complex chemical speciation and solid form landscapes with significant physical-chemical stability liabilities. A combination of experimental and computational methods including microelectron diffraction (MicroED), total scattering, tablet colorimetry, finite element, and molecular dynamics modeling were used to understand CMC developability across drug substance and product manufacture and storage. The prodrug's chemical structural characteristics and loose crystal packing were found to be responsible for the loss of crystallinity during its manufacturing, which in turn led to high solid-state chemical reactivity and poor shelf life stability. The ABBV-167 case exemplifies key CMC development challenges for complex chemical matter such as bRo5 phosphate prodrugs with significant ramifications during drug substance and drug product manufacturing and storage.

Beyond Rule-of-five: Permeability Assessment of Semipeptidic Macrocycles

Compounds beyond the rule-of-five are generating interest as they expand the molecular toolbox for modulating targets previously considered "undruggable". Macrocyclic peptides are an efficient class of molecules for modulating protein-protein interactions. However, predicting their permeability is difficult as they differ from small molecules. Although constrained by macrocyclization, they generally retain some conformational flexibility associated with an enhanced ability to cross biological membranes. In this study, we investigated the relationship between the structure of semi-peptidic macrocycles and their membrane permeability through structural modifications. Based on a scaffold of four amino acids and a linker, we synthesized 56 macrocycles incorporating modifications in either stereochemistry, N-methylation, or lipophilicity and assessed their passive permeability using the parallel artificial membrane permeability assay (PAMPA). Our results show that some semi-peptidic macrocycles have adequate passive permeability even with properties outside the Lipinski rule of five. We found that N-methylation in position 2 and the addition of lipophilic groups to the side chain of tyrosine led to an improvement in permeability with a decrease in tPSA and 3D-PSA. This enhancement could be attributed to the shielding effect of the lipophilic group on some regions of the macrocycle, which in turn, facilitates a favorable macrocycle conformation for permeability, suggesting some degree of chameleonic behavior.

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.

Challenges in Permeability Assessment for Oral Drug Product Development

Drug permeation across the intestinal epithelium is a prerequisite for successful oral drug delivery. The increased interest in oral administration of peptides, as well as poorly soluble and poorly permeable compounds such as drugs for targeted protein degradation, have made permeability a key parameter in oral drug product development. This review describes the various in vitro, in silico and in vivo methodologies that are applied to determine drug permeability in the human gastrointestinal tract and identifies how they are applied in the different stages of drug development. The various methods used to predict, estimate or measure permeability values, ranging from in silico and in vitro methods all the way to studies in animals and humans, are discussed with regard to their advantages, limitations and applications. A special focus is put on novel techniques such as computational approaches, gut-on-chip models and human tissue-based models, where significant progress has been made in the last few years. In addition, the impact of permeability estimations on PK predictions in PBPK modeling, the degree to which excipients can affect drug permeability in clinical studies and the requirements for colonic drug absorption are addressed.

Targeted Protein Degradation: Advances, Challenges, and Prospects for Computational Methods

The therapeutic approach of targeted protein degradation (TPD) is gaining momentum due to its potentially superior effects compared with protein inhibition. Recent advancements in the biotech and pharmaceutical sectors have led to the development of compounds that are currently in human trials, with some showing promising clinical results. However, the use of computational tools in TPD is still limited, as it has distinct characteristics compared with traditional computational drug design methods. TPD involves creating a ternary structure (protein-degrader-ligase) responsible for the biological function, such as ubiquitination and subsequent proteasomal degradation, which depends on the spatial orientation of the protein of interest (POI) relative to E2-loaded ubiquitin. Modeling this structure necessitates a unique blend of tools initially developed for small molecules (e.g., docking) and biologics (e.g., protein-protein interaction modeling). Additionally, degrader molecules, particularly heterobifunctional degraders, are generally larger than conventional small molecule drugs, leading to challenges in determining drug-like properties like solubility and permeability. Furthermore, the catalytic nature of TPD makes occupancy-based modeling insufficient. TPD consists of multiple interconnected yet distinct steps, such as POI binding, E3 ligase binding, ternary structure interactions, ubiquitination, and degradation, along with traditional small molecule properties. A comprehensive set of tools is needed to address the dynamic nature of the induced proximity ternary complex and its implications for ubiquitination. In this Perspective, we discuss the current state of computational tools for TPD. We start by describing the series of steps involved in the degradation process and the experimental methods used to characterize them. Then, we delve into a detailed analysis of the computational tools employed in TPD. We also present an integrative approach that has proven successful for degrader design and its impact on project decisions. Finally, we examine the future prospects of computational methods in TPD and the areas with the greatest potential for impact.

Combining Chemical Protein Synthesis and Random Nonstandard Peptides Integrated Discovery for Modulating Biological Processes

Chemical manipulation of naturally occurring peptides offers a convenient route for generating analogs to screen against different therapeutic targets. However, the limited success of the conventional chemical libraries has urged chemical biologists to adopt alternative methods such as phage and mRNA displays and create libraries of a large number of variants for the screening and selection of novel peptides. Messenger RNA (mRNA) display provides great advantages in terms of the library size and the straightforward recovery of the selected polypeptide sequences. Importantly, the integration of the flexible in vitro translation (FIT) system with the mRNA display provides the basis of the random nonstandard peptides integrated discovery (RaPID) approach for the introduction of diverse nonstandard motifs, such as unnatural side chains and backbone modifications. This platform allows the discovery of functionalized peptides with tight binding against virtually any protein of interest (POI) and therefore shows great potential in the pharmaceutical industry. However, this method has been limited to targets generated by recombinant expression, excluding its applications to uniquely modified proteins, particularly those with post-translational modifications.Chemical protein synthesis allows a wide range of changes to the protein's chemical composition to be performed, including side chain and backbone modifications and access to post-translationally modified proteins, which are often inaccessible or difficult to achieve via recombinant expression methods. Notably, d-proteins can be prepared via chemical synthesis, which has been used in mirror image phase display for the discovery of nonproteolytic d-peptide binders.Combining chemical protein synthesis with the RaPID system allows the production of a library of trillions of cyclic peptides and subsequent selection for novel cyclic peptide binders targeting a uniquely modified protein to assist in studying its unexplored biology and possibly the discovery of new drug candidates.Interestingly, the small post-translational modifier protein ubiquitin (Ub), with its various polymeric forms, regulates directly or indirectly many biochemical processes, e.g., proteasomal degradation, DNA damage repair, cell cycle regulation, etc. In this Account, we discuss combining the RaPID approach against various synthetic Ub chains for selecting effective and specific macrocyclic peptide binders. This offers an advancement in modulating central Ub pathways and provides opportunities in drug discovery areas associated with Ub signaling. We highlight experimental approaches and conceptual adaptations required to design and modulate the activity of Lys48- and Lys63-linked Ub chains by macrocyclic peptides. We also present the applications of these approaches to shed light on related biological activities and ultimately their activity against cancer. Finally, we contemplate future developments still pending in this exciting multidisciplinary field.

Corneal Permeability and Uptake of Twenty-Five Drugs: Species Comparison and Quantitative Structure-Permeability Relationships

The purpose of this study was to determine corneal permeability and uptake in rabbit, porcine, and bovine corneas for twenty-five drugs using an N-in-1 (cassette) approach and relate these parameters to drug physicochemical properties and tissue thickness through quantitative structure permeability relationships (QSPRs). A twenty-five-drug cassette containing β-blockers, NSAIDs, and corticosteroids in solution at a micro-dose was exposed to the epithelial side of rabbit, porcine, or bovine corneas mounted in a diffusion chamber, and the corneal drug permeability and tissue uptake were monitored using an LC-MS/MS method. Data obtained were used to construct and evaluate over 46,000 quantitative structure-permeability (QSPR) models using multiple linear regression, and the best-fit models were cross-validated by Y-randomization. Drug permeability was generally higher in rabbit cornea and comparable between bovine and porcine corneas. Permeability differences between species could be explained in part by differences in corneal thickness. Corneal uptake between species correlated with a slope close to 1, indicating generally similar drug uptake per unit weight of tissue. A high correlation was observed between bovine, porcine, and rabbit corneas for permeability and between bovine and porcine corneas for uptake (R² ≥ 0.94). MLR models indicated that drug characteristics such as lipophilicity (LogD), heteroatom ratio (HR), nitrogen ratio (NR), hydrogen bond acceptors (HBA), rotatable bonds (RB), index of refraction (IR), and tissue thickness (TT) are of great influence on drug permeability and uptake. When data for all species along with thickness as a parameter was used in MLR, the best fit equation for permeability was Log (% transport/cm²·s) = 0.441 LogD - 8.29 IR + 8.357 NR - 0.279 HBA - 3.833 TT + 10.432 (R² = 0.826), and the best-fit equation for uptake was Log (%/g) = 0.387 LogD + 4.442 HR + 0.105 RB - 0.303 HBA - 2.235 TT + 1.422 (R² = 0.750). Thus, it is feasible to explain corneal drug delivery in three species using a single equation.

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.

Controlling the Evolution of Selective Vancomycin Resistance through Successful Ophthalmic Eye-Drop Preparation of Vancomycin-Loaded Nanoliposomes Using the Active-Loading Method

Vancomycin is the front-line defense and drug of choice for the most serious and life-threatening methicillin-resistant Staphylococcus aureus (MRSA) infections. However, poor vancomycin therapeutic practice limits its use, and there is a consequent rise of the threat of vancomycin resistance by complete loss of its antibacterial activity. Nanovesicles as a drug-delivery platform, with their featured capabilities of targeted delivery and cell penetration, are a promising strategy to resolve the shortcomings of vancomycin therapy. However, vancomycin's physicochemical properties challenge its effective loading. In this study, we used the ammonium sulfate gradient method to enhance vancomycin loading into liposomes. Depending on the pH difference between the extraliposomal vancomycin-Tris buffer solution (pH 9) and the intraliposomal ammonium sulfate solution (pH 5-6), vancomycin was actively and successfully loaded into liposomes (up to 65% entrapment efficiency), while the liposomal size was maintained at 155 nm. Vancomycin-loaded nanoliposomes effectively enhanced the bactericidal effect of vancomycin; the minimum inhibitory concentration (MIC) value for MRSA decreased 4.6-fold. Furthermore, they effectively inhibited and killed heteroresistant vancomycin-intermediate S.aureous (h-VISA) with an MIC of 0.338 μg mL^-1. Moreover, MRSA could not develop resistance against vancomycin that was loaded into and delivered by liposomes. Vancomycin-loaded nanoliposomes could be a feasible solution for enhancing vancomycin's therapeutic use and controlling the emerging vancomycin resistance.

Amide-to-ester substitution as a stable alternative to N-methylation for increasing membrane permeability in cyclic peptides

Naturally occurring peptides with high membrane permeability often have ester bonds on their backbones. However, the impact of amide-to-ester substitutions on the membrane permeability of peptides has not been directly evaluated. Here we report the effect of amide-to-ester substitutions on the membrane permeability and conformational ensemble of cyclic peptides related to membrane permeation. Amide-to-ester substitutions are shown to improve the membrane permeability of dipeptides and a model cyclic hexapeptide. NMR-based conformational analysis and enhanced sampling molecular dynamics simulations suggest that the conformational transition of the cyclic hexapeptide upon membrane permeation is differently influenced by an amide-to-ester substitution and an amide N-methylation. The effect of amide-to-ester substitution on membrane permeability of other cyclic hexapeptides, cyclic octapeptides, and a cyclic nonapeptide is also investigated to examine the scope of the substitution. Appropriate utilization of amide-to-ester substitution based on our results will facilitate the development of membrane-permeable peptides.

Passive Membrane Permeability of Sizable Acyclic β-Hairpin Peptides

The recent shift toward increasingly larger drug modalities has created a significant demand for novel classes of compounds with high membrane permeability that can inhibit intracellular protein-protein interactions (PPIs). While major advances have been made in the design of cell-permeable helices, stapled β-sheets, and cyclic peptides, the development of large acyclic β-hairpins lags far behind. Therefore, we investigated a series of 26 β-hairpins (MW > 1.6 kDa) belonging to a chemical space far beyond the Lipinski "rule of five" (fbRo5) and showed that, in addition to their innate plasticity, the lipophilicity of these peptides (log D 7.4 ≈ 0 ± 0.7) can be tuned to drastically improve the balance between aqueous solubility and passive membrane permeability.

A Model for the Rapid Assessment of Solution Structures for 24-Atom Macrocycles: The Impact of β-Branched Amino Acids on Conformation

Experiment and computation are used to develop a model to rapidly predict solution structures of macrocycles sharing the same Murcko framework. These 24-atom triazine macrocycles result from the quantitative dimerization of identical monomers presenting a hydrazine group and an acetal tethered to an amino acid linker. Monomers comprising glycine and the β-branched amino acids threonine, valine, and isoleucine yield macrocycles G-G, T-T, V-V, and I-I, respectively. Elements common to all members of the framework include the efficiency of macrocyclization (quantitative), the solution- and solid-state structures (folded), the site of protonation (opposite the auxiliary dimethylamine group), the geometry of the hydrazone (E), the C2 symmetry of the subunits (conserved), and the rotamer state adopted. In aggregate, the data reveal metrics predictive of the three-dimensional solution structure that derive from the fingerprint region of the 1D 1H spectrum and a network of rOes from a single resonance. The metrics also afford delineation of more nuanced structural features that allow subpopulations to be identified among the members of the framework. Well-tempered metadynamics provides free energy surfaces and population distributions of these macrocycles. The areas of the free energy surface decrease with increasing steric bulk (G-G > V-V ∼ T-T > I-I). In addition, the surfaces are increasingly isoenergetic with decreasing steric bulk (G-G > V-V ∼ T-T > I-I).

Predictive Modeling of PROTAC Cell Permeability with Machine Learning

Approaches for predicting proteolysis targeting chimera (PROTAC) cell permeability are of major interest to reduce resource-demanding synthesis and testing of low-permeable PROTACs. We report a comprehensive investigation of the scope and limitations of machine learning-based binary classification models developed using 17 simple descriptors for large and structurally diverse sets of cereblon (CRBN) and von Hippel-Lindau (VHL) PROTACs. For the VHL PROTAC set, kappa nearest neighbor and random forest models performed best and predicted the permeability of a blinded test set with >80% accuracy (k ≥ 0.57). Models retrained by combining the original training and the blinded test set performed equally well for a second blinded VHL set. However, models for CRBN PROTACs were less successful, mainly due to the imbalanced nature of the CRBN datasets. All descriptors contributed to the models, but size and lipophilicity were the most important. We conclude that properly trained machine learning models can be integrated as effective filters in the PROTAC design process.

Simulation Reveals the Chameleonic Behavior of Macrocycles

Conformational analysis is central to the design of bioactive molecules. It is particularly challenging for macrocycles due to noncovalent transannular interactions, steric interactions, and ring strain that are often coupled. Herein, we simulated the conformations of five macrocycles designed to express a progression of increasing complexity in environment-dependent intramolecular interactions and verified the results against NMR measurements in chloroform and dimethyl sulfoxide. Molecular dynamics using an explicit solvent model, but not the Monte Carlo method with implicit solvation, handled both solvents correctly. Refinement of conformations at the ab initio level was fundamental to reproducing the experimental observations─standard state-of-the-art molecular mechanics force fields were insufficient. Our simulations correctly predicted the intramolecular interactions between side chains and the macrocycle and revealed an unprecedented solvent-induced conformational switch of the macrocyclic ring. Our results provide a platform for the rational, prospective design of molecular chameleons that adapt to the properties of the environment.

Using Macrocyclic G-Quadruplex Ligands to Decipher the Interactions Between Small Molecules and G-Quadruplex DNA

This study aims to deepen the knowledge of the current state of rational G4-ligand design through the design and synthesis of a novel set of compounds based on indoles, quinolines, and benzofurans and their comparisons with well-known G4-ligands. This resulted in novel synthetic methods and G4-ligands that bind and stabilize G4 DNA with high selectivity. Furthermore, the study corroborates previous studies on the design of G4-ligands and adds deeper explanations to why a) macrocycles offer advantages in terms of G4-binding and -selectivity, b) molecular pre-organization is of key importance in the development of strong novel binders, c) an electron-deficient aromatic core is essential to engage in strong arene-arene interactions with the G4-surface, and d) aliphatic amines can strengthen interactions indirectly through changing the arene electrostatic nature of the compound. Finally, fundamental physicochemical properties of selected G4-binders are evaluated, underscoring the complexity of aligning the properties required for efficient G4 binding and stabilization with feasible pharmacokinetic properties.

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.

Improving the solubility and antileukemia activity of Wnt/β-catenin signaling inhibitors by disrupting molecular planarity

Leukemia cells depend on the Wnt/β-catenin signaling pathway for their growth. Pyrvinium, a known Wnt signaling inhibitor, has demonstrated promising efficacy in the treatment of the aggressive blast phase chronic myeloid leukemia (BP-CML). We previously developed potent inhibitors 1-2 for the Wnt/β-catenin signaling pathway. However, the further application of these compounds as anti-leukemia agents is limited by their modest anti-leukemia activity in cells and poor aqueous solubility, due to the high molecular planarity of the chemical scaffold. Here, we reported our efforts in the synthesis and in vitro evaluation of 18 new compounds (4a-r) that have been designed to disrupt the molecular planarity of the chemical scaffold. Several compounds of the series showed significantly improved anti-leukemia activity and aqueous solubility. As a highlight, compounds 4c not only maintained excellent inhibitory potency (IC50 = 1.3 nM) for Wnt signaling but also demonstrated good anti-leukemia potency (IC50 = 0.9 µM) in the CML K562 cells. Moreover, compound 4c had an aqueous solubility of 5.9 µg/mL, which is over 50-fold enhanced compared to its parents 1-2.

Conformational Effects on the Passive Membrane Permeability of Synthetic Macrocycles

Macrocyclic compounds (MCs) can have complex conformational properties that affect pharmacologically important behaviors such as membrane permeability. We measured the passive permeability of 3600 diverse nonpeptidic MCs and used machine learning to analyze the results. Incorporating selected properties based on the three-dimensional (3D) conformation gave models that predicted permeability with Q² = 0.81. A biased spatial distribution of polar versus nonpolar regions was particularly important for good permeability, consistent with a mechanism in which the initial insertion of nonpolar portions of a MC helps facilitate the subsequent membrane entry of more polar parts. We also examined effects on permeability of 800 substructural elements by comparing matched molecular pairs. Some substitutions were invariably beneficial or invariably deleterious to permeability, while the influence of others was highly contextual. Overall, the work provides insights into how the permeability of MCs is influenced by their 3D conformational properties and suggests design hypotheses for achieving macrocycles with high membrane permeability.

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.

RNA-Binding Macrocyclic Peptides

Being able to effectively target RNA with potent ligands will open up a large number of potential therapeutic options. The knowledge on how to achieve this is ever expanding but an important question that remains open is what chemical matter is suitable to achieve this goal. The high flexibility of an RNA as well as its more limited chemical diversity and featureless binding sites can be difficult to target selectively but can be addressed by well-designed cyclic peptides. In this review we will provide an overview of reported cyclic peptide ligands for therapeutically relevant RNA targets and discuss the methods used to discover them. We will also provide critical insights into the properties required for potent and selective interaction and suggestions on how to assess these parameters. The use of cyclic peptides to target RNA is still in its infancy but the lessons learned from past examples can be adopted for the development of novel potent and selective ligands.

Novel Macrocyclic Antagonists of the Calcitonin Gene-Related Peptide Receptor: Design, Realization, and Structural Characterization of Protein-Ligand Complexes

A series of macrocyclic calcitonin gene-related peptide (CGRP) receptor antagonists identified using structure-based design principles, exemplified by HTL0028016 (1) and HTL0028125 (2), is described. Structural characterization by X-ray crystallography of the interaction of two of the macrocycle antagonists with the CGRP receptor ectodomain is described, along with structure-activity relationships associated with point changes to the macrocyclic antagonists. The identification of non-peptidic/natural product-derived, macrocyclic ligands for a G protein coupled receptor (GPCR) is noteworthy.

Diarylamines with the Neighboring Pyridyl Group: Synthesis and Modulation of the Amine Functionality via Intramolecular H-Bonding

New pyridyl-containing diarylamines were obtained via Cu-assisted reductive amination of the ortho-2-pyridylarylboronic acids. Comparative analysis of the spectral and electrochemical data obtained for new diarylamines and their pyridyl-free counterparts revealed the intramolecular H-bond (IMHB) formation which significantly influences the properties of the amino group. The electron density at the N atom of the amino group is increased due to partial weakening of the N–H bond, although the BDE and activation energy for the H-atom abstraction is increased due to the chelating effect of two N atoms. The ortho-pyridyl-containing diarylamines are more prone to be oxidized as compared to their pyridyl-free counterparts; the shift in the oxidation potential values correlates with the strength of the intramolecular H-bonding which can be tuned by inserting substituents in the pyridyl or phenyl rings. The IMHB is reserved even in polar solvents having a significant H-acceptor ability (such as DMSO) but can be destroyed in methanol, testifying in favor of the dynamic nature of the H-bonding.

Using in vitro ADME data for lead compound selection: An emphasis on PAMPA pH 5 permeability and oral bioavailability

Membrane permeability plays an important role in oral drug absorption. Caco-2 and Madin-Darby Canine Kidney (MDCK) cell culture systems have been widely used for assessing intestinal permeability. Since most drugs are absorbed passively, Parallel Artificial Membrane Permeability Assay (PAMPA) has gained popularity as a low-cost and high-throughput method in early drug discovery when compared to high-cost, labor intensive cell-based assays. At the National Center for Advancing Translational Sciences (NCATS), PAMPA pH 5 is employed as one of the Tier I absorption, distribution, metabolism, and elimination (ADME) assays. In this study, we have developed a quantitative structure activity relationship (QSAR) model using our ∼6500 compound PAMPA pH 5 permeability dataset. Along with ensemble decision tree-based methods such as Random Forest and eXtreme Gradient Boosting, we employed deep neural network and a graph convolutional neural network to model PAMPA pH 5 permeability. The classification models trained on a balanced training set provided accuracies ranging from 71% to 78% on the external set. Of the four classifiers, the graph convolutional neural network that directly operates on molecular graphs offered the best classification performance. Additionally, an ∼85% correlation was obtained between PAMPA pH 5 permeability and in vivo oral bioavailability in mice and rats. These results suggest that data from this assay (experimental or predicted) can be used to rank-order compounds for preclinical in vivo testing with a high degree of confidence, reducing cost and attrition as well as accelerating the drug discovery process. Additionally, experimental data for 486 compounds (PubChem AID: 1645871) and the best models have been made publicly available (https://opendata.ncats.nih.gov/adme/).

Relating Conformational Equilibria to Conformer-Specific Lipophilicities: New Opportunities in Drug Discovery

Efficient drug discovery is based on a concerted effort in optimizing bioactivity and compound properties such as lipophilicity, and is guided by efficiency metrics that reflect both aspects. While conformation–activity relationships and ligand conformational control are known strategies to improve bioactivity, the use of conformer‐specific lipophilicities (logp) is much less explored. Here we show how conformer‐specific logp values can be obtained from knowledge of the macroscopic logP value, and of the equilibrium constants between the individual species in water and in octanol. This is illustrated with fluorinated amide rotamers, with integration of rotamer ¹⁹F NMR signals as a facile, direct method to obtain logp values. The difference between logp and logP optimization is highlighted, giving rise to a novel avenue for lipophilicity control in drug discovery.

Structure prediction of cyclic peptides by molecular dynamics + machine learning

Recent computational methods have made strides in discovering well-structured cyclic peptides that preferentially populate a single conformation. However, many successful cyclic-peptide therapeutics adopt multiple conformations in solution. In fact, the chameleonic properties of some cyclic peptides are likely responsible for their high cell membrane permeability. Thus, we require the ability to predict complete structural ensembles for cyclic peptides, including the majority of cyclic peptides that have broad structural ensembles, to significantly improve our ability to rationally design cyclic-peptide therapeutics. Here, we introduce the idea of using molecular dynamics simulation results to train machine learning models to enable efficient structure prediction for cyclic peptides. Using molecular dynamics simulation results for several hundred cyclic pentapeptides as the training datasets, we developed machine-learning models that can provide molecular dynamics simulation-quality predictions of structural ensembles for all the hundreds of thousands of sequences in the entire sequence space. The prediction for each individual cyclic peptide can be made using less than 1 second of computation time. Even for the most challenging classes of poorly structured cyclic peptides with broad conformational ensembles, our predictions were similar to those one would normally obtain only after running multiple days of explicit-solvent molecular dynamics simulations. The resulting method, termed StrEAMM (Structural Ensembles Achieved by Molecular Dynamics and Machine Learning), is the first technique capable of efficiently predicting complete structural ensembles of cyclic peptides without relying on additional molecular dynamics simulations, constituting a seven-order-of-magnitude improvement in speed while retaining the same accuracy as explicit-solvent simulations.

Discovery and Development of Cyclic Peptide Inhibitors of CIB1

Calcium and integrin binding protein 1 (CIB1) is a small, intracellular protein recently implicated in survival and proliferation of triple-negative breast cancer (TNBC). Considering its interactions with PAK1 and downstream signaling, CIB1 has been suggested as a potential therapeutic target in TNBC. As such, CIB1 has been the focus of inhibitor discovery efforts. To overcome issues of potency and stability in previously reported CIB1 inhibitors, we deploy mRNA display to discover new cyclic peptide inhibitors with improved biophysical properties and cellular activity. We advance UNC10245131, a cyclic peptide with low nanomolar affinity and good selectivity for CIB1 over other EF-hand domain proteins and improved permeability and stability over previously identified linear peptide inhibitor UNC10245092. Unlike UNC10245092, UNC10245131 lacks cytotoxicity and does not affect downstream signaling. Despite this, UNC10245131 is a potent ligand that could aid in clarifying roles of CIB1 in TNBC survival and proliferation and other CIB1-associated biological phenotypes.

Implications of the Conformationally Flexible, Macrocyclic Structure of the First-Generation, Direct-Acting Anti-Viral Paritaprevir on Its Solid Form Complexity and Chameleonic Behavior

Direct-acting antiviral regimens have transformed therapeutic management of hepatitis C across all prevalent genotypes. Most of the chemical matter in these regimens comprises molecules well outside the traditional drug development chemical space and presents significant challenges. Herein, the implications of high conformational flexibility and the presence of a 15-membered macrocyclic ring in paritaprevir are studied through a combination of advanced computational and experimental methods with focus on molecular chameleonicity and crystal form complexity. The ability of the molecule to toggle between high and low 3D polar surface area (PSA) conformations is underpinned by intramolecular hydrogen bonding (IMHB) interactions and intramolecular steric effects. Computational studies consequently show a very significant difference of over 75 Ų in 3D PSA between polar and apolar environments and provide the structural basis for the perplexingly favorable passive permeability of the molecule. Crystal packing and protein binding resulting in strong intermolecular interactions disrupt these intramolecular interactions. Crystalline Form I benefits from strong intermolecular interactions, whereas the weaker intermolecular interactions in Form II are partially compensated by the energetic advantage of an IMHB. Like Form I, no IMHB is observed within the receptor-bound conformation; instead, an intermolecular H-bond contributes to the potency of the molecule. The choice of metastable Form II is derisked through strategies accounting for crystal surface and packing features to manage higher form specific solid-state chemical reactivity and specific processing requirements. Overall, the results show an unambiguous link between structural features and derived properties from crystallization to dissolution, permeation, and docking into the protein pocket.

Three Methods for Peptide Cyclization Via Lactamization

Lactamization is the key step in the synthesis of many compounds with macrocyclic structure. As the interest for these types of molecules grows in various fields such as drug discovery and nanomaterials, different methodologies to access them are being developed. Three different strategies to obtain cyclic peptides via lactamization are described in this chapter: solution-phase macrocyclization following solid-phase peptide synthesis (SPPS) of the linear precursor, SPPS and on-resin cyclization on the 2-chlorotrityl chloride (2-CTC) resin, and SPPS and on-resin cyclization by native chemical ligation on the amino-PEGA resin.

Picomole-Scale Synthesis and Screening of Macrocyclic Compound Libraries by Acoustic Liquid Transfer

Macrocyclic compounds are an attractive class of therapeutic ligands against challenging targets, such as protein-protein interactions. However, the development of macrocycles as drugs is hindered by the lack of large combinatorial macrocyclic libraries, which are cumbersome, expensive, and time consuming to make, screen, and deconvolute. Here, we established a strategy for synthesizing and screening combinatorial libraries on a picomolar scale by using acoustic droplet ejection to combine building blocks at nanoliter volumes, which reduced the reaction volumes, reagent consumption, and synthesis time. As a proof-of-concept, we assembled a 2700-member target-focused macrocyclic library that we could subsequently assay in the same microtiter synthesis plates, saving the need for additional transfers and deconvolution schemes. We screened the library against the MDM2-p53 protein-protein interaction and generated micromolar and sub-micromolar inhibitors. Our approach based on acoustic liquid transfer provides a general strategy for the development of macrocycle ligands.

Identifying the Cellular Target of Cordyheptapeptide A and Synthetic Derivatives

Cordyheptapeptide A is a lipophilic cyclic peptide from the prized Cordyceps fungal genus that shows potent cytotoxicity in multiple cancer cell lines. To better understand the bioactivity and physicochemical properties of cordyheptapeptide A with the ultimate goal of identifying its cellular target, we developed a solid-phase synthesis of this multiply N-methylated cyclic heptapeptide which enabled rapid access to both side chain- and backbone-modified derivatives. Removal of one of the backbone amide N-methyl (N-Me) groups maintained bioactivity, while membrane permeability was also preserved due to the formation of a new intramolecular hydrogen bond in a low dielectric solvent. Based on its cytotoxicity profile in the NCI-60 cell line panel, as well as its phenotype in a microscopy-based cytological assay, we hypothesized that cordyheptapeptide was acting on cells as a protein synthesis inhibitor. Further studies revealed the molecular target of cordyheptapeptide A to be the eukaryotic translation elongation factor 1A (eEF1A), a target shared by other lipophilic cyclic peptide natural products. This work offers a strategy to study and improve cyclic peptide natural products while highlighting the ability of these lipophilic compounds to effectively inhibit intracellular disease targets.

Ribosomal Synthesis of Macrocyclic Peptides with β2- and β2,3-Homo-Amino Acids for the Development of Natural Product-Like Combinatorial Libraries

The development of large, natural-product-like, combinatorial macrocyclic peptide libraries is essential in the quest to develop therapeutics for "undruggable" cellular targets. Herein we report the ribosomal synthesis of macrocyclic peptides containing one or more β²-homo-amino acids (β²haa) to enable their incorporation into mRNA display-based selection libraries. We confirmed the compatibility of 14 β²-homo-amino acids, (S)- and (R)-stereochemistry, for single incorporation into a macrocyclic peptide with low to high translation efficiency. Interestingly, N-methylation of the backbone amide of β²haa prevented the incorporation of this amino acid subclass by the ribosome. Additionally, we designed and incorporated several α,β-disubstituted β^2,3-homo-amino acids (β^2,3haa) with different R-groups on the α- and β-carbons of the same amino acid. Incorporation of these β^2,3haa enables increased diversity in a single position of a macrocyclic peptide without significantly increasing the overall molecular weight, which is an important consideration for passive cell permeability. We also successfully incorporated multiple (S)-β²hAla into a single macrocycle with other non-proteinogenic amino acids, confirming that this class of β-amino acid is suitable for development of large scale macrocyclic peptide libraries.