Cyclosporin A: Conformational Complexity and Chameleonicity

Time-course cross-species transcriptomics reveals conserved hepatotoxicity pathways induced by repeated administration of cyclosporine A

Cyclosporine A (CsA) has shown efficacy against immunity-related diseases despite its toxicity in various organs, including the liver, emphasizing the need to elucidate its underlying hepatotoxicity mechanism. This study aimed to capture the alterations in genome-wide expression over time and the subsequent perturbations of corresponding pathways across species. Six data from humans, mice, and rats, including animal liver tissue, human liver microtissues, and two liver cell lines exposed to CsA toxic dose, were used. The microtissue exposed to CsA for 10 d was analyzed to obtain dynamically differentially expressed genes (DEGs). Single-time points data at 1, 3, 5, 7, and 28 d of different species were used to provide additional evidence. Using liver microtissue-based longitudinal design, DEGs that were consistently up- or down-regulated over time were captured, and the well-known mechanism involved in CsA toxicity was elucidated. Thirty DEGs that consistently changed in longitudinal data were also altered in 28-d rat in-house data with concordant expression. Some genes (e.g. TUBB2A, PLIN2, APOB) showed good concordance with identified DEGs in 1-d and 7-d mouse data. Pathway analysis revealed up-regulations of protein processing, asparagine N-linked glycosylation, and cargo concentration in the endoplasmic reticulum. Furthermore, the down-regulations of pathways related to biological oxidations and metabolite and lipid metabolism were elucidated. These pathways were also enriched in single-time-point data and conserved across species, implying their biological significance and generalizability. Overall, the human organoids-based longitudinal design coupled with cross-species validation provides temporal molecular change tracking, aiding mechanistic elucidation and biologically relevant biomarker discovery.

A novel application of hydrophilic interaction liquid chromatography for the identification of compounds with intramolecular hydrogen bonds

The incorporation of intramolecular hydrogen bonds (IMHB) into small molecules constitutes an interesting optimization strategy to afford potential drug candidates with enhanced solubility as well as permeability and consequently improved bioavailability (if metabolic stability is high). Common methods to assess IMHB rely on spectroscopic or diffraction techniques, which, however, have limited throughput when screening for hit compounds in early phases of drug discovery. Inspired by literature findings using supercritical fluid chromatography (SFC) as an indirect method for IMHB identification in a screening context, we aimed at developing a secondary chromatographic methodology taking advantage of commonly used HPLC-MS instrumentation. In this work, we explored hydrophilic interaction liquid chromatography (HILIC) and developed a method for discriminating compounds based on their hydrogen bonding features. By quantifying retention of different matched molecular pairs (MMP) and using information about their low energy conformations from quantum-mechanical calculations, we defined a hydrogen bonding-driven adsorption (kads) chromatographic parameter to assess a compound's propensity to forming IMHB. In addition to the MMP analysis, we found that the kads parameter allows for the differentiation of analytes forming IMHB regardless of the comparison with control compounds.

Unlocking the Reverse Targeting Mechanisms of Cannabidiol: Unveiling New Therapeutic Avenues

Cannabidiol (CBD) and Δ9-tetrahydrocannabinol (THC), the main components of Cannabis sativa plants, have attracted a significant amount of attention due to their biological activities. This study identified GPR18 as the target of partial agonist CBD activating the p42/p44 MAPK pathway leading to migration of endometrial epithelial cells. Induced fit docking (IFD) showed that the affinity of THC for GPR18 is higher than that of CBD, and molecular dynamics (MD) simulations showed that CBD-GPR18 complexes at 130/200 ns might have stable conformations, potentially activating GPR18 by changing the distances of key residues in its active pocket. In contrast, THC maintains "metastable" conformations, generating a "shrinking space" leading to full agonism of THC by adding mechanical constraints in GPR18's active pocket. Steered molecular dynamics (SMD) revealed GPR18's active pocket was influenced more by CBD's partial agonism compared with THC. This combined IFD-MD-SMD method may be used to explain the mechanism of activation of partial or full agonists of GPR18.

Structural and Physicochemical Features of Oral PROTACs

Achieving oral bioavailability with Proteolysis Targeting Chimeras (PROTACs) is a key challenge. Here, we report the in vivo pharmacokinetic properties in mouse, rat, and dog of four clinical oral PROTACs and compare with an internally derived data set. We use NMR to determine 3D molecular conformations and structural preorganization free in solution, and we introduce the new experimental descriptors, solvent-exposed H-bond donors (eHBD), and acceptors (eHBA). We derive an upper limit of eHBD ≤ 2 for oral PROTACs in apolar environments and show a greater tolerance for other properties (eHBA, polarity, lipophilicity, and molecular weight) than for Rule-of-5 compliant oral drugs. Within a set of structurally related PROTACs, we show that examples with eHBD > 2 have much lower oral bioavailability than those that have eHBD ≤ 2. We summarize our findings as an experimental "Rule-of-oral-PROTACs" in order to assist medicinal chemists to achieve oral bioavailability in this challenging space.

IMHB-Mediated Chameleonicity in Drug Design: A Focus on Structurally Related PROTACs

Molecular chameleonicity may enable compounds to compensate for the unfavorable ADME properties typically associated with complex molecules, such as PROTACs. Here we present a few in silico strategies to implement chameleonicity considerations in drug design. Initially, we identified six structurally related CRBN-based PROTACs targeting BET proteins and experimentally verified whether chameleonicity is needed to obtain an acceptable physicochemical profile. Then, we utilized experimental data to validate our novel computational strategies based on tools crafted to encompass a spectrum of complexities and innovative features. After confirming that the formation of IMHBs is the primary driving factor behind chameleonicity, we initially utilized conformational sampling data to define cChameCS, an IMHB-mediated, simple, and rapid chameleonicity predictor index suitable for early drug discovery. Subsequently, we identified dynamic IMHB patterns relevant to chameleonicity through molecular dynamics simulations. Finally, we proposed a workflow for designing structurally related chameleonic PROTACs of potential application in the lead optimization process.

Mechanism Analysis of Antimicrobial Peptide NoPv1 Related to Potato Late Blight through a Computer-Aided Study

Phytophthora infestans (Mont.) de Bary, the oomycotic pathogen responsible for potato late blight, is the most devastating disease of potato production. The primary pesticides used to control oomycosis are phenyl amide fungicides, which cause environmental pollution and toxic residues harmful to both human and animal health. To address this, an antimicrobial peptide, NoPv1, has been screened to target Plasmopara viticola cellulose synthase 2 (PvCesA2) to inhibit the growth of Phytophthora infestans (P. infestans). In this study, we employed AlphaFold2 to predict the three-dimensional structure of PvCesA2 along with NoPv peptides. Subsequently, utilizing computational methods, we dissected the interaction mechanism between PvCesA2 and these peptides. Based on this analysis, we performed a saturation mutation of NoPv1 and successfully obtained the double mutants DP1 and DP2 with a higher affinity for PvCesA2. Meanwhile, dynamics simulations revealed that both DP1 and DP2 utilize a mechanism akin to the barrel-stave model for penetrating the cell membrane. Furthermore, the predicted results showed that the antimicrobial activity of DP1 was superior to that of NoPv1 without being toxic to human cells. These findings may offer insights for advancing the development of eco-friendly pesticides targeting various oomycete diseases, including late blight.

Gaussian accelerated molecular dynamics simulations facilitate prediction of the permeability of cyclic peptides

Despite their widespread use as therapeutics, clinical development of small molecule drugs remains challenging. Among the many parameters that undergo optimization during the drug development process, increasing passive cell permeability (i.e., log(P)) can have some of the largest impact on potency. Cyclic peptides (CPs) have emerged as a viable alternative to small molecules, as they retain many of the advantages of small molecules (oral availability, target specificity) while being highly effective at traversing the plasma membrane. However, the relationship between the dominant conformations that typify CPs in an aqueous versus a membrane environment and cell permeability remain poorly characterized. In this study, we have used Gaussian accelerated molecular dynamics (GaMD) simulations to characterize the effect of solvent on the free energy landscape of lariat peptides, a subset of CPs that have recently shown potential for drug development (Kelly et al., JACS 2021). Differences in the free energy of lariat peptides as a function of solvent can be used to predict permeability of these molecules, and our results show that permeability is most greatly influenced by N-methylation and exposure to solvent. Our approach lays the groundwork for using GaMD as a way to virtually screen large libraries of CPs and drive forward development of CP-based therapeutics.

Taming Conformational Heterogeneity on Ion Racetrack to Unveil Principles that Drive Membrane Permeation of Cyclosporines

Our study reveals the underlying principles governing the passive membrane permeability in three large N-methylated macrocyclic peptides (N-MeMPs): cyclosporine A (CycA), Alisporivir (ALI), and cyclosporine H (CycH). We determine a series of conformers required for robust passive membrane diffusion and those relevant to other functions, such as binding to protein targets or intermediates, in the presence of solvent additives. We investigate the conformational interconversions and establish correlations with the membrane permeability. Nuclear magnetic resonance (NMR) and cyclic ion-mobility spectrometry-mass spectrometry (cIMS-MS) are employed to characterize conformational heterogeneity and identify cis-amides relevant for good membrane permeability. In addition, ion mobility selected cIMS-MS and infrared (IR) multiple-photon dissociation (IRMPD) spectroscopy experiments are conducted to evaluate the energy barriers between conformations. We observe that CycA and ALI, both cyclosporines with favorable membrane permeabilities, display multiple stable and well-defined conformers. In contrast, CycH, an epimer of CycA with limited permeability, exhibits fewer and fewer stable conformers. We demonstrate the essential role of the conformational shift from the aqueous cis MeVal11-MeBmt1 state (A1) to the closed conformation featuring cis MeLeu9-MeLeu10 (C1) in facilitating membrane permeation. Additionally, we highlight that the transition from A1 to the all-trans open conformation (O1) is specifically triggered by the presence of CaCl2. We also capture a set of conformers with cis Sar3-MeLeu4, MeLeu9-MeLeu10, denoted as I. Conformationally selected cIMS-MS and IRMPD data of [CycA+Ca]2+ show immediate repopulation of the original population distribution, suggesting that CaCl2 smooths out the energy barriers. Finally, our work presents an improved sampling molecular dynamics approach based on a refined force field that not only consistently and accurately captures established conformers of cyclosporines but also exhibits strong predictive capabilities for novel conformers.

Targeted protein degradation in CNS disorders: a promising route to novel therapeutics?

Targeted protein degradation (TPD) is a rapidly expanding field, with various PROTACs (proteolysis-targeting chimeras) in clinical trials and molecular glues such as immunomodulatory imide drugs (IMiDs) already well established in the treatment of certain blood cancers. Many current approaches are focused on oncology targets, leaving numerous potential applications underexplored. Targeting proteins for degradation offers a novel therapeutic route for targets whose inhibition remains challenging, such as protein aggregates in neurodegenerative diseases. This mini review focuses on the prospect of utilizing TPD for neurodegenerative disease targets, particularly PROTAC and molecular glue formats and opportunities for novel CNS E3 ligases. Some key challenges of utilizing such modalities including molecular design of degrader molecules, drug delivery and blood brain barrier penetrance will be discussed.

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.

Macrocycles and macrocyclization in anticancer drug discovery: Important pieces of the puzzle

Increasing disease-related proteins have been identified as novel therapeutic targets. Macrocycles are emerging as potential solutions, bridging the gap between conventional small molecules and biomacromolecules in drug discovery. Inspired by successful macrocyclic drugs of natural origins, macrocycles are attracting more attention for enhanced binding affinity and target selectivity. Due to the conformation constraint and structure preorganization, macrocycles can reach bioactive conformations more easily than parent acyclic compounds. Also, rational macrocyclization combined with sequent structural modification will help improve oral bioavailability and combat drug resistance. This review introduces various strategies to enhance membrane permeability in macrocyclization and subsequent modification, such as N-methylation, intramolecular hydrogen bonding modulation, isomerization, and reversible bicyclization. Several case studies highlight macrocyclic inhibitors targeting kinases, HDAC, and protein-protein interactions. Finally, some macrocyclic agents targeting tumor microenvironments are illustrated.

Exploring the Effects of Cyclosporin A to Isocyclosporin A Rearrangement on Ion Mobility Separation

Cyclosporin A (CycA) is a peptide secondary metabolite derived from fungi that plays a crucial role in transplantation surgery. Cyclic traveling wave ion mobility mass spectrometry (IM-MS) revealed an N → O peptidyl shift in singly protonated CycA to isocyclosporin A (isoA), whereas no such isomerization was observed for doubly protonated and sodiated molecules. CycA and isoA were able to be separated by considering doubly protonated precursors using a specific ion fragment. In parallel, sodium ion stabilization facilitated the simultaneous separation and quantitation of singly charged cyclosporin isomers with the limit of detection and coefficient of determination of 1.3% and 0.9908 for CycA in isoA and 1.0% and 0.9830 for isoA in CycA, respectively. Finally, 1H-13C gHSQC NMR experiments permitted parallel recording of up to 11 cyclosporin conformers. The ratios were determined by integrating the volume of cross-peaks of the upfield resonating hydrogen in the diastereotopic methylene group of sarcosine-3.

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.

Backbone N-methylation of peptides: Advances in synthesis and applications in pharmaceutical drug development

Peptide-based drugs have garnered considerable attention in recent years owing to their increasingly crucial role in the treatment of diverse diseases. However, the limited pharmacokinetic properties of peptides have hindered their full potential. One prominent strategy for enhancing the druggability of peptides is N-methylation, which involves the addition of a methyl group to the nitrogen atom of the peptide backbone. This modification significantly improves the stability, bioavailability, receptor binding affinity and selectivity of peptide drug candidates. In this review, we provide a comprehensive overview of the advancements in synthetic methods for N-methylated peptide synthesis, as well as the associated limitations. Moreover, we explore the versatile effects of N-methylation on various aspects of peptide properties. Furthermore, we emphasize the efforts dedicated to N-methylated peptide pharmaceuticals that have successfully obtained marketing approval.

Adaptation of Empirical Methods to Predict the LogD of Triazine Macrocycles

Octanol/water partition coefficients guide drug design, but algorithms do not always accurately predict these values. For cationic triazine macrocycles that adopt a conserved folded shape in solution, common algorithms fall short. Here, the logD values for 12 macrocycles differing in amino acid choice were predicted and then measured experimentally. On average, AlogP, XlogP, and ChemAxon predictions deviate by 0.9, 2.8, and 3.9 log units, with XlogP overestimating lipophilicity and AlogP and ChemAxon underestimating lipophilicity. Importantly, however, a linear relationship (R2 > 0.98) exists between the values predicted by AlogP and the experimentally determined logD values, thus enabling more accurate predictions.

Controlling the Chameleonic Behavior and Membrane Permeability of Cyclosporine Derivatives via Backbone and Side Chain Modifications

Some macrocycles exhibit enhanced membrane permeability through conformational switching in different environmental polarities, a trait known as chameleonic behavior. In this study, we demonstrate specific backbone and side chain modifications that can control chameleonic behavior and passive membrane permeability using a cyclosporin O (CsO) scaffold. To quantify chameleonic behavior, we used a ratio of the population of the closed conformation obtained in polar solvent and nonpolar solvent for each CsO derivative. We found that β-hydroxylation at position 1 (1 and 3) can encode chameleonicity and improve permeability. However, the conformational stabilization induced by adding an additional transannular H-bond (2 and 5) leads to a much slower rate of membrane permeation. Our CsO scaffold provides a platform for the systematic study of the relationship among conformation, membrane permeability, solubility, and protein binding. This knowledge contributes to the discovery of potent beyond the rule of five (bRo5) macrocycles capable of targeting undruggable targets.

Chamelogk: A Chromatographic Chameleonicity Quantifier to Design Orally Bioavailable Beyond-Rule-of-5 Drugs

New chemical modalities in drug discovery include molecules belonging to the bRo5 chemical space. Because of their complex and flexible structure, bRo5 compounds often suffer from a poor solubility/permeability profile. Chameleonicity describes the capacity of a molecule to adapt to the environment through conformational changes; the design of molecular chameleons is a medicinal chemistry strategy simultaneously optimizing solubility and permeability. A default method to quantify chameleonicity in early drug discovery is still missing. Here we introduce Chamelogk, an automated, fast, and cheap chromatographic descriptor of chameleonicity. Moreover, we report measurements for 55 Ro5 and bRo5 compounds and validate our method with literature data. Then, selected case studies (macrocycles, nonmacrocyclic compounds, and PROTACs) are used to illustrate the application of Chamelogk in combination with lipophilicity (BRlogD) and polarity (Δ log kwIAM) descriptors. Overall, we show how Chamelogk deserves being included in property-based drug discovery strategies to design oral bioavailable bRo5 compounds.

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.

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).

Computational and Experimental Evidence for Templated Macrocyclization: The Role of a Hydrogen Bond Network in the Quantitative Dimerization of 24-Atom Macrocycles

In the absence of preorganization, macrocyclization reactions are often plagued by oligomeric and polymeric side products. Here, a network of hydrogen bonds was identified as the basis for quantitative yields of macrocycles derived from the dimerization of monomers. Oligomers and polymers were not observed. Macrocyclization, the result of the formation of two hydrazones, was hypothesized to proceed in two steps. After condensation to yield the monohydrazone, a network of hydrogen bonds formed to preorganize the terminal acetal and hydrazine groups for cyclization. Experimental evidence for preorganization derived from macrocycles and acyclic models. Solution NMR spectroscopy and single-crystal X-ray diffraction revealed that the macrocycles isolated from the cyclization reaction were protonated twice. These protons contributed to an intramolecular network of hydrogen bonds that engaged distant carbonyl groups to realize a long-range order. DFT calculations showed that this network of hydrogen bonds contributed 8.7 kcal/mol to stability. Acyclic models recapitulated this network in solution. Condensation of an acetal and a triazinyl hydrazine, which adopted a number of conformational isomers, yielded a hydrazone that adopted a favored rotamer conformation in solution. The critical hydrogen-bonded proton was also evident. DFT calculations of acyclic models showed that the rotamers were isoenergetic when deprotonated. Upon protonation, however, energies diverged with one low-energy rotamer adopting the conformation observed in the macrocycle. This conformation anchored the network of hydrogen bonds of the intermediate. Computation revealed that the hydrogen-bonded network in the acyclic intermediate contributed up to 14 kcal/mol of stability and preorganized the acetal and hydrazine for cyclization.

Conformational Sampling Deciphers the Chameleonic Properties of a VHL-Based Degrader

Chameleonicity (the capacity of a molecule to adapt its conformations to the environment) may help to identify orally bioavailable drugs in the beyond-Rule-of-5 chemical space. Computational methods to predict the chameleonic behaviour of degraders have not yet been reported and the identification of molecular chameleons still relies on experimental evidence. Therefore, there is a need to tune predictions with experimental data. Here, we employ PROTAC-1 (a passively cell-permeable degrader), for which NMR and physicochemical data prove the chameleonic behaviour, to benchmark the capacity of two conformational sampling algorithms and selection schemes. To characterize the conformational ensembles in both polar and nonpolar environments, we compute three molecular properties proven to be essential for cell permeability: conformer shape (radius of gyration), polarity (3D PSA), and the number of intramolecular hydrogen bonds. Energetic criteria were also considered. Infographics monitored the simultaneous variation of those properties in computed and NMR conformers. Overall, we provide key points for tuning conformational sampling tools to reproduce PROTAC-1 chameleonicity according to NMR evidence. This study is expected to improve the design of PROTAC drugs and the development of computational sustainable strategies to exploit the potential of new modalities in drug discovery.

Development of the force field for cyclosporine A

Membrane permeability of cyclic peptides is an important factor in drug design. To investigate the membrane permeability of cyclic peptides using molecular dynamics (MD) simulations, the accurate force fields for unnatural amino acids present in the cyclic peptides are required. Therefore, we developed the CHARMM force fields of the unnatural amino acids present in cyclosporin A (CsA), a cyclic peptide used as an immune suppressor. Especially for N-methyl amino acids, which contribute to the membrane permeability of cyclic peptides, we developed a grid correction map (CMAP) of the energy surface using the φ and ψ dihedral angles in the main chain of CsA. To validate the developed force field, we performed MD simulations, including the generalized replica exchange with solute tempering method, of CsA in water and chloroform solvents. The conformations of CsA in water and chloroform sampled using the developed force field were consistent with those of the experimental results of the solution nuclear magnetic resonance spectroscopy.

Pseudoprolines as stereoelectronically tunable proline isosteres

The cyclic structure of proline (Pro) confers unique conformational properties on this natural amino acid that influences polypeptide structure and function. Pseudoprolines are a family of Pro isosteres that incorporate a heteroatom, most prominently oxygen or sulfur but also silicon and selenium, to replace the C_β or C_γ carbon atom of the pyrrolidine ring. These readily synthetically accessible structural motifs can facilitate facile molecular editing in a fashion that allows modulation of the amide bond topology of dipeptide elements and influence over ring pucker. While the properties of pseudoprolines have been exploited most prominently in the design of oligopeptide analogues, they have potential application in the design and optimization of small molecules. In this Digest, we summarize the physicochemical properties of pseudoprolines and illustrate their potential in drug discovery by surveying examples of applications in the design of bioactive molecules.

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.

Momomycin, an Antiproliferative Cryptic Metabolite from the Oxytetracycline Producer Streptomyces rimosus

Natural products provide an important source of pharmaceuticals and chemical tools. Traditionally, assessment of unexplored microbial phyla has led to new natural products. However, with every new microbe, the number of orphan biosynthetic gene clusters (BGC) grows. As such, the more difficult proposition is finding new molecules from well-studied strains. Herein, we targeted Streptomyces rimosus, the widely-used oxytetracycline producer, for the discovery of new natural products. Using MALDI-MS-guided high-throughput elicitor screening (HiTES), we mapped the global secondary metabolome of S. rimosus and structurally characterized products of three cryptic BGCs, including momomycin, an unusual cyclic peptide natural product with backbone modifications and several non-canonical amino acids. We elucidated important aspects of its biosynthesis and evaluated its bioactivity. Our studies showcase HiTES as an effective approach for unearthing new chemical matter from "drained" strains.

Refinement of Computational Access to Molecular Physicochemical Properties: From Ro5 to bRo5

There is a need of computational tools to rank bRo5 drug candidates in the very early phases of drug discovery when chemical matter is unavailable. In this study, we selected three compounds: (a) a Ro5 drug (Pomalidomide), (b) a bRo5 orally available drug (Saquinavir), and (c) a polar PROTAC (CMP 98) to focus on computational access to physicochemical properties. To provide a benchmark, the three compounds were first experimentally characterized for their lipophilicity, polarity, IMHBs, and chameleonicity. To reproduce the experimental information content, we generated conformer ensembles with conformational sampling and molecular dynamics in both water and nonpolar solvents. Then we calculated Rgyr, 3D PSA, and IMHB number. An innovative pool of strategies for data analysis was then provided. Overall, we report a contribution to close the gap between experimental and computational methods for characterizing bRo5 physicochemical properties.

Atomic View of Aqueous Cyclosporine A: Unpacking a Decades-Old Mystery

An atomic view of a main aqueous conformation of cyclosporine A (CycA), an important 11-amino-acid macrocyclic immunosuppressant, is reported. For decades, it has been a grand challenge to determine the conformation of free CycA in an aqueous-like solution given its poor water solubility. Using a combination of X-ray and single-crystal neutron diffraction, we unambiguously resolve a unique conformer (A1) with a novel cis-amide between residues 11 and 1 and two water ligands that stabilize hydrogen bond networks. NMR spectroscopy and titration experiments indicate that the novel conformer is as abundant as the closed conformer in 90/10 (v/v) methanol/water and is the main conformer at 10/90 methanol/water. Five other conformers were also detected in 90/10 methanol/water, one in slow exchange with A1, another one in slow exchange with the closed form and three minor ones, one of which contains two cis amides Abu2-Sar3 and MeBmt1-MeVal11. These conformers help better understand the wide spectrum of membrane permeability observed for CycA analogues and, to some extent, the binding of CycA to protein targets.

Enhanced sampling without borders: on global biasing functions and how to reweight them

Molecular dynamics (MD) simulations are a powerful tool to follow the time evolution of biomolecular motions in atomistic resolution. However, the high computational demand of these simulations limits the timescales of motions that can be observed. To resolve this issue, so called enhanced sampling techniques are developed, which extend conventional MD algorithms to speed up the simulation process. Here, we focus on techniques that apply global biasing functions. We provide a broad overview of established enhanced sampling methods and promising new advances. As the ultimate goal is to retrieve unbiased information from biased ensembles, we also discuss benefits and limitations of common reweighting schemes. In addition to concisely summarizing critical assumptions and implications, we highlight the general application opportunities as well as uncertainties of global enhanced sampling.