Defining and navigating macrocycle chemical space

Exploring the Potential of Cyclic Peptidyl Antitumor Agents Derived from Natural Macrocyclic Peptide Phakellistatin

The exploration of novel anticancer compounds based on natural cyclopeptides has emerged as a pivotal paradigm in the contemporary advancement of macrocyclic pharmaceuticals. Phakellistatin 13 is a cycloheptapeptide derived from the brown snubby sponge and exhibits remarkable antitumor activity. In this study, we have designed and synthesized a series of chiral cyclopeptides incorporating the rigid isoindolinone moiety at various sites within the natural cycloheptapeptide Phakellistatin 13, with the aim of investigating conformationally constrained cyclopeptides as potential antitumor agents. Cyclopeptide 3, comprising alternating l-/d-amino acid residues, exhibited promising antihepatocellular carcinoma effects. Detailed biological experiments have revealed that Phakellistatin 13 analogs effectively inhibit the proliferation of tumor cells and induce apoptosis and autophagy, while also causing cell cycle arrest through the modulation of the p53 and mitogen-activated protein kinase (MAPK) signaling pathway. This study not only provides valuable insights into chemical structural modifications but also contributes to a deeper understanding of the biological mechanisms underlying the development of natural cyclopeptide-based drugs.

The macrocycle inhibitor landscape of SLC-transporter

In the past years the interest in Solute Carrier Transporters (SLC) has increased due to their potential as drug targets. At the same time, macrocycles demonstrated promising activities as therapeutic agents. However, the overall macrocycle/SLC-transporter interaction landscape has not been fully revealed yet. In this study, we present a statistical analysis of macrocycles with measured activity against SLC-transporter. Using a data mining pipeline based on KNIME retrieved in total 825 bioactivity data points of macrocycles interacting with SLC-transporter. For further analysis of the SLC inhibitor profiles we developed an interactive KNIME workflow as well as an interactive map of the chemical space coverage utilizing parametric t-SNE models. The parametric t-SNE models provide a good discrimination ability among several corresponding SLC subfamilies' targets. The KNIME workflow, the dataset, and the visualization tool are freely available to the community.

Targeted sampling of natural product space to identify bioactive natural product-like polyketide macrolides

Polyketide or polyketide-like macrolides (pMLs) continue to serve as a source of inspiration for drug discovery. However, their inherent structural and stereochemical complexity challenges efforts to explore related regions of chemical space more broadly. Here, we report a strategy termed the Targeted Sampling of Natural Product space (TSNaP) that is designed to identify and assess regions of chemical space bounded by this important class of molecules. Using TSNaP, a family of tetrahydrofuran-containing pMLs are computationally assembled from pML inspired building blocks to provide a large collection of natural product-like virtual pMLs. By scoring functional group and volumetric overlap against their natural counterparts, a collection of compounds are prioritized for targeted synthesis. Using a modular and stereoselective synthetic approach, a library of polyketide-like macrolides are prepared to sample these unpopulated regions of pML chemical space. Validation of this TSNaP approach by screening this library against a panel of whole-cell biological assays, reveals hit rates exceeding those typically encountered in small molecule libraries. This study suggests that the TSNaP approach may be more broadly useful for the design of improved chemical libraries for drug discovery.

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.

Insights on Structure-Passive Permeability Relationship in Pyrrole and Furan-Containing Macrocycles

Macrocycles have recognized therapeutic potential, but their limited cellular permeability can hinder their development as oral drugs. To better understand the structure-permeability relationship of heterocycle-containing, semipeptidic macrocycles, a library was synthesized. These compounds were created by developing two novel reactions described herein: the reduction of activated oximes by LiBH4 and the aqueous reductive mono-N-alkylation of aldehydes using catalytic SmI2 and stoichiometric Zn. The permeability of the macrocycles was evaluated through a parallel artificial membrane permeability assay (PAMPA), and the results indicated that macrocycles with a furan incorporated into the structure have better passive permeability than those with a pyrrole moiety. Compounds bearing a 2,5-disubstituted pyrrole (endo orientation) were shown to be implicated in intramolecular H-bonds, enhancing their permeability. This study highlighted the impact of heterocycles moieties in semipeptides, creating highly permeable macrocycles, thus showing promising avenues for passive diffusion of drugs beyond the rule-of-five chemical space.

Leveraging nitrogen occurrence in approved drugs to identify structural patterns

BACKGROUND

The process of drug development and discovery is costly and slow. Although an understanding of molecular design principles and biochemical processes has progressed, it is essential to minimize synthesis-testing cycles. An effective approach is to analyze key heteroatoms, including oxygen and nitrogen. Herein, we present an analysis focusing on the utilization of nitrogen atoms in approved drugs.

RESEARCH DESIGN AND METHODS

The present work examines the frequency, distribution, prevalence, and diversity of nitrogen atoms in a dataset comprising 2,049 small molecules approved by different regulatory agencies (FDA and others). Various types of nitrogen atoms, such as sp3-, sp2-, sp-hybridized, planar, ring, and non-ring are included in this investigation.

RESULTS

The results unveil both previously reported and newly discovered patterns of nitrogen atom distribution around the center of mass in the majority of drug molecules.

CONCLUSIONS

This study has highlighted intriguing trends in the role of nitrogen atoms in drug design and development. The majority of drugs contain 1-3 nitrogen atoms within 5Å from the center of mass (COM) of a molecule, with a higher preference for the ring and planar nitrogen atoms. The results offer invaluable guidance for the multiparameter optimization process, thus significantly contributing toward the conversion of lead compounds into potential drug candidates.

Oral Absorption of Middle-to-Large Molecules and Its Improvement, with a Focus on New Modality Drugs

To meet unmet medical needs, middle-to-large molecules, including peptides and oligonucleotides, have emerged as new therapeutic modalities. Owing to their middle-to-large molecular sizes, middle-to-large molecules are not suitable for oral absorption, but there are high expectations around orally bioavailable macromolecular drugs, since oral administration is the most convenient dosing route. Therefore, extensive efforts have been made to create bioavailable middle-to-large molecules or develop absorption enhancement technology, from which some successes have recently been reported. For example, Rybelsus® tablets and Mycapssa® capsules, both of which contain absorption enhancers, were approved as oral medications for type 2 diabetes and acromegaly, respectively. The oral administration of Rybelsus and Mycapssa exposes their pharmacologically active peptides with molecular weights greater than 1000, namely, semaglutide and octreotide, respectively, into systemic circulation. Although these two medications represent major achievements in the development of orally absorbable peptide formulations, the oral bioavailability of peptides after taking Rybelsus and Mycapssa is still only around 1%. In this article, we review the approaches and recent advances of orally bioavailable middle-to-large molecules and discuss challenges for improving their oral absorption.

Sampling and Mapping Chemical Space with Extended Similarity Indices

Visualization of the chemical space is useful in many aspects of chemistry, including compound library design, diversity analysis, and exploring structure-property relationships, to name a few. Examples of notable research areas where the visualization of chemical space has strong applications are drug discovery and natural product research. However, the sheer volume of even comparatively small sub-sections of chemical space implies that we need to use approximations at the time of navigating through chemical space. ChemMaps is a visualization methodology that approximates the distribution of compounds in large datasets based on the selection of satellite compounds that yield a similar mapping of the whole dataset when principal component analysis on a similarity matrix is performed. Here, we show how the recently proposed extended similarity indices can help find regions that are relevant to sample satellites and reduce the amount of high-dimensional data needed to describe a library's chemical space.

Macrocyclization of linear molecules by deep learning to facilitate macrocyclic drug candidates discovery

Interest in macrocycles as potential therapeutic agents has increased rapidly. Macrocyclization of bioactive acyclic molecules provides a potential avenue to yield novel chemical scaffolds, which can contribute to the improvement of the biological activity and physicochemical properties of these molecules. In this study, we propose a computational macrocyclization method based on Transformer architecture (which we name Macformer). Leveraging deep learning, Macformer explores the vast chemical space of macrocyclic analogues of a given acyclic molecule by adding diverse linkers compatible with the acyclic molecule. Macformer can efficiently learn the implicit relationships between acyclic and macrocyclic structures represented as SMILES strings and generate plenty of macrocycles with chemical diversity and structural novelty. In data augmentation scenarios using both internal ChEMBL and external ZINC test datasets, Macformer display excellent performance and generalisability. We showcase the utility of Macformer when combined with molecular docking simulations and wet lab based experimental validation, by applying it to the prospective design of macrocyclic JAK2 inhibitors.

Lessons for Oral Bioavailability: How Conformationally Flexible Cyclic Peptides Enter and Cross Lipid Membranes

Cyclic peptides extend the druggable target space due to their size, flexibility, and hydrogen-bonding capacity. However, these properties impact also their passive membrane permeability. As the "journey" through membranes cannot be monitored experimentally, little is known about the underlying process, which hinders rational design. Here, we use molecular simulations to uncover how cyclic peptides permeate a membrane. We show that side chains can act as "molecular anchors", establishing the first contact with the membrane and enabling insertion. Once inside, the peptides are positioned between headgroups and lipid tails─a unique polar/apolar interface. Only one of two distinct orientations at this interface allows for the formation of the permeable "closed" conformation. In the closed conformation, the peptide crosses to the lower leaflet via another "anchoring" and flipping mechanism. Our findings provide atomistic insights into the permeation process of flexible cyclic peptides and reveal design considerations for each step of the process.

Expansion of the genetic code through reassignment of redundant sense codons using fully modified tRNA

Breaking codon degeneracy for the introduction of non-canonical amino acids offers many opportunities in synthetic biology. Yet, despite the existence of 64 codons, the code has only been expanded to 25 amino acids in vitro. A limiting factor could be the over-reliance on synthetic tRNAs which lack the post-transcriptional modifications that improve translational fidelity. To determine whether modified, wild-type tRNA could improve sense codon reassignment, we developed a new fluorous method for tRNA capture and applied it to the isolation of roughly half of the Escherichia coli tRNA isoacceptors. We then performed codon competition experiments between the five captured wild-type leucyl-tRNAs and their synthetic counterparts, revealing a strong preference for wild-type tRNA in an in vitro translation system. Finally, we compared the ability of wild-type and synthetic leucyl-tRNA to break the degeneracy of the leucine codon box, showing that only captured wild-type tRNAs are discriminated with enough fidelity to accurately split the leucine codon box for the encoding of three separate amino acids. Wild-type tRNAs are therefore enabling reagents for maximizing the reassignment potential of the genetic code.

Efficient Crystal Structure Prediction for Structurally Related Molecules with Accurate and Transferable Tailor-Made Force Fields

Crystal structure prediction (CSP) his generally used to complement experimental solid form screening and applied to individual molecules in drug development. The fast development of algorithms and computing resources offers the opportunity to use CSP earlier and for a broader range of applications in the drug design cycle. This study presents a novel paradigm of CSP specifically designed for structurally related molecules, referred to as Quick-CSP. The approach prioritizes more accurate physics through robust and transferable tailor-made force fields (TMFFs), such that significant efficiency gains are achieved through the reduction of expensive ab initio calculations. The accuracy of the TMFF is increased by the introduction of electrostatic multipoles, and the fragment-based force field parameterization scheme is demonstrated to be transferable for a family of chemically related molecules. The protocol is benchmarked with structurally related compounds from the Bromodomain and Extraterminal (BET) domain inhibitors series. A new convergence criterion is introduced that aims at performing only as many ab initio optimizations of crystal structures as required to locate the bottom of the crystal energy landscape within a user-defined accuracy. The overall approach provides significant cost savings ranging from three- to eight-fold less than the full-CSP workflow. The reported advancements expand the scope and utility of the underlying CSP building blocks as well as their novel reassembly to other applications earlier in the drug design cycle to guide molecule design and selection.

Mapping the binding sites of challenging drug targets

An increasing number of medically important proteins are challenging drug targets because their binding sites are too shallow or too polar, are cryptic and thus not detectable without a bound ligand or located in a protein-protein interface. While such proteins may not bind druglike small molecules with sufficiently high affinity, they are frequently druggable using novel therapeutic modalities. The need for such modalities can be determined by experimental or computational fragment based methods. Computational mapping by mixed solvent molecular dynamics simulations or the FTMap server can be used to determine binding hot spots. The strength and location of the hot spots provide very useful information for selecting potentially successful approaches to drug discovery.

Computational Site Saturation Mutagenesis of Canonical and Non-Canonical Amino Acids to Probe Protein-Peptide Interactions

Technologies for discovering peptides as potential therapeutics have rapidly advanced in recent years with significant interest from both academic and pharmaceutical labs. These advancements in turn drive the need for new computational tools to design peptides for purposes of advancing lead molecules into the clinic. Here we report the development and application of a new automated tool, AutoRotLib, for parameterizing a diverse set of non-canonical amino acids (NCAAs), N-methyl, or peptoid residues for use with the computational design program Rosetta. In addition, we developed a protocol for designing thioether-cyclized macrocycles within Rosetta, due to their common application in mRNA display using the RaPID platform. To evaluate the utility of these new computational tools, we screened a library of canonical and NCAAs on both a linear peptide and a thioether macrocycle, allowing us to quickly identify mutations that affect peptide binding and subsequently measure our results against previously published data. We anticipate in silico screening of peptides against a diverse chemical space will be a fundamental component for peptide design and optimization, as more amino acids can be explored in a single in silico screen than an in vitro screen. As such, these tools will enable maturation of peptide affinity for protein targets of interest and optimization of peptide pharmacokinetics for therapeutic applications.

Divergent, C-C Bond Forming Macrocyclizations Using Modular Sulfonylhydrazone and Derived Substrates

A divergent approach to C-C bond forming macrocycle construction is described. Modular sulfonylhydrazone and derived pyridotriazole substrates with three key building blocks have been constructed and cyclized to afford diverse macrocyclic frameworks. Broad substrate scope and functional group tolerance have been demonstrated. In addition, site-selective postfunctionalization allowed for further diversification of macrocyclic cores.

Enantioselective Construction of Modular and Asymmetric Baskets

The precise positioning of functional groups about the inner space of abiotic hosts is a challenging task and of interest for developing more effective receptors and catalysts akin to those found in nature. To address it, we herein report a synthetic methodology for preparing basket-like cavitands comprised of three different aromatics as side arms with orthogonal esters at the rim for further functionalization. First, enantioenriched A (borochloronorbornene), B (iodobromonorbornene), and C (boronorbornene) building blocks were obtained by stereoselective syntheses. Second, consecutive A-to-B and then AB-to-C Suzuki-Miyaura (SM) couplings were optimized to give enantioenriched ABC cavitand as the principal product. The robust synthetic protocol allowed us to prepare (a) an enantioenriched basket with three benzene sides and each holding either tBu, Et, or Me esters, (b) both enantiomers of a so-called "spiral staircase" basket with benzene, naphthalene, and anthracene groups surrounding the inner space, and (c) a photo-responsive basket bearing one anthracene and two benzene arms.

Improvement on Permeability of Cyclic Peptide/Peptidomimetic: Backbone N-Methylation as A Useful Tool

Peptides have a three-dimensional configuration that can adopt particular conformations for binding to proteins, which are well suited to interact with larger contact surface areas on target proteins. However, low cell permeability is a major challenge in the development of peptide-related drugs. In recent years, backbone N-methylation has been a useful tool for manipulating the permeability of cyclic peptides/peptidomimetics. Backbone N-methylation permits the adjustment of molecule’s conformational space. Several pathways are involved in the drug absorption pathway; the relative importance of each N-methylation to total permeation is likely to differ with intrinsic properties of cyclic peptide/peptidomimetic. Recent studies on the permeability of cyclic peptides/peptidomimetics using the backbone N-methylation strategy and synthetic methodologies will be presented in this review.