Discovery of selective monosaccharide receptors via dynamic combinatorial chemistry.

The molecular recognition of saccharides by synthetic hosts has become an appealing but elusive task in the last decades. Herein, we combine Dynamic Combinatorial Chemistry (DCC) for the rapid self-assembly and screening of virtual libraries of receptors, with the use of ITC and NMR to validate the hits and molecular modelling to understand the binding mechanisms. We discovered a minimalistic receptor, 1F (N-benzyl-L-phenylalanine), with considerable affinity for fructose (Ka = 1762 M-1) and remarkable selectivity (>50-fold) over other common monosaccharides. The approach accelerates the discovery process of receptors for saccharides.

Molecular Recognition of Tyrosine-Containing Polypeptides with Pseudopeptidic Cages Unraveled by Fluorescence and NMR Spectroscopies.

The molecular recognition of Tyr-containing peptide copolymers with pseudopeptidic cages has been studied using a combination of fluorescence and NMR spectroscopies. Fluorescence titrations rendered a reasonable estimation of the affinities, despite the presence of dynamic quenching masking the unambiguous detection of the supramolecular complexes. Regarding NMR, the effect of polypeptide (PP) binding on relaxation and diffusion parameters of the cages is much more reliable than the corresponding chemical shift perturbations. To that, purification of the commercial PPs is mandatory to obtain biopolymers with lower polydispersity. Thus, the relaxation/diffusion-filtered 1H spectra of the cages in the absence vs presence of the PPs represent a suitable setup for the fast detection of the noncovalent interactions. Additional key intermolecular NOE cross-peaks supported by molecular models allow the proposal of a structure of the supramolecular species, stabilized by the Tyr encapsulation within the cage cavity and additional attractive polar interactions between the side chains of cage and PP, thus defining a binding epitope with a potential for implementing sequence selectivity. Accordingly, the cages bearing positive/negative residues prefer to bind the peptides having complementary negative/positive side chains close to the target Tyr, suggesting an electrostatic contribution to the interaction. Overall, our results show that both techniques represent a powerful and complementary combination for studying cage-to-PP molecular recognition processes.

A Degenerate Metal-Templated Catalytic System with Redundant Functional Groups for the Asymmetric Aldol Reaction.

A degenerate zinc-templated catalytic system containing two bipyridine ligands with redundant functional groups for either enamine or hydrogen bond formation was applied to the asymmetric aldol reaction. This concept led to both a higher probability of reaction and rate acceleration. Thus, the catalyst loading could be decreased to a remarkable 2 mol % in what we think is a general approach.

Pseudopeptidic host adaptation in peptide recognition unveiled by ion mobility mass spectrometry.

Complexation of the glutamic-tyrosine-glutamic tripeptide (EYE) with a series of pseudopeptidic cages has been thoroughly investigated using different analytical techniques. The stoichiometry and affinities of the supramolecular host : guest complexes both in aqueous solution and in the gas-phase were obtained from a suitable combination of fluorescence spectroscopy, NMR, and mass spectrometry (MS) methods. The cages bearing basic groups (lysine, ornitine and histidine) display the tightest EYE binding in aqueous media following the order CyHis > CyLys > CyOrn, thus suggesting that Tyr side chain encapsulation is additionally modulated by the identity of the cage side chains and their ability to be engaged in polar interactions with the EYE peptide. Similarly, binding affinities estimated by MS methods clearly point towards a reduced affinity for the Cy cages with acidic pendant groups and a higher affinity of the CyHis cage over CyLys and CyOrn. Ion mobility spectrometry (IMS)-MS, assisted by molecular modelling, has been used to uncover the structural and conformational characteristics of the pseudopeptidic hosts and their supramolecular adducts with the EYE peptide. The cages display a collisional cross-section increase upon EYE inclusion that is associated with the expansion of the binding pocket of the cage cavity, thus constituting a unique example of conformational pseudopeptidic host adaptation to accommodate the inclusion of the guest.

Modulation of Src Kinase Activity by Selective Substrate Recognition with Pseudopeptidic Cages.

The selective recognition of tyrosine residues in peptides is an appealing approach to inhibiting their tyrosine kinase (TK)-mediated phosphorylation. Herein, we describe pseudopeptidic cages that efficiently protect substrates from the action of the Src TK enzyme, precluding the corresponding Tyr phosphorylation. Fluorescence emission titrations show that the most efficient cage inhibitors strongly bind the peptide substrates with a very good correlation between the binding constant and the inhibitory potency. Structural insights and additional control experiments further support the proposed mechanism of selective supramolecular protection of the substrates. Moreover, the approach also works in a completely different kinase-substrate system. These results illustrate the potential of supramolecular complexes for the efficient and selective modulation of TK signaling.

Molecular cages for biological applications.

Artificial receptors able to recognise biologically relevant molecules or ions have gained interest in the chemical community because they offer a plethora of posibilities. Molecular cage compounds are polycyclic compounds with a cavity designed for the encapsulation of guest species. Once inside the host cavity, the substrate can be transported through membranes and protected from the action of enzymes or other reactive species, thus offering the possibility of interfering with biological systems. Commonly, enzymes have been an inspiration for chemists in the search and design of defined cavities for different purposes. However, the chemical preparation of molecular cages has struggled with many synthetic challenges but this effort is worthwhile as they are a very promising tool for many applications ranging from sensing, delivery, purification or even promotion of/prevention from chemical modifications. Since the early reports at the end of the 60s, this field has experienced a growing interest; this review summarises the progress in the preparation and study of cage-like compounds highlighting their importance in biological applications.

Dynamic Stereoselection of Peptide Helicates and Their Selective Labeling of DNA Replication Foci in Cells*.

Although largely overlooked in peptide engineering, coordination chemistry offers a new set of interactions that opens unexplored design opportunities for developing complex molecular structures. In this context, we report new artificial peptide ligands that fold into chiral helicates in the presence of labile metal ions such as FeII and CoII . Heterochiral ß-turn-promoting sequences encode the stereoselective folding of the peptide ligands and define the physicochemical properties of their corresponding metal complexes. Circular dichroism and NMR spectroscopy in combination with computational methods allowed us to identify and determine the structure of two isochiral ΛΛ-helicates, folded as topological isomers. Finally, in addition to the in-vitro characterization of their selective binding to DNA three-way junctions, cell-microscopy experiments demonstrated that a rhodamine-labeled FeII helicate was internalized and selectively stains DNA replication factories in functional cells.

MCR-ALS analysis of 1H NMR spectra by segments to study the zebrafish exposure to acrylamide.

Metabolomics is currently an important field within bioanalytical science and NMR has become a key technique for drawing the full metabolic picture. However, the analysis of 1H NMR spectra of metabolomics samples is often very challenging, as resonances usually overlap in crowded regions, hindering the steps of metabolite profiling and resonance integration. In this context, a pre-processing method for the analysis of 1D 1H NMR data from metabolomics samples is proposed, consisting of the blind resolution and integration of all resonances of the spectral dataset by multivariate curve resolution-alternating least squares (MCR-ALS). The resulting concentration estimates can then be examined with traditional chemometric methods such as principal component analysis (PCA), ANOVA-simultaneous component analysis (ASCA), and partial least squares-discriminant analysis (PLS-DA). Since MCR-ALS does not require the use of spectral templates, the concentration estimates for all resonances are obtained even before being assigned. Consequently, the metabolomics study can be performed without neglecting any relevant resonance. In this work, the proposed pipeline performance was validated with 1D 1H NMR spectra from a metabolomics study of zebrafish upon acrylamide (ACR) exposure. Remarkably, this method represents a framework for the high-throughput analysis of NMR metabolomics data that opens the way for truly untargeted NMR metabolomics analyses. Graphical abstract.

Live-Cell-Templated Dynamic Combinatorial Chemistry.

Dynamic covalent chemistry combines in a single step the screening and synthesis of ligands for biomolecular recognition. In order to do that, a chemical entity is used as template within a dynamic combinatorial library of interconverting species, so that the stronger binders are amplified due to the efficient interaction with the target. Here we employed whole A549 living cells as template in a dynamic mixture of imines, for which amplification reflects the efficient and selective interaction with the corresponding extracellular matrix. The amplified polyamine showed strong interaction with the A549 extracellular matrix in on-cell NMR experiments, while combination of NMR, SPR, and molecular dynamics simulations in model systems provided insights on the molecular recognition event. Notably, our work pioneers the use of whole living cells in dynamic combinatorial chemistry, which paves the way towards the discovery of new bioactive molecules in a more biorelevant environment.

pH-Dependent Chloride Transport by Pseudopeptidic Cages for the Selective Killing of Cancer Cells in Acidic Microenvironments.

Acidic microenvironments in solid tumors are a hallmark of cancer. Inspired by that, we designed a family of pseudopeptidic cage-like anionophores displaying pH-dependent activity. When protonated, they efficiently bind chloride anions. They also transport chloride through lipid bilayers, with their anionophoric properties improving at acidic pH, suggesting an H+ /Cl- symport mechanism. NMR studies in DPC micelles demonstrate that the cages bind chloride within the lipid phase. The chloride affinity and the chloride-exchange rate with the aqueous bulk solution are improved when the pH is lowered. This increases cytotoxicity towards lung adenocarcinoma cells at the pH of the microenvironment of a solid tumor. These properties depend on the nature of the amino-acid side chains of the cages, which modulate their lipophilicity and interactions with the cell membrane. This paves the way towards using pH as a parameter to control the selectivity of cytotoxic ionophores as anticancer drugs.

Deciphering the Underlying Metabolomic and Lipidomic Patterns Linked to Thermal Acclimation in Saccharomyces cerevisiae.

Temperature is one of the most critical parameters for yeast growth, and it has deep consequences in many industrial processes where yeast is involved. Nevertheless, the metabolic changes required to accommodate yeast cells at high or low temperatures are still poorly understood. In this work, the ultimate responses of these induced transcriptomic effects have been examined using metabolomics-derived strategies. The yeast metabolome and lipidome have been characterized by 1D proton nuclear magnetic resonance spectroscopy and ultra-high-performance liquid chromatography-mass spectrometry at four temperatures, corresponding to low, optimal, high, and extreme thermal conditions. The underlying pathways that drive the acclimation response of yeast to these nonoptimal temperatures were evaluated using multivariate curve resolution-alternating least-squares. The analysis revealed three different thermal profiles (cold, optimal, and high temperature), which include changes in the lipid composition, secondary metabolic pathways, and energy metabolism, and we propose that they reflect the acclimation strategy of yeast cells to low and high temperatures. The data suggest that yeast adjusts membrane fluidity by changing the relative proportions of the different lipid families (acylglycerides, phospholipids, and ceramides, among others) rather than modifying the average length and unsaturation levels of the corresponding fatty acids.

Comparative analysis of 1H NMR and 1H-13C HSQC NMR metabolomics to understand the effects of medium composition in yeast growth.

In nuclear magnetic resonance (NMR) metabolomics, most of the studies have been focused on the analysis of one-dimensional proton (1D 1H) NMR, whereas the analysis of other nuclei, such as 13C, or other NMR experiments are still underrepresented. The preference of 1D 1H NMR metabolomics lies on the fact that it has good sensitivity and a short acquisition time, but it lacks spectral resolution because it presents a high degree of overlap. In this study, the growth metabolism of yeast ( Saccharomyces cerevisiae) was analyzed by 1D 1H NMR and by two-dimensional (2D) 1H-13C heteronuclear single quantum coherence (HSQC) NMR spectroscopy, leading to the detection of more than 50 metabolites with both analytical approaches. These two analyses allow for a better understanding of the strengths and intrinsic limitations of the two types of NMR approaches. The two data sets (1D and 2D NMR) were investigated with PCA, ASCA, and PLS DA chemometric methods, and similar results were obtained regardless of the data type used. However, data-analysis time for the 2D NMR data set was substantially reduced when compared with the data analysis of the corresponding 1H NMR data set because, for the 2D NMR data, signal overlap was not a major problem and deconvolution was not required. The comparative study described in this work can be useful for the future design of metabolomics workflows, to assist in the selection of the most convenient NMR platform and to guide the posterior data analysis of biomarker selection.

Reversible Self-Assembly of Water-Soluble Gold(I) Complexes.

The reaction of the gold polymers containing bipyridyl and terpyridyl units, [Au(C≡CC15H10N3)]n and [Au(C≡CC10H7N2)]n, with the water-soluble phosphines 1,3,5-triaza-7-phosphatricyclo[3.3.1.13.7]decane and 3,7-diacetyl-1,3,7-triaza-5-phosphabicyclo[3.3.1]nonane gives rise to the formation of four gold(I) alkynyl complexes that self-assemble in water (H2O) and dimethyl sulfoxide (DMSO), through different intermolecular interactions, with an impact on the observed luminescence displayed by the supramolecular assemblies. A detailed analysis carried out by NMR studies performed in different DMSO/deuterated H2O mixtures indicates the presence of two different assembly modes in the aggregates: (i) chain assemblies, which are based mainly on aurophilic interactions, and (ii) stacked assemblies, which are based on Au···π and π···π interactions. These different supramolecular environments can also be detected by their intrinsic optical properties (differences in absorption and emission spectra) and are predicted by the changes in the relative binding energy from density functional theory calculations carried out in DMSO and H2O. Small-angle X-ray scattering (SAXS) experiments performed in the same mixture of solvents are in agreement with the formation of aggregates in all cases. The aromatic units chosen, bipyridine and terpyridine, allow the use of external stimuli to reversibly change the aggregation state of the supramolecular assemblies. Interaction with the Zn2+ cation is observed to disassemble the aggregates, while encapsulating agents competing for Zn2+ complexation revert the process to the aggregation stage, as verified by SAXS and NMR. The adaptive nature of the supramolecular assemblies to the metal-ion content is accompanied by significant changes in the absorption and emission spectra, signaling the aggregation state and also the content on Zn2+.

A Dynamic Chemical Network for Cystinuria Diagnosis.

The study of molecular networks represents a conceptual revolution in chemistry. Building on previous knowledge and after understanding the rules of non-covalent interactions, the design of stimulus-responsive chemical systems is possible. Herein we report a new strategy, based on the reorganization of a dynamic chemical network that generates new fluorescent associations in the presence of cysteine or cystine. The binding and sensing units are encoded in the components that dynamically assemble and disassemble responding to external stimuli as a successful tool to detect both cysteine and cystine in aqueous media. Moreover, the dynamic sensing system works in human urine, as a prospective application for cystinuria diagnosis.

Dynamic Covalent Identification of an Efficient Heparin Ligand.

Despite heparin being the most widely used macromolecular drug, the design of small-molecule ligands to modulate its effects has been hampered by the structural properties of this polyanionic polysaccharide. Now a dynamic covalent selection approach is used to identify a new ligand for heparin, assembled from extremely simple building blocks. The amplified molecule strongly binds to heparin (KD in the low µm range, ITC) by a combination of electrostatic, hydrogen bonding, and CH-π interactions as shown by NMR and molecular modeling. Moreover, this ligand reverts the inhibitory effect of heparin within an enzymatic cascade reaction related to blood coagulation. This study demonstrates the power of dynamic covalent chemistry for the discovery of new modulators of biologically relevant glycosaminoglycans.

Unraveling the Multistimuli Responses of a Complex Dynamic System of Pseudopeptidic Macrocycles.

Dynamic combinatorial libraries (DCLs) are excellent benchmark models to study the stimuli-responsiveness of chemical networks. However, increasingly complex systems are difficult to analyze with simple data analysis methods, because many variables and connections must be considered for their full understanding. Here we propose the use of multivariate data analysis methods to bisect the evolution of a complex synthetic dynamic library of pseudopeptidic macrocycles, containing side chains with charges of different sign. Several stimuli (ionic strength, pH and the presence of a biogenic polyamine) were applied to the same dynamic chemical mixture, and the adaptation of the whole system was characterized by HPLC and analyzed with principal component analysis (PCA) and multivariate curve resolution-alternating least squares (MCR-ALS) methods. Both multivariate data analysis chemometric approaches are an excellent combination to extract both qualitative and semi-quantitative information about the adaptive process of the library upon the action of each stimulus. The resolution of the system with these chemometric tools proved to be especially useful when two inter-connected stimuli were combined in the same dynamic system. Our results demonstrate the utility of these two approaches for the analysis of complex dynamic chemical systems and open the way toward the application of these powerful tools in the emergent field of systems chemistry.

A copper-templated, bifunctional organocatalyst: a strongly cooperative dynamic system for the aldol reaction.

The study of novel metal-templated dynamic organocatalytic systems has led to the identification of CuSO4 as the most efficient template to assemble monofunctional prolinamide- and thiourea-modified pyridine ligands. The structural and electronic requirements to assemble an efficient catalyst have been disclosed: both pyridine ligands must bear a 1,3-substitution pattern, and the thiourea ligand serves as a reducing agent to copper(i) as well. Eventually, the cooperative effects achieved with such a simple system deliver high reaction rates and stereoselectivities at room temperature in the asymmetric aldol reaction, requiring only 1 mol% of copper salt.

Cationic Peptides and Peptidomimetics Bind Glycosaminoglycans as Potential Sema3A Pathway Inhibitors.

Semaphorin3A (Sema3A) is a vertebrate-secreted protein that was initially characterized as a repulsive-guidance cue. Semaphorins have crucial roles in several diseases; therefore, the development of Sema3A inhibitors is of therapeutic interest. Sema3A interacts with glycosaminoglycans (GAGs), presumably through its C-terminal basic region. We used different biophysical techniques (i.e., NMR, surface plasmon resonance, isothermal titration calorimetry, fluorescence, and UV-visible spectroscopy) to characterize the binding of two Sema3A C-terminus-derived basic peptides (FS2 and NFS3) to heparin and chondroitin sulfate A. We found that these peptides bind to both GAGs with affinities in the low-micromolar range. On the other hand, a peptoid named SICHI (semaphorin-induced chemorepulsion inhibitor), which is positively charged at physiological pH, was first identified by our group as being able to block Sema3A chemorepulsion and growth-cone collapse in axons at the extracellular level. To elucidate the direct target for the reported SICHI inhibitory effect in the Sema3A signaling pathway, we looked first to the protein-protein interaction between secreted Sema3A and the Nrp1 receptor. However, our results show that SICHI does not bind directly to the Sema3A sema domain or to Nrp1 extracellular domains. We evaluated a new, to our knowledge, hypothesis, according to which SICHI binds to GAGs, thereby perturbing the Sema3A-GAG interaction. By using the above-mentioned techniques, we observed that SICHI binds to GAGs and competes with Sema3A C-terminus-derived basic peptides for binding to GAGs. These data support the ability of SICHI to block the biologically relevant interaction between Sema3A and GAGs, thus revealing SICHI as a new, to our knowledge, class of inhibitors that target the GAG-protein interaction.

Pseudopeptidic compounds for the generation of dynamic combinatorial libraries of chemically diverse macrocycles in aqueous media.

A straightforward four-step synthesis leads to the preparation of C2-symmetric dithiols containing a central aromatic core and amino acid side chains. These building blocks allow the preparation of dynamic covalent libraries of pseudopeptidic macrocycles in aqueous media that cover a broad range of polarities, functional groups and bulkiness mirroring the diversity found in natural peptides. The versatility of the generated dynamic libraries has been illustrated by the amplification of two different members from the same library upon the action of two biologically relevant templates.

Anion Recognition and Induced Self-Assembly of an α,γ-Cyclic Peptide To Form Spherical Clusters.

A cyclic octapeptide composed of hydroxy-functionalized γ-amino acids folds in a "V-shaped" conformation that allows the selective recognition of anions such as chloride, nitrate, and carbonate. The process involves the simultaneous self-assembly of six peptide subunits and the recognition of four anions to form a tetrahedral structure, in which the anions are located at the corners of the resulting structure. Each anion is coordinated to three different peptides. The structure was fully characterized by several techniques, including NMR spectroscopy and X-ray diffraction, and the material was able to facilitate the transmembrane transport of chloride ions.