Machine Learning Aids Classification and Discrimination of Noncanonical DNA Folding Motifs by an Arrayed Host:Guest Sensing System

Copper Vacancy-Doped Cu2-xSe Activating Nanozyme Sensor Arrays for Multiprotein Discrimination and Cancer Screening

Given the complexity and interrelated nature of biological activities, acquiring multitarget information is crucial for accurate cancer diagnosis. In this study, we developed a cross-reactive sensor array using peroxidase-like nonstoichiometric copper selenide nanoparticles (Cu2-xSe), which featured varying copper vacancies, for multiplex protein detection and cancer screening. The Cu2-xSe nanoparticles demonstrated outstanding peroxidase-like activity that can be modulated to varying degrees in the presence of multiple proteins with varying isoelectric points and compositions, generating fingerprint outputs. By integrating pattern recognition method principal component analysis with linear discriminant analysis (PCA-LDA), the sensor array effectively discriminated among six proteins and was further applied to cells and clinical samples, attaining 100% accuracy in differentiating cancer patients from healthy individuals, as well as in identifying specific cancer types, namely, liver and prostate cancers. Moreover, as a proof-of-concept, the partial least-squares regression (PLSR) approached the accurate detection of AFP and PSA within the range of 0.1-2.0 μg/L in the complex biological matrix. These results highlighted the practical potential of multitarget sensing and clinical diagnosis by the nanozyme-based chemical nose strategies.

Supramolecular Host:Guest Arrays Site-Selectively Recognize Peptide Phosphorylation and Kinase Activity

A synergistic combination of cationic styrylpyridinium dyes and water-soluble deep cavitand hosts can recognize phosphorylated peptides with both site- and state-selectivity. Two mechanisms of interaction are dominant: either the cationic dye interacts with Trp residues in the peptide or the host:dye pair forms a heteroternary complex with the peptide, driven by both strong dye-peptide and cavitand-peptide binding (Kd values up to 4 μM). The presence of multiple recognition mechanisms results in varying fluorescence responses dependent on the phosphorylation state and position, eliminating the need for covalent modification of the peptide target. Differential sensing aided by machine learning algorithms permits full discrimination between differently positioned serine phosphorylations with a minimal 3-component array. The array is fully functional in the presence of protein kinase A (PKA) and its required cofactors and capable of site-selective monitoring of serine phosphorylation at the privileged PKA motif, in the presence of serine residues that do not undergo reaction, illustrating the potential of the system in kinase-based drug screening.

Identification and detection of conserved G-quadruplex in monkeypox virus using conformation specific fluorogenic probe

Identifying distinct noncanonical structures in pathogenic genomes is crucial for developing new diagnostic tools. This study uncovers stable G-quadruplex (GQ) structures in conserved DNA sequences unique to the monkeypox virus (MPV). Furthermore, we developed a method for the detection of target GQ using a fluorogenic probe.

Applying Machine Learning and SERS for Precise Typing of DNA Secondary Structures

Surface-enhanced Raman spectroscopy (SERS) has been demonstrated as an effective method for elucidating secondary structural characteristics of DNA. However, the inherent complexity of the DNA conformation and the lack of SERS samples pose challenges for identifying numerous secondary structures. To address these issues, a synergistic method integrating machine learning with SERS was proposed so as to analyze the SERS spectra of 54 well-defined conformational oligonucleotides, namely, G-quadruplex (G4), i-motif (iM), double-strand (DS), and single-strand (SS) configurations. Principal component analysis (PCA) effectively segregated the oligonucleotides into three distinct conformational groups (G4s, iMs, and others). Furthermore, linear discriminant analysis (LDA), K-nearest neighbor (KNN), and support vector machine (SVM) approaches were utilized to improve the typing accuracy of 54 trained sequences. This enabled the correct classification of the structures of five untrained sequences, as well as the identification of the predominant conformations including G4, iM, and DS formed by two complementary G-rich and C-rich sequences in acidic and neutral pH conditions. The results of this study demonstrated the potential of the proposed methodology for rapid screening and prediction of secondary DNA conformations.

Mixed host co-assembled systems for broad-scope analyte sensing

Here we report a systems chemistry oriented approach for developing information-rich mixed host chemosensors. We show that co-assembling macrocyclic hosts from different classes, DimerDye sulfonatocalix[4]arenes and cucurbit[n]urils, effectively increases the scope of analyte binding interactions and therefore, sensory outputs. This simple dynamic strategy exploits cross-reactive noncovalent host-host complexation interactions while integrating a reporter dye, thereby producing emergent photophysical responses when an analyte interacts with either host. We first demonstrate the advantages of mixed host co-assembled chemosensors through an increased detection range of hydrophobic, cationic, neutral, and anionic drugs. We then implement mixed host sensors in an array-based platform for the differentiation of illicit drugs, including cannabinoids, benzodiazepine analogs, opiates, anesthetics, amphetamine, and common adulterating substances. Finally, the potential of this approach is applied to profiling real-world multi-component illicit street drug samples, proving to be more effective than classical sensor arrays.

Supramolecular 3 in 1: A Lubrication and Co-Delivery System for Synergistic Advanced Osteoarthritis Therapy

The complexity, heterogeneity, and drug resistance of diseases necessitate a shift in therapeutic paradigms from monotherapy to combination therapy, which could augment treatment efficiency. Effective treatment of advanced osteoarthritis (OA) requires addressing three key factors contributing to its deterioration: chronic joint inflammation, lubrication dysfunction, and cartilage-tissue degradation. Herein, we present a supramolecular nanomedicine of multifunctionality via molecular recognition and self-assembly. The employed macrocyclic carrier, zwitterion-modified cavitand (CV-2), not only accurately loads various drugs but also functions as a therapeutic agent with lubricating properties for the treatment of OA. Kartogenin (KGN), a drug for articular cartilage regeneration and protection, and flurbiprofen (FP), an anti-inflammatory agent, were coloaded onto CV-2 assembly, forming a supramolecular nanomedicine KGN&FP@CV-2. The three-in-one combination therapy of KGN&FP@CV-2 addresses the three pathological features for treating OA collectively, and thus provides long-term therapeutic benefits for OA through sustained drug release and intrinsic lubrication in vivo. The multifunctional integration of macrocyclic delivery and therapeutics provides a simple, flexible, and universal platform for the synergistic treatment of diseases involving multiple drugs.

"Gear-driven"-type chirality transfer of tetraphenylethene-based supramolecular organic frameworks for peptides in water

Chirality transfer for natural chiral biomolecules can reveal the indispensable role of chiral structures in life and can be used to develop the chirality-sensing biomolecular recognition. Here, we report the synthesis and characterization of a series of achiral supramolecular organic frameworks (SOF-1, SOF-2, and SOF-3), constructed from cucurbit[8]uril (CB[8]) and tetraphenylethene (TPE) derivatives (1, 2, and 3), respectively, as chirality-sensing platforms to explore their chirality transfer mechanism for peptides in water. Given the right-handed (P) and left-handed (M) rotational conformation of TPE units and the selective binding of CB[8] to aromatic amino acids, these achiral SOFs can be selectively triggered in water by peptides containing N-terminal tryptophan (W) and phenylalanine (F) residues into their P- or M-rotational conformation, exhibiting significantly different circular dichroism (CD) spectra. Although various peptides have the same l-type chiral configuration, they can induce positive CD signals of SOF-1 and negative CD signals of SOF-2 and SOF-3, respectively. Based on the structural analysis of the linkage units between CB[8] and TPE units in these SOFs, a "gear-driven"-type chirality transfer mechanism has been proposed to visually illustrate the multiple-step chirality transfer process from the recognition site in the CB[8]'s cavity to TPE units. Furthermore, by utilizing the characteristic CD signals generated through the "gear-driven"-type chirality transfer, these SOFs can serve as chiroptical sensor arrays to effectively recognize and distinguish various peptides based on their distinctive CD spectra.

Colocalization of protein and microRNA markers reveals unique extracellular vesicle subpopulations for early cancer detection

Extracellular vesicles (EVs) play important roles in cell-cell communication but are highly heterogeneous, and each vesicle has dimensions smaller than 200 nm with very limited amounts of cargos encapsulated. The technique of NanOstirBar (NOB)-EnabLed Single Particle Analysis (NOBEL-SPA) reported in the present work permits rapid inspection of single EV with high confidence by confocal fluorescence microscopy, thus enables colocalization assessment for selected protein and microRNA (miRNA) markers in the EVs produced by various cell lines, or present in clinical sera samples. EV subpopulations marked by the colocalization of unique protein and miRNA combinations were discovered to be able to detect early-stage (stage I or II) breast cancer (BC). NOBEL-SPA can be adapted to analyze other types of cargo molecules or other small submicron biological particles. Study of the sorting of specific cargos to heterogeneous vesicles under different physiological conditions can help discover distinct vesicle subpopulations valuable in clinical examination and therapeutics development and gain better understanding of their biogenesis.

Machine learning-assisted fluorescence sensor array for qualitative and quantitative analysis of pyrethroid pesticides

The simultaneous detection of multiple residues of pyrethroid pesticides (PPs) on vegetables and fruits is still challenging using traditional nanosensing methods due to the high structural similarity of PPs. In this work, sensor arrays composed of three nanocomposite complexes (rhodamine B-CD@Au, rhodamine 6G-CD@Au, and coumarin 6-CD@Au) were constructed to discriminate between structurally similar PPs. Four PPs, deltamethrin, fenvalerate, cyfluthrin, and fenpropathrin, were successfully discriminated. The ability of these sensor units was derived from the different affinity between receptor/analyte and receptor/dye, as well as the non-linear relationship between fluorescence signal and analyte concentration. Upon multivariate pattern recognition analysis, the array performed high-throughput identification of four PPs in unknown samples with 100% classification accuracy. In addition, good accuracy of predicting concentration using the "stepwise prediction" strategy combined with the machine learning method was achieved.

Selective recognition and discrimination of single isomeric changes in peptide strands with a host : guest sensing array

An indirect competitive binding mechanism can be exploited to allow a combination of cationic fluorophores and water-soluble synthetic receptors to selectively recognize and discriminate peptide strands containing a single isomeric residue in the backbone. Peptide isomerization occurs in long-lived proteins and has been linked with diseases such as Alzheimer's, cataracts and cancer, so isomers are valuable yet underexplored targets for selective recognition. Planar cationic fluorophores can selectively bind hydrophobic, Trp-containing peptide strands in solution, and when paired with receptors that provide a competitive host for the fluorophore, can form a differential sensing array that enables selective discrimination of peptide isomers. Residue variations such as D- and L-Asp, D- and L-isoAsp, D-Ser and D-Glu can all be recognized, simply by their effects on the folded structure of the flexible peptide. Molecular dynamics simulations were applied to determine the most favorable conformation of the peptide : fluorophore conjugate, indicating that favorable π-stacking with internal tryptophan residues in a folded binding pocket enables micromolar binding affinity.

Adaptive Supramolecular Networks: Emergent Sensing from Complex Systems

Molecular differentiation by supramolecular sensors is typically achieved through sensor arrays, relying on the pattern recognition responses of large panels of isolated sensing elements. Here we report a new one-pot systems chemistry approach to differential sensing in biological solutions. We constructed an adaptive network of three cross-assembling sensor elements with diverse analyte-binding and photophysical properties. This robust sensing approach exploits complex interconnected sensor-sensor and sensor-analyte equilibria, producing emergent supramolecular and photophysical responses unique to each analyte. We characterize the basic mechanisms by which an adaptive network responds to analytes. The inherently data-rich responses of an adaptive network discriminate among very closely related proteins and protein mixtures without relying on designed protein recognition elements. We show that a single adaptive sensing solution provides better analyte discrimination using fewer response observations than a sensor array built from the same components. We also show the network's ability to adapt and respond to changing biological solutions over time.

Guidelines for G-quadruplexes: I. In vitro characterization

Besides the well-known DNA double-helix, non-canonical nucleic acid structures regulate crucial biological activities. Among these oddities, guanine-rich DNA sequences can form unusual four-stranded secondary structures called G-quadruplexes (G4s). G4-prone sequences have been found in the genomes of most species, and G4s play important roles in essential processes such as transcription, replication, genome integrity and epigenetic regulation. Here, we present a short overview of G-quadruplexes followed by a detailed description of the biophysical and biochemical methods used to characterize G4s in vitro. The principles, experimental details and possible shortcomings of each method are discussed to provide a comprehensive view of the techniques used to study these structures. We aim to provide a set of guidelines for standardizing research on G-quadruplexes; these guidelines are not meant to be a dogmatic set of rules, but should rather provide useful information on the methods currently used to study these fascinating motifs.

Selective Molecular Recognition and Indicator Displacement Sensing of Neurotransmitters in Cellular Environments

Flexible, water-soluble hosts are capable of selective molecular recognition in cellular environments and can detect neurotransmitters such as choline in cells. Both cationic and anionic water-soluble self-folded deep cavitands can recognize suitable styrylpyridinium dyes in cellular interiors. The dyes selectively accumulate in nucleotide-rich regions of the cell nucleus and cytoplasm. The hosts bind the dyes and promote their relocation to the outer cell membrane: the lipophilic cavitands predominantly reside in membrane environments but are still capable of binding suitable targets in other cellular organelles. Incubating the cells with structurally similar biomarkers such as choline, cholamine, betaine, or butyrylcholine illustrates the selective recognition. Choline and butyrylcholine can be bound by the hosts, but minimal binding is seen with betaine or cholamine. Varying the dye allows control of the optical detection method, and both "turn-on" sensing and "turn-off" sensing are possible.

Colocalization of Protein and microRNA Markers Reveals Unique Extracellular Vesicle Sub-Populations for Early Cancer Detection

Extracellular vesicles (EVs) play important roles in cell-cell communication but they are highly heterogeneous, and each vesicle has dimensions smaller than 200 nm thus encapsulates very limited amounts of cargos. We report the technique of NanOstirBar (NOB)-EnabLed Single Particle Analysis (NOBEL-SPA) that utilizes NOBs, which are superparamagnetic nanorods easily handled by a magnet or a rotating magnetic field, to act as isolated "islands" for EV immobilization and cargo confinement. NOBEL-SPA permits rapid inspection of single EV with high confidence by confocal fluorescence microscopy, and can assess the colocalization of selected protein/microRNA (miRNA) pairs in the EVs produced by various cell lines or present in clinical sera samples. Specific EV sub-populations marked by the colocalization of unique protein and miRNA combinations have been revealed by the present work, which can differentiate the EVs by their cells or origin, as well as to detect early-stage breast cancer (BC). We believe NOBEL-SPA can be expanded to analyze the co-localization of other types of cargo molecules, and will be a powerful tool to study EV cargo loading and functions under different physiological conditions, and help discover distinct EV subgroups valuable in clinical examination and therapeutics development.

Iridium(III) solvent complex-based electrogenerated chemiluminescence and photoluminescence sensor array for the discrimination of bases in oligonucleotides

Development of rapid and sensitive method for the discrimination of bases in oligonucleotides is of great importance in clinical diagnosis. Here, we demonstrate the first case of single iridium(III) solvent complex-based electrogenerated chemiluminescence (ECL) and photoluminescence (PL) sensor array for the discrimination of bases in oligonucleotides. One iridium (III) solvent complex ([Ir(ppy)₂(DMSO)Cl], ppy = 2-phenylpyridine, probe 1) was designed as both ECL and PL probe while five bases (guanine, adenine, cytosine, thymine and uracil) were chosen as analytes. Two-element sensor array was built for the discrimination of five bases based on the fingerprint response of probe 1 to bases via coordination interactions. The combination of unique ECL and PL variations with principal component analysis was applied for the quantitative analysis of five bases in a linear range of 1.0 μM-10 μM and for the effective discrimination of individual base, the mixture of bases and oligonucleotides. Moreover, the sensor array was successfully applied to discriminate different mismatched ss-DNAs from HIV gene (a fully-matched ss-DNA), even at single-base difference. This work demonstrates that the sensor array using single iridium (III) solvent complex is a promising approach for the discrimination of bases with good sensitivity and simpleness in clinical diagnosis.

Recent Progress in Sensor Arrays: From Construction Principles of Sensing Elements to Applications

The traditional sensors are designed based on the "lock-and-key" strategy with high selectivity and specificity for detecting specific analytes, which however are not suitable for detecting multiple analytes simultaneously. With the help of pattern recognition technologies, the sensor arrays excel in distinguishing subtle changes caused by multitarget analytes with similar structures in a complex system. To construct a sensor array, the multiple sensing elements are undoubtedly indispensable units that will selectively interact with targets to generate the unique "fingerprints" based on the distinct responses, enabling the identification among various analytes through pattern recognition methods. This comprehensive review mainly focuses on the construction strategies and principles of sensing elements, as well as the applications of sensor array for identification and detection of target analytes in a wide range of fields. Furthermore, the present challenges and further perspectives of sensor arrays are discussed in detail.

Ligands for Abasic Site-containing DNA and their Use as Fluorescent Probes

Apurinic and apyrimidinic sites, also referred to as abasic or AP sites, are residues of duplex DNA in which one DNA base is removed from a Watson-Crick base pair. They are formed during the enzymatic repair of DNA and offer binding sites for a variety of guest molecules. Specifically, the AP site may bind an appropriate ligand as a substitute for the missing nucleic base, thus stabilizing the abasic site-containing DNA (AP-DNA). Notably, ligands that bind selectively to abasic sites may be employed for analytical and therapeutical purposes. As a result, there is a search for structural features that establish a strong and selective association of a given ligand with the abasic position in DNA. Against this background, this review provides an overview of the different classes of ligands for abasic site-containing DNA (AP-DNA). This review covers covalently binding substrates, namely amine and oxyamine derivatives, as well as ligands that bind to AP-DNA by noncovalent association, as represented by small heterocyclic aromatic compounds, metal-organic complexes, macrocyclic cyclophanes, and intercalator-nucleobase conjugates. As the systematic development of fluorescent probes for AP-DNA has been somewhat neglected so far, this review article contains a survey of the available reports on the fluorimetric response of the ligand upon binding to the AP-DNA. Based on these data, this compilation shall present a perspective for future developments of fluorescent probes for AP-DNA.

Applications of Synthetic Receptors in Bioanalysis and Drug Transport

Synthetic receptors are powerful tools for molecular recognition. They can bind to guests with high selectivity and affinity, and their structures are tunable and diversified. These features, plus the relatively low cost and high simplicity in synthesis and modification, support the feasibility of array-based molecular analysis with synthetic receptors for improved selectivity in the recognition of a wide range of targets. More attractively, host-guest interaction is reversible and guest displacement allows biocompatible and gentle release of the host-bound molecules, simplifying the stimulation designs needed to control analyte sensing, enrichment, and transportation. Here, we highlight a few recent advancements in using synthetic receptors for molecular analysis and manipulation, with the focus on macrocyclic receptors and their applications in displacement sensing, separation, imaging, and drug transport.

pH Programmed Optical Sensor Arrays for Cancer Plasma Straightforward Discrimination Based on Protein-Responsive Patterns

Optical cross-reactive sensor arrays inspired by the mammalian olfactory system that can realize straightforward discrimination of plasma from cancer patients hold great potential for point-of-care diseases diagnostics. Herein, a pH programmed fluorescence sensor array based on protein-responsive patterns was designed for straightforward discrimination of different types of cancer plasma. It is worth noting that plasma discrimination can be realized only by programming one nanomaterial using different pH values, which greatly simplifies the programmable design of the sensor array, making it an important highlight of this work. In addition, the mechanism of the pH programmed fluorescence sensor array for protein responsiveness was systematically investigated through molecular docking simulation, fluorescence resonance energy transfer (FRET), and fluorescence lifetime experiments. Most importantly, not only can the differences between plasma from healthy people and and from patients with different cancer species including gastric cancer, liver cancer, breast cancer, and cervical cancer be discriminated by this pH programmed fluorescence sensor array, but also the blind test of unknown plasma samples can be well identified with 100% accuracy, indicating its promising prospect in clinical application.

Sensing Base Modifications in Non-Canonically Folded DNA with an Optimized Host:Guest Sensing Array

An arrayed host:guest fluorescence sensor system can discriminate DNA G-quadruplex structures that differ only in the presence of single oxidation or methylation modification in the guanine base. These small modifications make subtle changes to G4 folding that are often not detectable by CD but induce differential fluorescence responses in the array. The sensing is functional in diluted serum and is capable of distinguishing individual modifications in DNA mixtures, providing a powerful method of detecting folding changes caused by DNA damage.

Feasibility and application of machine learning enabled fast screening of poly-beta-amino-esters for cartilage therapies

Despite the large prevalence of diseases affecting cartilage (e.g. knee osteoarthritis affecting 16% of population globally), no curative treatments are available because of the limited capacity of drugs to localise in such tissue caused by low vascularisation and electrostatic repulsion. While an effective delivery system is sought, the only option is using high drug doses that can lead to systemic side effects. We introduced poly-beta-amino-esters (PBAEs) to effectively deliver drugs into cartilage tissues. PBAEs are copolymer of amines and di-acrylates further end-capped with other amine; therefore encompassing a very large research space for the identification of optimal candidates. In order to accelerate the screening of all possible PBAEs, the results of a small pool of polymers (n = 90) were used to train a variety of machine learning (ML) methods using only polymers properties available in public libraries or estimated from the chemical structure. Bagged multivariate adaptive regression splines (MARS) returned the best predictive performance and was used on the remaining (n = 3915) possible PBAEs resulting in the recognition of pivotal features; a further round of screening was carried out on PBAEs (n = 150) with small variations of structure of the main candidates from the first round. The refinements of such characteristics enabled the identification of a leading candidate predicted to improve drug uptake > 20 folds over conventional clinical treatment; this uptake improvement was also experimentally confirmed. This work highlights the potential of ML to accelerate biomaterials development by efficiently extracting information from a limited experimental dataset thus allowing patients to benefit earlier from a new technology and at a lower price. Such roadmap could also be applied for other drug/materials development where optimisation would normally be approached through combinatorial chemistry.

Cucurbit[7]uril Macrocyclic Sensors for Optical Fingerprinting: Predicting Protein Structural Changes to Identifying Disease-Specific Amyloid Assemblies

In a three-dimensional (3D) representation, each protein molecule displays a specific pattern of chemical and topological features, which are altered during its misfolding and aggregation pathway. Generating a recognizable fingerprint from such features could provide an enticing approach not only to identify these biomolecules but also to gain clues regarding their folding state and the occurrence of pathologically lethal misfolded aggregates. We report here a universal strategy to generate a fluorescent fingerprint from biomolecules by employing the pan-selective molecular recognition feature of a cucurbit[7]uril (CB[7]) macrocyclic receptor. We implemented a direct sensing strategy by covalently tethering CB[7] with a library of fluorescent reporters. When CB[7] recognizes the chemical and geometrical features of a biomolecule, it brings the tethered fluorophore into the vicinity, concomitantly reporting the nature of its binding microenvironment through a change in their optical signature. The photophysical properties of the fluorophores allow a multitude of probing modes, while their structural features provide additional binding diversity, generating a distinct fluorescence fingerprint from the biomolecule. We first used this strategy to rapidly discriminate a diverse range of protein analytes. The macrocyclic sensor was then applied to probe conformational changes in the protein structure and identify the formation of oligomeric and fibrillar species from misfolded proteins. Notably, the sensor system allowed us to differentiate between different self-assembled forms of the disease-specific amyloid-β (Aβ) aggregates and segregated them from other generic amyloid structures with a 100% identification accuracy. Ultimately, this sensor system predicted clinically relevant changes by fingerprinting serum samples from a cohort of pregnant women.

A facile way to construct sensor array library via supramolecular chemistry for discriminating complex systems

Differential sensing, which discriminates analytes via pattern recognition by sensor arrays, plays an important role in our understanding of many chemical and biological systems. However, it remains challenging to develop new methods to build a sensor unit library without incurring a high workload of synthesis. Herein, we propose a supramolecular approach to construct a sensor unit library by taking full advantage of recognition and assembly. Ten sensor arrays are developed by replacing the building block combinations, adjusting the ratio between system components, and changing the environment. Using proteins as model analytes, we examine the discriminative abilities of these supramolecular sensor arrays. Then the practical applicability for discriminating complex analytes is further demonstrated using honey as an example. This sensor array construction strategy is simple, tunable, and capable of developing many sensor units with as few syntheses as possible.

Combining Excellent Selectivity with Broad Target Scope: Biosensing with Arrayed Deep Cavitand Hosts

Simple macrocyclic water-soluble hosts such as cucurbiturils, cyclophanes, and calixarenes have long been used for biosensing via indicator displacement assays. Using multiple hosts and dyes in an arrayed format allows pattern recognition-based "chemical nose" sensing, which confers exquisite selectivity, even rivaling the abilities of biological recognition tools such as antibodies. However, a challenge in indicator displacement-based biosensing with macrocyclic hosts is that selectivity and scope are often inversely correlated: strong selectivity for a specific target can limit wide application, and broad scope sensing can suffer from a lack of selectivity between similar targets. This problem can be addressed by using water-soluble, self-folding deep cavitands as hosts. These flexible bowl-shaped receptors can be easily functionalized with different motifs at the upper and lower rim, and the large cavities can bind many different fluorescent dyes, causing either fluorescence enhancement or quenching upon binding.Cavity-based affinity is strongest for NMe₃⁺ groups such as trimethyl-lysine, and we have exploited this for the site-selective recognition of post-translational lysine methylations in oligopeptides. The host recognizes the NMe₃⁺ group, and by applying differently functionalized hosts in an arrayed format, discrimination between identical modifications at different positions on the oligopeptide is possible. Multiple recognition elements can be exploited for selectivity, including a defined, yet "breathable" cavity, and variable upper rim functions oriented toward the target.While the performance of the host/guest sensing system is impressive for lysine methylations, the most important advance is the use of multiple different sensing mechanisms that can target a broad range of different biorelevant species. The amphiphilic deep cavitands can both bind fluorescent dyes and interact with charged biomolecules. These non-cavity-based interactions, when paired with additives such as heavy metal ions, modulate fluorescence response in an indirect manner, and these different mechanisms allow selective recognition of serine phosphorylation, lysine acetylation, and arginine citrullination. Other targets include heavy metals, drugs of abuse, and protein isoforms. Furthermore, the hosts can be applied in supramolecular tandem assays of enzyme function: the broad scope allows analysis of such different enzymes as chromatin writers/erasers, kinases, and phosphatases, all from a single host scaffold. Finally, the indirect sensing concept allows application in sensing different oligonucleotide secondary structures, including G-quadruplexes, hairpins, triplexes, and i-motifs. Discrimination between DNA strands with highly similar structures such as G-quadruplex strands with bulges and vacancies can be achieved. Instead of relying on a single highly specific fluorescent probe, the synthetic hosts tune the fluorophore-DNA interaction, introducing multiple recognition equilibria that modulate the fluorescence signal. By applying machine learning algorithms, a classification model can be established that can accurately predict the folding state of unknown sequences. Overall, the unique recognition profile of self-folded deep cavitands provides a powerful, yet simple sensing platform, one that can be easily tuned for a wide scope of biorelevant targets, in complex biological media, without sacrificing selectivity in the recognition.

Enantioselective sensing of insect pheromones in water

An arrayed combination of water-soluble deep cavitands and cationic dyes has been shown to optically sense insect pheromones at micromolar concentration in water. Machine learning approaches were used to optimize the most effective array components, which allows differentiation between small structural differences in targets, including between different diastereomers, even though the pheromones have no innate chromophore. When combined with chiral additives, enantiodiscrimination is possible, dependent on the size and shape of the pheromone.

Folding dynamics of polymorphic G-quadruplex structures

G-quadruplexes (G4), found in numerous places within the human genome, are involved in essential processes of cell regulation. Chromosomal DNA G4s are involved for example, in replication and transcription as first steps of gene expression. Hence, they influence a plethora of downstream processes. G4s possess an intricate structure that differs from canonical B-form DNA. Identical DNA G4 sequences can adopt multiple long-lived conformations, a phenomenon known as G4 polymorphism. A detailed understanding of the molecular mechanisms that drive G4 folding is essential to understand their ambivalent regulatory roles. Disentangling the inherent dynamic and polymorphic nature of G4 structures thus is key to unravel their biological functions and make them amenable as molecular targets in novel therapeutic approaches. We here review recent experimental approaches to monitor G4 folding and discuss structural aspects for possible folding pathways. Substantial progress in the understanding of G4 folding within the recent years now allows drawing comprehensive models of the complex folding energy landscape of G4s that we herein evaluate based on computational and experimental evidence.