Molecular Environment Research Articles

A new perspective on diagnostic strategies concerning the potential of saliva-based miRNA signatures in oral cancer.

Oral cancer, the most prevalent cancer worldwide, is far more likely to occur after the age of forty-five, according to the World Health Organization. Although many biomarkers have been discovered over the years using non-invasive saliva samples, biopsies, and human blood, these biomarkers have not been incorporated into standard clinical practice. Investigating the function of microRNAs (miRNAs) in the diagnosis, aetiology, prognosis, and treatment of oral cancer has drawn more attention in recent years. Though salivary microRNA can act as a window into the molecular environment of the tumour, there are challenges due to the heterogeneity of oral squamous cell carcinoma (OSCC), diversity in sample collection, processing techniques, and storage conditions. The up and downregulation of miRNAs has been found to have a profound role in OSCC as it regulates tumour stages by targeting many genes. As a result, the regulatory functions of miRNAs in OSCC underscore their significance in the field of cancer biology. Salivary miRNAs are useful diagnostic and prognostic indicators because their abnormal expression profiles shed light on tumour behaviour and patient prognosis. In addition to their diagnostic and prognostic value, miRNAs hold promise as therapeutic targets for oral cancer intervention. The current review sheds light on the challenges and potentials of microRNA studies that could lead to a better understanding of oral cancer prognosis, diagnosis, and therapeutic intervention. Furthermore, the clinical translation of OSCC biomarkers requires cooperation between investigators, physicians, regulatory bodies, and business partners. There is much potential for improving early identification, tracking therapy response, and forecasting outcomes in OSCC patients by including saliva-based miRNAs as biomarkers.

Side-Chain Engineering of Boron β-Dialdiminate Homopolymer for Solvent-Dependent Emission Properties.

Luminescent materials that respond to changes in microscopic chemical conditions are essential for visualizing and evaluating molecular environments. Boron complexes are often employed as robust scaffolds for constructing such responsive systems because of their inherent stimuli-responsive properties. However, in the case of nonresponsive luminophores, the absence of these intrinsic features limits their range of applications. In this study, environment-responsive luminescent homopolymers based on the boron β-dialdiminate complex are developed, which is intrinsically less responsive, by introducing optimized side chains. As a key finding, the triethylene glycol-decorated polymer exhibits more intense luminescence in chloroform but weaker luminescence in N,N-dimethylformamide. Structural analyses using NMR and size-exclusion chromatography suggest that this polymer forms larger aggregates in polar solvents because of the solvophobicity of its main chain, while the polar side chains assist in maintaining adequate dispersibility of these aggregates. Photophysical measurements indicate that interchromophore interactions within the aggregates should be responsible for the reduced luminescence in polar solvents. These findings suggest that side-chain engineering should be an effective strategy for creating stimuli-responsive polymers from otherwise nonresponsive luminophores.

Structural basis for C-degron selectivity across KLHDCX family E3 ubiquitin ligases.

Specificity of the ubiquitin-proteasome system depends on E3 ligase-substrate interactions. Many such pairings depend on E3 ligases binding to peptide-like sequences - termed N- or C-degrons - at the termini of substrates. However, our knowledge of structural features distinguishing closely related C-degron substrate-E3 pairings is limited. Here, by systematically comparing ubiquitylation activities towards a suite of common model substrates, and defining interactions by biochemistry, crystallography, and cryo-EM, we reveal principles of C-degron recognition across the KLHDCX family of Cullin-RING ligases (CRLs). First, a motif common across these E3 ligases anchors a substrate's C-terminus. However, distinct locations of this C-terminus anchor motif in different blades of the KLHDC2, KLHDC3, and KLHDC10 β-propellers establishes distinct relative positioning and molecular environments for substrate C-termini. Second, our structural data show KLHDC3 has a pre-formed pocket establishing preference for an Arg or Gln preceding a C-terminal Gly, whereas conformational malleability contributes to KLHDC10's recognition of varying features adjacent to substrate C-termini. Finally, additional non-consensus interactions, mediated by C-degron binding grooves and/or by distal propeller surfaces and substrate globular domains, can substantially impact substrate binding and ubiquitylatability. Overall, the data reveal combinatorial mechanisms determining specificity and plasticity of substrate recognition by KLDCX-family C-degron E3 ligases.

Abstract IA024: Validation of liquid biopsy approaches for the care of children with cancer

Abstract Pediatric cancers are driven by a unique set of mutations, destinct from the variants that typically drive adult cancers. Therefore, widely available liquid biopsy assays are often not relevant for detection, quantificaiton, or profiling of circulating tumor DNA in childhood cancer. Custom liquid biopsy approaches have been developed by the Crompton lab and others and these assays demonstrate that ctDNA levels provide valuable prognostic information and can guide some therapeutic choices in pediatrics. Implementation of liquid biopsies into national phase 3 trials for children with cancer will require translation of these approaches into a clinical molecular laboratory environment. Citation Format: Brian Crompton. Validation of liquid biopsy approaches for the care of children with cancer [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr IA024.

Proximity Effects and Aggregation of Hamilton-Receptor Barbiturate Host-Guest Complexes Probed by Cross-Metathesis and ESI MS Analysis.

The molecular environment around supramolecular bonding systems significantly affects their stability and the assembly of host-guest complexes, most prominent for hydrogen bonds (H-bonds). Hamilton receptor-barbiturate host-guest complexes are well-known in solution, typically forming a 1:1 molar ratio complex. However, within a polymer matrix, these complexes can form higher-order assemblies, deviating from the standard 1:1 complex, which are challenging to characterize and often require lab-intensive methods. In this study, a novel Hamilton receptor (H) was equipped with cyclopentene moieties and used as a host to form host-guest complexes (H-B) with allobarbital (B), followed by covalent crosslinking. UV-Vis spectroscopy titration experiments in different solvents and at various temperatures revealed that polar solvents containing additional H-bonding sites significantly reduce the formation of the 1:1 H-B complex, as indicated by a reduced association constant. Higher-order aggregates (HH-dimer, HHH-trimer) were subsequently detected via an alkene cross-metathesis (CM) reaction to fix the assemblies covalently, followed by analysis via electrospray ionization mass spectrometry (ESI MS). This two-step method, firstly via CM fixation followed by ESI MS, was extended to study the H-B model complex within a polyisobutylene (PIB) matrix, presenting a direct method to analyze the complex host-guest assembly in solvent-free (polymer) environments.

UCBShift 2.0: Bridging the Gap from Backbone to Side Chain Protein Chemical Shift Prediction for Protein Structures.

Chemical shifts are a readily obtainable NMR observable that can be measured with high accuracy, and because they are sensitive to conformational averages and the local molecular environment, they yield detailed information about protein structure in solution. To predict chemical shifts of protein structures, we introduced the UCBShift method that uniquely fuses a transfer prediction module, which employs sequence and structure alignments to select reference chemical shifts from an experimental database, with a machine learning model that uses carefully curated and physics-inspired features derived from X-ray crystal structures to predict backbone chemical shifts for proteins. In this work, we extend the UCBShift 1.0 method to side chain chemical shift prediction to perform whole protein analysis, which, when validated against well-defined test data shows higher accuracy and better reliability compared to the popular SHIFTX2 method. With the greater abundance of cleaned protein shift-structure data and the modularity of the general UCBShift algorithms, users can gain insight into different features important for residue-specific stabilizing interactions for protein backbone and side chain chemical shift prediction. We suggest several backward and forward applications of UCBShift 2.0 that can help validate AlphaFold structures and probe protein dynamics.

Kinetic Basis for the Design of Azobenzene-Based Photoswitchable A2a Adenosine Receptor Ligands.

Photoisomerization of ligands is a key process in the field of photopharmacology. Thus, the kinetics and efficiency of this initial photoreaction are of great importance but can be influenced by the molecular environment of the binding pocket and the resulting confinement of the reaction pathway. In this study, we investigated the photoisomerization of an azobenzene derivative of the anti-Parkinson's drug istradefylline. To identify the impact of the binding pocket, the ligand was examined in solution and bound to its target protein, the A2a adenosine receptor (A2aR), belonging to the family of G protein-coupled receptors (GPCRs). Although the overall efficiency of isomerization is reduced when the ligand is bound, the initial photoreaction experiences little influence from the binding pocket. However, protein-coupled motion promotes a longer-lived excited-state population and thus leads to a reduction in efficiency. The results provide the kinetic basis for a photoswitchable GPCR ligand and demonstrate the influence of the binding pocket on fundamental photochemistry.

Molecular Docking Assessment of Limonoids from Cameroonian Entandrophragma Species as Potential Inhibitors of Anopheles gambiae Acetylcholinesterase (AChE)

Malaria remains one of the great killers in tropical regions of the world due to the transmission of the Plasmodium parasite by the bites of the female mosquito Anopheles. The resistance of this species to synthetic insecticides contributes to an increase in the incidence of malaria and therefore necessitates the development of new potent and eco-friendly insecticides. In this study, twelve previously reported limonoids from four Entandrophragma species collected in Cameroon have been computationally evaluated for their Anopheles gambiae AChE inhibitory activity. The docking procedure was carried out through Molecular Operating Environment 2019.01 (MOE), while the UCSF Chimera program was used to model the docking results based on interactions between proteins and ligands, and molecular dynamics trajectories were analyzed using the GROMACS 2021.1 tool. Entandrophragmin and encandollens B and C with docking scores ranging from −6.45 to −7.28 kcal/mol were the most promising hits compared to the reference azadirachtin (−6.22 kcal/mol) and were further evaluated for their mechanism of action. Subsequent evaluation classified encandollen C as the best candidate for the development of new potent eco-friendly insecticides based on its lower average RMSD and RMSF and its compactness over a 150 ns duration with acetylcholinesterase.

Absorption line broadening in atomic beams produced in a molecular beam epitaxy environment

Tunable diode laser absorption spectroscopy (TDLAS) is used to measure the 6s2 1S-5d6p 3D0 absorption line profile of a Ba atomic beam produced in a molecular beam epitaxy (MBE) reactor. Despite the noisy MBE environment, a signal-to-noise ratio up to 100 is obtained thanks to a thorough optimization of the measurement setup. A model that realistically describes this absorption profile is presented, taking into account the angular distribution of atomic concentration in the atomic beam as well as the reactor and setup geometry. Our results highlight the influence of the latter on the Doppler line broadening, and allows to estimate the angular distribution of concentration in the beam emitted by the effusion cell. The model can be adapted to estimate the absorption profile for any element in any reactor geometry, making it a useful tool to design MBE dedicated atomic absorption sensors such as optical flux monitoring sensors, or to characterize the beam emitted by any effusion cell.

Phase-Sensitive Fluorescence Image Correlation Spectroscopy.

Fluorescence lifetime imaging microscopy is sensitive to molecular interactions and environments. In homo-dyne frequency-domain fluorescence lifetime imaging microscopy, images of fluorescence objects are acquired at different phase settings of the detector. The detected intensity as a function of detector phase is a sinusoidal function that is sensitive to the lifetime of the fluorescent species. In this paper, the theory of phase-sensitive fluorescence image correlation spectroscopy is described. In this version of lifetime imaging, image correlation spectroscopy analysis (i.e., spatial autocorrelation) is applied to successive fluorescence images acquired at different phase settings of the detector. Simulations of different types of lifetime distributions reveal that the phase-dependent density of fluorescent objects is dependent on the heterogeneity of lifetimes present in the objects. We provide an example of this analysis workflow to a cervical cancer cell stained with a fluorescent membrane probe.

Electroinduced Reductive and Dearomative Alkene-Aldehyde Coupling.

The direct coupling of alkene feedstocks with aldehydes represents an expedient approach to the generation of new and structurally diverse C(sp3)-hybridized alcohols that are primed for elaboration into privileged architectures. Despite their abundance, current disconnection strategies enabling the direct coupling of carbon-carbon π-bonds and aldehydes remain challenging because contemporary methods are often limited by substrate or functional group tolerance and compatibility in complex molecular environments. Here, we report a coupling between simple alkenes, heteroarenes and unactivated aliphatic aldehydes via an electrochemically induced reductive activation of C-C π-bonds. The cornerstone of this approach is the discovery of rapid alternating polarity (rAP) electrolysis to access and direct highly reactive radical anion intermediates derived from conjugated alkenes and heterocyclic compounds. Our developed catalyst-free protocol enables direct access to new and structurally diverse C(sp3)-hybridized alcohol products. This is achieved by the controlled reduction of conjugated alkenes and the C2-C3 π-bond in heteroarenes via an unprecedented reductive dearomative functionalization for heterocyclic compounds. Experimental mechanistic studies demonstrate a kinetically biased single-electron reduction of C-C π-bonds over aldehydes. Application of rAP enables chemoselective generation of olefinic radical anion intermediates and avoids undesired saturative overreduction. Overall, this technology provides a versatile approach to the reductive coupling of olefin and heterocycle feedstocks with aliphatic aldehydes, offering straightforward access to diverse C(sp3)-rich oxygenated scaffolds.

Ultrafast T1-T1ρ NMR for Correlating Different Motional Regimes of Molecules.

Nuclear magnetic resonance (NMR) relaxation times provide detailed information about molecular motions and local chemical environments. Longitudinal T1 relaxation time is most often sensitive to relatively fast, nano- to picosecond ranges of molecular motion. Rotating frame T1ρ relaxation time reflects a much slower, micro- to millisecond range of motion, and the motional regime can be tuned by changing spin-lock field strength. Conventional methods for measuring T1 and T1ρ relaxation times are time-consuming, since experiments must be repeated many times with incremented magnetization recovery or decay delay. In this work, we introduce two novel and efficient NMR methods to correlate the T1 and T1ρ relaxation times. The first method, IR-SPICY, combines the conventional T1 inversion recovery (IR) with the single-scan T1ρ detection-based spin-lock cycle (SPICY). The second method, ultrafast (UF) IR-SPICY, allows measurement of whole two-dimensional T1-T1ρ correlation data in a single scan, in a couple of seconds, based on spatial encoding of the T1 dimension. We demonstrate the performance of the methods by studying relaxation of water in porous silica and hydrogel samples, latter acting as a model of the articular cartilage extracellular matrix. The methods allow correlating different molecular motional regimes, potentially providing unprecedented information about various chemical and biochemical systems, such as structures and fluid dynamics in porous materials, macromolecular changes in tissues, and protein dynamics. One to three orders of magnitude shortened experiment time enable the studies of changing or degrading samples. Furthermore, the single-scan approach may significantly facilitate the use of modern nuclear-spin hyperpolarization techniques to enhance the sensitivity of T1-T1ρ measurements by several orders of magnitude.

Switchable protection and exposure of a sensitive squaraine dye within a redox active rotaxane

In nature, molecular environments in proteins can sterically protect and stabilize reactive species such as organic radicals through non-covalent interactions. Here, we report a near-infrared fluorescent rotaxane in which the stabilization of a chemically labile squaraine fluorophore by the coordination of a tetralactam macrocycle can be controlled chemically and electrochemically. The rotaxane can be switched between two co-conformations in which the wheel either stabilizes or exposes the fluorophore. Coordination by the wheel affects the squaraine’s stability across four redox states and renders the radical anion significantly more stable—by a factor of 6.7—than without protection by a mechanically bonded wheel. Furthermore, the fluorescence properties can be tuned by the redox reactions in a stepwise manner. Mechanically interlocked molecules provide an excellent scaffold to stabilize and selectively expose reactive species in a co-conformational switching process controlled by external stimuli.

Studi Molecular Docking dan Evaluasi Farmakokinetik Senyawa Analog Pirazol Turunan Benzen-Sulfonilurea sebagai Inhibitor Enzim Aldose Reduktase and α-Glukosidase Menggunakan Pendekatan In Silico

The pyrazole scaffold modification in various chemical structures on several studies has shown various biopharmacological activities. This study aims to predict the potential inhibition of pyrazole analogs derived benzene-sulfonylurea (4A, 4B, 4E, 5A, 5C, 5D) against the α-glucosidase (3A4A) and aldose reductase (3RX2) enzymes based on a molecular docking approach using Molecular Operating Environment (MOE) 2020.0102 software and evaluate pharmacokinetic profile (ADMET). In this study, the six test compounds were obtained from previous studies that have been proven antihyperglycemic. The results showed that all the 3,5-disubstituted benzene-sulfonylurea derivative pyrazole analogs are predicted to have low inhibitory activity against the α-glucosidase enzyme. Further, all compounds showed good aldose reductase inhibitor activity and had lower binding free energy values ​​than tolrestat as the positive control (-6.82 kcal/mol). Compound 5C has the best potential inhibitory activity against the aldose reductase enzyme compared to the other test compounds, because it has the lowest binding free energy value (-8.76 kcal/mol) and interacts with important residues on the receptor forming four hydrogen bonds, namely the carbonyl group of SO2 with residues Trp111 and His110, and the carbonyl group of the amide with residues His110 and Tyr48, as well as 3 hydrophobic bonds, namely a pyrazole ring with residues Leu300, Trp219 and a furan ring with Phe122. ADMET properties of the compounds are also predicted. This information provides an opportunity for a 5C compound as an aldose reductase inhibitor agent to develop drug candidates with better and safer activities.

In-silico Molecular Docking of Two Bioactive Constituents (Quercetin 3-Glucuronide and Quercitrin) from Polygonum minus Leaves into Monoamine Oxidase-A Crystal Structure

The aim of the current research was to dock the two abundant bioactive constituents of Polygonum minus leaf extract, in1cluding Quercetin 3-Glucuronide (Miquelianin) and Quercitrin (Quercetin-3-rhamnoside). In-silico Molecular modelling technique was used to predict about a protein (enzyme) interacts with molecules (ligands). Monoamine oxidase-A (MAO-A) is the key enzyme that is involved in the breakdown of neurotransmitters like serotonin and noradrenaline. Drugs that are involved in its inhibition, are considered to be antidepressant agents. This molecular docking study observed the binding energy of selected ligands and their interactions with amino acid residue along with bond types in the MAO-A structure. Molecular docking was done using Molecular Operating Environment (MOE) software, whereas visualization and expression of results were carried out using Discovery Studio (DS) visualizer. Clorgyline was used in this study as a co-crystal ligand, whereas moclobemide was used as a standard MAO-A inhibitor, and Amitriptyline was used as a common antidepressant which also has some MAO-A inhibitory effect. Quercetin 3-glucuronide (Miquelianin) and Quercitrin (Quercetin-3-rhamnoside) have more binding affinities with MAO-A structure as compared to all other drugs. Its interaction pattern was most likely moclobemide and Clorgyline, which are considered standard MAO-A inhibitors in this study. Based on these results, it is concluded that Quercetin 3-Glucuronide (Miquelianin) and Quercitrin (Quercetin-3-rhamnoside) have the potential to become potent MAO-A inhibitors in future.

Insights into the enhanced adsorption of glyphosate by dissolved organic matter in farmland Mollisol: effects and mechanisms of action.

Dissolved organic matter (DOM) is easy to combine with residual pesticides and affect their morphology and environmental behavior. Given that the binding mechanism between DOM and the typical herbicide glyphosate in soil is not yet clear, this study used adsorption experiments, multispectral techniques, density functional theory, and pot experiments to reveal the interaction mechanism between DOM and glyphosate on Mollisol in farmland and their impact on the environment. The results show that the adsorption of glyphosate by Mollisol is a multilayer heterogeneous chemical adsorption process. After adding DOM, due to the early formation of DOM and glyphosate complex, the adsorption process gradually became dominated by single-layer chemical adsorption, and the adsorption capacity increased by 1.06 times. Glyphosate can quench the endogenous fluorescence of humic substances through a static quenching process dominated by hydrogen bonds and van der Waals forces, and instead enhance the fluorescence intensity of protein substances by affecting the molecular environment of protein molecules. The binding of glyphosate to protein is earlier, of which affinity stronger than that of humic acid. In this process, two main functional groups (C-O in aromatic groups and C-O in alcohols, ethers and esters) exist at the binding sites of glyphosate and DOM. Moreover, the complexation of DOM and glyphosate can effectively alleviate the negative impact of glyphosate on the soil. This study has certain theoretical guidance significance for understanding the environmental behavior of glyphosate and improving the sustainable utilization of Mollisol.

A Novel Technique for Fluorescence Lifetime Tomography.

Fluorescence lifetime has emerged as a unique imaging modality for quantitatively assessing in vivo the molecular environment of diseased tissues. Although fluorescence lifetime microscopy (in 2D) is a mature field, 3D imaging in deep tissues remains elusive and challenging owing to scattering. Herein, we report on a deep neural network (coined AUTO-FLI) that performs both 3D intensity and quantitative lifetime reconstructions in deep tissues. The proposed Deep Learning (DL)-based approach involves an in silico scheme to generate fluorescence lifetime data accurately. The developed DL model is validated both in silico and on experimental phantoms. Overall, AUTO-FLI provides accurate 3D quantitative estimates of both intensity and lifetime distributions in highly scattering media, demonstrating its unique potential for fluorescence lifetime-based molecular imaging at the mesoscopic and macroscopic scale.

Disulfide Bond Engineering of Soluble ACE2 for Thermal Stability Enhancement.

Although the primary pandemic of SARS-CoV-2 is over, there are concerns about the resurgence of the next wave of related viruses, including a wide range of variant viruses. The soluble ACE2 (sACE2) inhibits the SARS-CoV-2 spike protein ACE2 interaction and has potential as a variant-independent therapeutic against SARS-CoV-2. Here, we introduce novel disulfide bonds in the wild-type sACE2-Fc by structure-guided mutagenesis, aiming to improve its stability. The stability of each mutant was assessed by a thermal shift assay to screen mutants with increased thermal stability. As a result, we identified a mutant sACE2-Fc with a significantly increased melting temperature. X-ray crystal structure determination of the sACE2 mutant confirmed the correct formation of the designed disulfide bond, and there were no significant structural disturbances. We also proved that the thermostable sACE2-Fc preserved the spike protein binding affinity comparable to the wild-type sACE2-Fc in both molecular and cellular environments, suggesting its therapeutic potential.

Prediction of Listeria monocytogenes Clonal Complexes from Multilocus Variable Number Tandem Repeat Analysis Patterns Using a Machine Learning Approach.

Multilocus variable number tandem repeat analysis (MLVA) is a molecular subtyping technique that remains useful for those without the resources to access whole genome sequencing for the tracking and tracing of bacterial contaminants. Unlike techniques such as multilocus sequence typing (MLST) and pulsed-field gel electrophoresis, MLVA did not emerge as a standardized subtyping method for Listeria monocytogenes, and as a result, there is no reference database of virulent or food-associated MLVA subtypes as there is for MLST-based clonal complexes (CCs). Having previously shown the close congruence of a 5-loci MLVA scheme with MLST, a predictive model was created using the XGBoost machine learning (ML) technique, which enabled the prediction of CCs from MLVA patterns with ∼85% (±4%) accuracy. As well as validating the model on existing data, a straightforward update protocol was simulated for if and when previously unseen subtypes might arise. This article illustrates how ML techniques can be applied with elementary coding skills to add value to previous-generation molecular subtyping data in-built food processing environments.

Magnetohydrodynamical modeling of star-disk formation: from isolated spherical collapse towards incorporation of external dynamics

The formation of protostars and their disks has been understood as the result of the gravitational collapse phase of an accumulation of dense gas that determines the mass reservoir of the star-disk system. Against this background, the broadly applied scenario of considering the formation of disks has been to model the collapse of a dense core assuming spherical symmetry. Our understanding of the formation of star-disk systems is currently undergoing a reformation though. The picture evolves from interpreting disks as the sole outcome of the collapse of an isolated prestellar core to a more dynamic picture where disks are affected by the molecular cloud environment in which they form. In this review, we provide a status report of the state-of-the-art of spherical collapse models that are highly advanced in terms of the incorporated physics together with constraints from models that account for the possibility of infall onto star-disk systems in simplified test setups, as well as in multi-scale simulations that cover a dynamical range from the Giant Molecular Cloud environment down to the disk. Considering the observational constraints that favor a more dynamical picture of star formation, we finally discuss the challenges and prospects in linking the efforts of tackle the problem of star-disk formation in combined multi-scale, multi-physics simulations.