Spatial photoluminescence and lifetime mappings of quasi-2D perovskites coupled with a dielectric metasurface.

Light-matter interaction between quantum emitters and optical cavities plays a vital role in fundamental quantum photonics and the development of optoelectronics. Resonant metasurfaces are proven to be an efficient platform for tailoring the spontaneous emission (SE) of the emitters. In this work, we study the interplay between quasi-2D perovskites and dielectric TiO2 metasurfaces. The metasurface, functioning as an open cavity, enhances electric fields near its plane, thereby influencing the emissions of the perovskite. This is verified through angle-resolved photoluminescence (PL) studies. We also conducted reflectivity measurements and numerical simulations to validate the coupling between the quasi-2D perovskites and photonic modes. Notably, our work introduces a spatial mapping approach to study Purcell enhancement. Using fluorescence lifetime imaging microscopy (FLIM), we directly link the PL and lifetimes of the quasi-2D perovskites in spatial distribution when positioned on the metasurface. This correlation provides unprecedented insights into emitter distribution and emitter-resonator interactions. The methodology opens a new (to the best of our knowledge) approach for studies in quantum optics, optoelectronics, and medical imaging by enabling spatial mapping of both PL intensity and lifetime, differentiating between uncoupled quantum emitters and those coupled with different types of resonators.

Structure-Activity Relationship Study of the High-Affinity Neuropeptide Y4 Receptor Positive Allosteric Modulator VU0506013.

Positive allosteric modulators targeting the Y4 receptor (Y4R), a G protein-coupled receptor (GPCR) involved in the regulation of satiety, offer great potential in anti-obesity research. In this study, we selected 603 compounds by using quantitative structure-activity relationship (QSAR) models and tested them in high-throughput screening (HTS). Here, the novel positive allosteric modulator (PAM) VU0506013 was identified, which exhibits nanomolar affinity and pronounced selectivity toward the Y4R in engineered cell lines and mouse descending colon mucosa natively expressing the Y4R. Based on this lead structure, we conducted a systematic SAR study in two regions of the scaffold and presented a series of 27 analogues with modifications in the N- and C-terminal heterocycles of the molecule to obtain insight into functionally relevant positions. By mutagenesis and computational docking, we present a potential binding mode of VU0506013 in the transmembrane core of the Y4R. VU0506013 presents a promising scaffold for developing in vivo tools to move toward anti-obesity drug research focused on the Y4R.

Highly Sensitive Molecularly Imprinted Polymer-Based Electrochemical Sensors Enhanced by Gold Nanoparticles for Norfloxacin Detection in Aquaculture Water.

The overuse of antibiotics in aquaculture and pharmaceuticals and their subsequent leaking into the environment have been demonstrated to be a potential route for creating antibiotic resistance in bacteria. In order to assess the impact of this problem and take regulatory measures, it is necessary to develop tools that allow for the detection of antibiotics in environmental samples in a routine, low-cost manner. In this study, we integrated gold nanoparticles (AuNPs) into a molecularly imprinted polymer (MIP) membrane to fabricate a new sensor for the detection of norfloxacin in pharmaceuticals and aquaculture samples. The receptor layers were characterized by scanning electron microscopy, electrochemical impedance spectroscopy, and Raman spectroscopy. The results of these studies demonstrate that the addition of AuNPs to the polymer network enhanced the sensor sensitivity by at least a factor of two. The MIP-AuNPs sensor has a low detection limit (0.15 ng/mL, S/N = 3) with a wide linear range and very high sensitivity. The selectivity of the fabricated sensor was measured in the sample containing other antibiotics (like chloramphenicol, ciprofloxacin, and levofloxacin). Rapid and precise norfloxacin detection in pharmaceutical compounds and fishpond water samples indicates that the fabricated sensor has the potential to be used for routine screening of aquacultures and pharmaceutical processes.

Business-community relations under COVID-19: A study of micro and small firms.

In considering the premises of social capital and stakeholder theory, this study examines the extent to which firm-community relationships were affected during the COVID-19 crisis, and the significance of firms for their community during this unprecedented event. Responses from 107 Italian micro and small firms were gathered through an online questionnaire. The findings first reveal a strengthening of relations, particularly between firms and other businesses in their community; however, participants' comments also recognise no changes or even weakening relations. Second, three dimensions highlighting the significance of firms' survival during the crisis emerged: the community context, underlining firms' socioeconomic and symbolic contributions, the immediate stakeholders, emphasising contributions towards employment and support of local businesses, and the broader community-society context, underscoring firms' contribution towards consumer and societal needs. The study proposes a conceptual framework illustrating various relationships between the findings and the considered conceptual underpinnings and suggests various implications.

Overcoming the unprecedented: Micro, small and medium hospitality enterprises under COVID-19.

The sudden irruption of COVID-19 has paralysed, even devastated, numerous industries. Academic and industry publications also convey the destructive impacts of this phenomenon on hospitality and tourism businesses. While business owners and managers are still constrained by unpredictability, restrictions, and ongoing uncertainty, those vying to continue will need to build their adaptive skill repertoire to cope with the crisis-related regime. This study is primarily concerned with businesses' adaptation phase from owners/managers' viewpoints, including how they manage and envision a future coexistence with COVID-19 threats. Drawing on an international sample of owners/managers of hospitality and tourism businesses, and considering the foundations of the dynamic capabilities framework, eight dimensions emerged from the findings. Five of these, persevering, dynamic, austere restrictions, business environment, and stakeholder, strongly suggest the relevance of reconfiguring, a cluster of dynamic capabilities. Together, the dimensions demonstrate participants' strong commitment to navigate through the threat while pursuing socioeconomic sustainability.

Introduction to the BioChemical Library (BCL): An Application-Based Open-Source Toolkit for Integrated Cheminformatics and Machine Learning in Computer-Aided Drug Discovery.

The BioChemical Library (BCL) cheminformatics toolkit is an application-based academic open-source software package designed to integrate traditional small molecule cheminformatics tools with machine learning-based quantitative structure-activity/property relationship (QSAR/QSPR) modeling. In this pedagogical article we provide a detailed introduction to core BCL cheminformatics functionality, showing how traditional tasks (e.g., computing chemical properties, estimating druglikeness) can be readily combined with machine learning. In addition, we have included multiple examples covering areas of advanced use, such as reaction-based library design. We anticipate that this manuscript will be a valuable resource for researchers in computer-aided drug discovery looking to integrate modular cheminformatics and machine learning tools into their pipelines.

Mapping the Binding Sites of UDP and Prostaglandin E2 Glyceryl Ester in the Nucleotide Receptor P2Y6.

Cyclooxygenase-2 catalyzes the biosynthesis of prostaglandins from arachidonic acid and the biosynthesis of prostaglandin glycerol esters (PG-Gs) from 2-arachidonoylglycerol. PG-Gs are mediators of several biological actions such as macrophage activation, hyperalgesia, synaptic plasticity, and intraocular pressure. Recently, the human UDP receptor P2Y6 was identified as a target for the prostaglandin E2 glycerol ester (PGE2 -G). Here, we show that UDP and PGE2 -G are evolutionary conserved endogenous agonists at vertebrate P2Y6 orthologs. Using sequence comparison of P2Y6 orthologs, homology modeling, and ligand docking studies, we proposed several receptor positions participating in agonist binding. Site-directed mutagenesis and functional analysis of these P2Y6 mutants revealed that both UDP and PGE2 -G share in parts one ligand-binding site. Thus, the convergent signaling of these two chemically very different agonists has already been manifested in the evolutionary design of the ligand-binding pocket.

Binding of Natural Peptide Ligands to the Neuropeptide Y5 Receptor.

The binding mode of natural peptide ligands to the Y5 G protein-coupled receptor (Y5 R), an attractive therapeutic target for the treatment of obesity, is largely unknown. Here, we apply complementary biochemical and computational approaches, including scanning of the receptor surface with a genetically encoded crosslinker, Ala-scanning of the ligand and double-cycle mutagenesis, to map interactions in the ligand-receptor interface and build a structural model of the NPY-Y5 R complex guided by the experimental data. In the model, the carboxyl (C)-terminus of bound NPY is placed close to the extracellular loop (ECL) 3, whereas the characteristic α-helical segment of the ligand drapes over ECL1 and is tethered towards ECL2 by a hydrophobic cluster. We further show that the other two natural ligands of Y5 R, peptide YY (PYY) and pancreatic polypeptide (PP) dock to the receptor in a similar pose.

Structural Perspective on Ancient Neuropeptide Y-like System reveals Hallmark Features for Peptide Recognition and Receptor Activation.

The neuropeptide Y (NPY) family is a peptide-activated G protein-coupled receptor system conserved across all bilaterians, and is involved in food intake, learning, and behavior. We hypothesized that comparing the NPY system in evolutionarily ancient organisms can reveal structural determinants of peptide recognition and receptor activation conserved in evolution. To test this hypothesis, we investigated the homologous FLP/NPR system of the protostome C.elegans. For three prototypic peptide-receptor complexes representing different ligand types, we integrate extensive functional data into structural models of the receptors. Common features include acidic patches in the extracellular loops (ECLs) of the receptors that cooperatively 'draw' the peptide into the binding pocket, which was functionally validated in vivo. A structurally conserved glutamate in the ECL2 anchors the peptides by a conserved salt bridge to the arginine of the RFamide motif. Beyond this conserved interaction, peptide binding show variability enabled by receptor-specific interactions. The family-conserved residue Q3.32 is a key player for peptide binding and receptor activation. Altered interaction patterns at Q3.32 may drastically increase the efficacy to activate the receptor.

Highly Selective Y4 Receptor Antagonist Binds in an Allosteric Binding Pocket.

Human neuropeptide Y receptors (Y1R, Y2R, Y4R, and Y5R) belong to the superfamily of G protein-coupled receptors and play an important role in the regulation of food intake and energy metabolism. We identified and characterized the first selective Y4R allosteric antagonist (S)-VU0637120, an important step toward validating Y receptors as therapeutic targets for metabolic diseases. To obtain insight into the antagonistic mechanism of (S)-VU0637120, we conducted a variety of in vitro, ex vivo, and in silico studies. These studies revealed that (S)-VU0637120 selectively inhibits native Y4R function and binds in an allosteric site located below the binding pocket of the endogenous ligand pancreatic polypeptide in the core of the Y4R transmembrane domains. Taken together, our studies provide a first-of-its-kind tool for probing Y4R function and improve the general understanding of allosteric modulation, ultimately contributing to the rational development of allosteric modulators for peptide-activated G protein-coupled receptors (GPCRs).

The Structural Basis of Peptide Binding at Class A G Protein-Coupled Receptors.

G protein-coupled receptors (GPCRs) represent the largest membrane protein family and a significant target class for therapeutics. Receptors from GPCRs' largest class, class A, influence virtually every aspect of human physiology. About 45% of the members of this family endogenously bind flexible peptides or peptides segments within larger protein ligands. While many of these peptides have been structurally characterized in their solution state, the few studies of peptides in their receptor-bound state suggest that these peptides interact with a shared set of residues and undergo significant conformational changes. For the purpose of understanding binding dynamics and the development of peptidomimetic drug compounds, further studies should investigate the peptide ligands that are complexed to their cognate receptor.

BCL::Mol2D-a robust atom environment descriptor for QSAR modeling and lead optimization.

Comparing fragment based molecular fingerprints of drug-like molecules is one of the most robust and frequently used approaches in computer-assisted drug discovery. Molprint2D, a popular atom environment (AE) descriptor, yielded the best enrichment of active compounds across a diverse set of targets in a recent large-scale study. We present here BCL::Mol2D descriptors that outperformed Molprint2D on nine PubChem datasets spanning a wide range of protein classes. Because BCL::Mol2D records the number of AEs from a universal AE library, a novel aspect of BCL::Mol2D over the Molprint2D is its reversibility. This property enables decomposition of prediction from machine learning models to particular molecular substructures. Artificial neural networks with dropout, when trained on BCL::Mol2D descriptors outperform those trained on Molprint2D descriptors by up to 26% in logAUC metric. When combined with the Reduced Short Range descriptor set, our previously published set of descriptors optimized for QSARs, BCL::Mol2D yields a modest improvement. Finally, we demonstrate how the reversibility of BCL::Mol2D enables visualization of a 'pharmacophore map' that could guide lead optimization for serine/threonine kinase 33 inhibitors.

Consensus queries in ligand-based virtual screening experiments.

BACKGROUND: In ligand-based virtual screening experiments, a known active ligand is used in similarity searches to find putative active compounds for the same protein target. When there are several known active molecules, screening using all of them is more powerful than screening using a single ligand. A consensus query can be created by either screening serially with different ligands before merging the obtained similarity scores, or by combining the molecular descriptors (i.e. chemical fingerprints) of those ligands. RESULTS: We report on the discriminative power and speed of several consensus methods, on two datasets only made of experimentally verified molecules. The two datasets contain a total of 19 protein targets, 3776 known active and ~ 2 × 106 inactive molecules. Three chemical fingerprints are investigated: MACCS 166 bits, ECFP4 2048 bits and an unfolded version of MOLPRINT2D. Four different consensus policies and five consensus sizes were benchmarked. CONCLUSIONS: The best consensus method is to rank candidate molecules using the maximum score obtained by each candidate molecule versus all known actives. When the number of actives used is small, the same screening performance can be approached by a consensus fingerprint. However, if the computational exploration of the chemical space is limited by speed (i.e. throughput), a consensus fingerprint allows to outperform this consensus of scores.