PARAFAC under non-negativity constraint is adapted to recover the underlying Beer-Lambert law of the excitation-emission fluorescence matrix measurements acquired from analyte-triggered semiconductor QDs photoluminescence modulation. When and why?

BACKGROUND: Analyte-triggered semiconductor quantum dots (QDs) modulation in the presence of non-consistently responsive fluorescent species represents a challenging analytical issue in concrete multi-way data handling. QDs with heterogeneous sizes and/or uneven distribution of functional moieties on their surfaces exhibit significant fluctuations in the fluorescent response components, known as chemical rank, across different excitation/emission modes. This phenomenon may lead to a substantial deviation from the proportionality prescribed by Beer-Lambert law. Nonetheless, even in the presence of such deviation, a multi-way model may be successfully selected after determining a proper chemical rank in a QDs system. RESULTS: We show that in a valid PARAllel FACtor (PARAFAC) model under properly determined chemical rank, meaningfully resolved pure spectral profiles can be reached for each fluorescent responsive constituent in the original excitation-emission fluorescence matrix (EEFM) measurements. This was thoroughly illustrated by applying PARAFAC trilinear decomposition of a three-way data array of two distinct datasets acquired from semiconductor QDs sensing systems with low-rank trilinear assumption. The first dataset, presented here for the first time, comprises EEFM measurements of the ligand-driven quenching of thiomalic acid (TMA)-capped AgInS2 (AIS) QDs by vomitoxin. The second dataset, employed for illustrative purposes, comprises EEFM measurements of the quenching, via cation bridging, of glutathione (GSH)-capped CdTe QDs by Pb(II). The results of this study enabled the determination of vomitoxin at a ppb level in real samples of fish feeds, showcasing the efficacy of the PARAFAC model in resolving spectral signatures (loadings) and pure concentration profiles (scores). SIGNIFICANCE: PARAFAC under a properly examined chemical rank can be easily adapted for retrieval the underlying Beer-Lambert law of the original EEFM measurements with a low-rank trilinear structure through the chemically meaningful information either when (i) no deviation of Beer-Lambert law was observed as deeply discussed in connection with the dataset acquired from vomitoxin-driven molecular sensing through TMA-capped AIS QDs, or when (ii) substantial deviations of the Beer-Lambert law are evident, as discussed in connection with the dataset collected from sensing ionic species through Pb(II) bridging of GSH-capped CdTe QDs.

The Chemical Space of Marine Antibacterials: Diphenyl Ethers, Benzophenones, Xanthones, and Anthraquinones.

The emergence of multiresistant bacteria and the shortage of antibacterials in the drug pipeline creates the need to search for novel agents. Evolution drives the optimization of the structure of marine natural products to act as antibacterial agents. Polyketides are a vast and structurally diverse family of compounds that have been isolated from different marine microorganisms. Within the different polyketides, benzophenones, diphenyl ethers, anthraquinones, and xanthones have shown promising antibacterial activity. In this work, a dataset of 246 marine polyketides has been identified. In order to characterize the chemical space occupied by these marine polyketides, molecular descriptors and fingerprints were calculated. Molecular descriptors were analyzed according to the scaffold, and principal component analysis was performed to identify the relationships among the different descriptors. Generally, the identified marine polyketides are unsaturated, water-insoluble compounds. Among the different polyketides, diphenyl ethers tend to be more lipophilic and non-polar than the remaining classes. Molecular fingerprints were used to group the polyketides according to their molecular similarity into clusters. A total of 76 clusters were obtained, with a loose threshold for the Butina clustering algorithm, highlighting the large structural diversity of the marine polyketides. The large structural diversity was also evidenced by the visualization trees map assembled using the tree map (TMAP) unsupervised machine-learning method. The available antibacterial activity data were examined in terms of bacterial strains, and the activity data were used to rank the compounds according to their antibacterial potential. This potential ranking was used to identify the most promising compounds (four compounds) which can inspire the development of new structural analogs with better potency and absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties.

A tutorial on multi-way data processing of excitation-emission fluorescence matrices acquired from semiconductor quantum dots sensing platforms.

This tutorial demonstrates how to exploit the second-order advantage on excitation-emission fluorescence matrices (EEFMs) acquired from sensing platforms based on analyte-triggered semiconductor quantum dots (QDs) fluorescence modulation (quenching/enhancing). The advantage in processing such second-order EEFMs data from complex samples, seeking successful quantification, is comprehensively addressed. It is worth emphasizing that, aiming to exploit the second-order advantage, the selection of the most appropriate advanced chemometric model should rely on the matching between the data structure and the physicochemical chemometric model assumption. In this sense, the achievement of second-order advantage after EEFMs' processing is extensively addressed throughout this tutorial taking into consideration three different analytical situations, each involving a specific data structure: i) parallel factor analysis (PARAFAC), which is applied in a real dataset stacked in a three-way data array containing a trilinear data structure acquired from QDs-based detection with non-selective species; ii) multivariate curve resolution - alternating least-squares (MCR-ALS), which is also employed in a real dataset arranged in an augmented data matrix containing non-trilinear data structure acquired from QDs-based detection with a single breaking mode caused by background signals; iii) unfolded partial least-squares with residual bilinearization (U-PLS/RBL), which is applied in a dataset containing non-trilinear data acquired from a classical fluorescence system with two breaking modes caused by inner filter effect (IFE) in both instrumental modes (excitation and emission). The latter challenging data structure can be acquired via fluorescence quenching from IFE-based sensing platforms and chemometrically handled in two main steps. First, a set of calibration EEFMs data is converted into an unfolded data matrix during the unfolding process, followed by applying U-PLS model. Second, a post-calibration procedure using RBL analysis is applied to a test sample of EEFM maintained in its matrix form, in order to handle potential interferents. In the last section, the state-of-the-art of second-order EEFMs data acquired from semiconductor QDs-based sensing platforms and coupled to multi-way fluorescence data processing to accomplish a successful quantification, even with substantial interfering species, is critically reviewed.

Bioactive Marine Xanthones: A Review.

The marine environment is an important source of specialized metabolites with valuable biological activities. Xanthones are a relevant chemical class of specialized metabolites found in this environment due to their structural variety and their biological activities. In this work, a comprehensive literature review of marine xanthones reported up to now was performed. A large number of bioactive xanthone derivatives (169) were identified, and their structures, biological activities, and natural sources were described. To characterize the chemical space occupied by marine-derived xanthones, molecular descriptors were calculated. For the analysis of the molecular descriptors, the xanthone derivatives were grouped into five structural categories (simple, prenylated, O-heterocyclic, complex, and hydroxanthones) and six biological activities (antitumor, antibacterial, antidiabetic, antifungal, antiviral, and miscellaneous). Moreover, the natural product-likeness and the drug-likeness of marine xanthones were also assessed. Marine xanthone derivatives are rewarding bioactive compounds and constitute a promising starting point for the design of other novel bioactive molecules.

Determination of atenolol based on the reversion of the fluorescence resonance energy transfer between AgInS2 quantum dots and Au nanoparticles.

The present work focused on the development of a fluorescence resonance energy transfer (FRET)-based sensing platform for the monitoring of atenolol in pharmaceutical formulations. The implemented approach involved the assembly of d-penicillamine-capped AgInS2/ZnS quantum dots (QDs), as energy donors, and gold nanoparticles (AuNPs) as acceptors and the establishment of electrostatic interaction between both capping ligands at the nanoparticle surface, which induced the inhibition of the ternary QD photoluminescence (PL). The presence of a ZnS shell around the ternary QD core and the use of cysteamine (CA) as the AuNP capping ligand, instead of the typical citrate, allowed a more efficient FRET process to occur. The ability of Cd-free ternary QDs to be used as a sensing element in FRET-based assays was demonstrated, emphasizing the advantages relative to the common Cd-based QDs, when seeking the implementation of more environmentally friendly and less toxic analytical methodologies. The influence of several ß-blocker drugs on the FRET donor-acceptor assemblies was thoroughly assessed. Atenolol and nadolol caused the aggregation of CA-AuNPs via hydrogen bonding interactions which reduced the spectral overlap between the donor and acceptor, impairing the FRET process and consequently the emission of the QDs was restored. Under the optimized conditions, the obtained results exhibited a linear relationship between the QD PL recovery signal and atenolol concentration of up to 11.22 mg L-1 with a detection limit of 1.05 mg L-1. This FRET sensing platform was successfully applied in the determination of atenolol in pharmaceutical formulations with recovery values ranging from 97.4 to 104.3%.

A Pyranoxanthone as a Potent Antimitotic and Sensitizer of Cancer Cells to Low Doses of Paclitaxel.

Microtubule-targeting agents (MTAs) remain a gold standard for the treatment of several cancer types. By interfering with microtubules dynamic, MTAs induce a mitotic arrest followed by cell death. This antimitotic activity of MTAs is dependent on the spindle assembly checkpoint (SAC), which monitors the integrity of the mitotic spindle and proper chromosome attachments to microtubules in order to ensure accurate chromosome segregation and timely anaphase onset. However, the cytotoxic activity of MTAs is restrained by drug resistance and/or toxicities, and had motivated the search for new compounds and/or alternative therapeutic strategies. Here, we describe the synthesis and mechanism of action of the xanthone derivative pyranoxanthone 2 that exhibits a potent anti-growth activity against cancer cells. We found that cancer cells treated with the pyranoxanthone 2 exhibited persistent defects in chromosome congression during mitosis that were not corrected over time, which induced a prolonged SAC-dependent mitotic arrest followed by massive apoptosis. Importantly, pyranoxanthone 2 was able to potentiate apoptosis of cancer cells treated with nanomolar concentrations of paclitaxel. Our data identified the potential of the pyranoxanthone 2 as a new potent antimitotic with promising antitumor potential, either alone or in combination regimens.

Dual-emission CdTe/AgInS2 photoluminescence probe coupled to neural network data processing for the simultaneous determination of folic acid and iron (II).

This work focused on the combination of CdTe and AgInS2 quantum dots in a dual-emission nanoprobe for the simultaneous determination of folic acid and Fe(II) in pharmaceutical formulations. The surface chemistry of the used QDs was amended with suitable capping ligands to obtain appropriate reactivity in terms of selectivity and sensitivity towards the target analytes. The implementation of PL-based sensing schemes combining multiple QDs of different nature, excited at the same wavelength and emitting at different ones, allowed to obtain a specific analyte-response profile. The first-order fluorescence data obtained from the whole emission spectra of the CdTe/AgInS2 combined nanoprobe upon interaction with folic acid and Fe(II) were processed by using chemometric tools, namely partial least-squares (PLS) and artificial neural network (ANN). This enabled to circumvent the selectivity issues commonly associated with the use of QDs prone to indiscriminate interaction with multiple species, which impair reliable and accurate quantification in complex matrices samples. ANN demonstrated to be the most efficient chemometric model for the simultaneous determination of both analytes in binary mixtures and pharmaceutical formulations due to the non-linear relationship between analyte concentration and fluorescence data that it could handle. The R2P and SEP% obtained for both analytes quantification in pharmaceutical formulations through ANN modelling ranged from 0.92 to 0.99 and 5.7-9.1%, respectively. The obtained results revealed that the developed approach is able to quantify, with high reliability and accuracy, more than one analyte in complex mixtures and real samples with pharmaceutical interest.

Yicathins B and C and Analogues: Total Synthesis, Lipophilicity and Biological Activities.

Natural products have always been an important source of new hits and leads in drug discovery, with the marine environment being regarded as a significant source of novel and exquisite bioactive compounds. Yicathins B and C are two marine-derived xanthones that have shown antibacterial and antifungal activity. Herein, the total synthesis of these yicathins and six novel analogues is reported for the first time. As marine natural products tend to have very lipophilic scaffolds, the lipophilicity of yicathins and their analogues was evaluated in the classical octanol/water system and a biomimetic model-based system. As the xanthonic nucleus is a "privileged structure", other biological activities were evaluated, namely antitumor and anti-inflammatory activities. An interesting anti-inflammatory activity was identified for yicathin analogues that paves the way for the design of dual activity (anti-infective and anti-inflammatory) marine-inspired xanthone derivatives.

Chalcone derivatives targeting mitosis: synthesis, evaluation of antitumor activity and lipophilicity.

This study describes the synthesis of a series of chalcones, including pyrazole and α,ß-epoxide derivatives, and evaluation of their cell growth inhibitory activity in three human tumor cell lines, as well as their lipophilicity using liposomes as a biomimetic membrane model. Structure-activity and structure-lipophilicity relationships were established for the synthetized chalcones. From this work, nine chalcones (3, 5, 9, 11, 15-19) showing suitable drug-like lipophilicity with potent growth inhibitory activity were identified, being the growth inhibitory effect of compounds 15-17 associated with a pronounced antimitotic effect. Compounds 15-17 affected spindle assembly and, as a consequence, arrested cells at metaphase in NCI-H460 cells, culminating in cell death. Amongst the compounds tested, compound 15 exhibited the highest antimitotic activity as revealed by mitotic index calculation. Moreover, 15 was able to enhance chemosensitivity of tumor cells to low doses of paclitaxel in NCI-H460 cells. The results indicate that 15 exerts its antiproliferative activity by affecting microtubules and causing cell death subsequently to a mitotic arrest, and thus has the potential for antitumor activity.

Structures, Activities and Drug-Likeness of Anti-Infective Xanthone Derivatives Isolated from the Marine Environment: A Review.

Marine organisms represent almost half of total biodiversity and are a very important source of new bioactive substances. Within the varied biological activities found in marine products, their antimicrobial activity is one of the most relevant. Infectious diseases are responsible for high levels of morbidity and mortality and many antimicrobials lose their effectiveness with time due to the development of resistance. These facts justify the high importance of finding new, effective and safe anti-infective agents. Among the variety of biological activities of marine xanthone derivatives, one that must be highlighted is their anti-infective properties. In this work, a literature review of marine xanthones with anti-infective activity, namely antibacterial, antifungal, antiparasitic and antiviral, is presented. Their structures, biological activity, sources and the methods used for bioactivity evaluation are described. The xanthone derivatives are grouped in three sets: xanthones, hydroxanthones and glycosylated derivatives. Moreover, molecular descriptors, biophysico-chemical properties, and pharmacokinetic parameters were calculated, and the chemical space occupied by marine xanthone derivatives is recognized. The chemical space was compared with marketed drugs and framed accordingly to the drug-likeness concept in order to profile the pharmacokinetic of anti-infective marine xanthone derivatives.

Accessing lipophilicity of drugs with biomimetic models: A comparative study using liposomes and micelles.

Lipophilicity is a physicochemical property of crucial importance in drug discovery and drug design. Biomimetic models, such as liposomes and micelles, constitute a valuable tool for the assessment of lipophilicity through the determination of partition coefficients (log Kp). However, the lack of standardization hampers the judgment about which model or method has the best and broadest passive drug permeation predictive capacity. This work provides a comparative analysis between the methodologies based on biomimetic models to determine the partition coefficient (log Kp). For that purpose, a set of reference substances preconized by the Organization for Economic Cooperation and Development (OECD) guidelines was used. The biomimetic models employed were liposomes and micelles composed by 1,2-dimyristoyl-sn-glycero-3-phosphorylcholine (DMPC) and hexadecylphosphocholine (HePC), respectively. Both lipids were used as representative phospholipids of natural membranes. The partition coefficients between biomimetic models and aqueous phases were determined by derivative spectroscopy at physiological conditions (37 °C and pH 7.4). The partition coefficients obtained using biomimetic models are quite different and more reliable than the ones obtained using an octanol/water system. Comparing the performance of the two biomimetic models, micelles revealed to be suitable only for substances with high molar absorption coefficient and log Kp > 3, but in general liposomes are the best model for accessing lipophilicity of drugs. Furthermore, a comparison between experimental data and the partition coefficients determined by the computational method COSMOmic is also provided and discussed. As a final summarizing result, a decision tree is provided in order to guide the selection of a tool for assessing the lipophilicity of drugs.

Multiplexed analysis combining distinctly-sized CdTe-MPA quantum dots and chemometrics for multiple mutually interfering analyte determination.

Semiconductor quantum dots (QDs) have demonstrated a great potential as fluorescent probes for heavy metals monitoring. However, their great reactivity, whose tunability could be difficult to attain, could impair selectivity yielding analytical results with poor accuracy. In this work, the combination in the same analysis of multiple QDs, each with a particular ability to interact with the analyte, assured a multi-point detection that was not only exploited for a more precise analyte discrimination but also for the simultaneous discrimination of multiple mutually interfering species, in the same sample. Three different MPA-CdTe QDs (2.5, 3.0 and 3.8nm) with a good size distribution, confirmed by the FWHM values of 48.6, 55.4 and 80.8nm, respectively, were used. Principal component analysis (PCA) and partial least squares regression (PLS) were used for fluorescence data analysis. Mixtures of two MPA-CdTe QDs, emitting at different wavelength namely 549/566, 549/634 and 566/634nm were assayed. The 549/634nm emitting QDs mixture provided the best results for the discrimination of distinct ions on binary and ternary mixtures. The obtained RMSECV and R2CV values for the binary mixture were good, namely, from 0.01 to 0.08mgL-1 and from 0.74 to 0.89, respectively. Regarding the ternary mixture the RMSECV and R2CV values were good for Hg(II) (0.06 and 0.73mgL-1, respectively) and Pb(II) (0.08 and 0.87mg L-1, respectively) and acceptable for Cu(II) (0.02 and 0.51mgL-1, respectively). In conclusion, the obtained results showed that the developed approach is capable of resolve binary and ternary mixtures of Pb (II), Hg (II) and Cu (II), providing accurate information about lead (II) and mercury (II) concentration and signaling the occurrence of Cu (II).

Pyranoxanthones: Synthesis, growth inhibitory activity on human tumor cell lines and determination of their lipophilicity in two membrane models.

The benzopyran and dihydrobenzopyran moieties can be considered as "privileged motifs" in drug discovery being good platforms for the search of new bioactive compounds. These moieties are commonly found fused to the xanthonic scaffold belonging to the biologically important family of the generally designated prenylated xanthones. Several pyranoxanthones have shown promising antitumor activity and since most of them are from natural origin, the biosynthetic pathway only allows a particular pattern of substitution which limits their structural diversity and renders any broad structure-activity study hard to be established. Accordingly, with the aim of rationalizing the importance of the fused ring orientation and oxygenation pattern in pyranoxanthones, this study describes the synthesis of 14 new pyranoxanthones and evaluation of their cell growth inhibitory activity in four human tumor cell lines as well as their lipophilicity in two membrane models. This systematic approach allowed establishing structure-activity and structure-lipophilicity relationships for the obtained compounds in combination with 6 previously described compounds. From this work an angular pyranoxanthone scaffold emerged as particularly promising, presenting a potent cell growth inhibitory activity and suitable drug-like lipophilicity.

Biophysical characterization of the drug-membrane interactions: the case of propranolol and acebutolol.

The interaction of propranolol and acebutolol with biological membranes was assessed in the present work by using a range of biophysical techniques and liposomes, as membrane mimetic models. Liposomes were made of zwitterionic phosphatidylcholines and experiments were performed at physiologic pH and at various membrane physical states (gel, ripple and fluid phases). Fluorescence techniques were used to study the partition coefficient of ß-blockers, the influence of drugs on membrane fluidity and the drugs-membrane binding. Moreover, small and wide angle X-ray scattering techniques were used to evaluate the ß-blockers effect on long range bilayer order and hydrocarbon chain packing. The gathered results highlighted the importance of electrostatic interactions between propranolol and acebutolol with membranes. Furthermore, both ß-blockers exhibited a membrane-fluidizing effect and the capacity to disturb the membrane organization. In general, propranolol unveiled a more pronounced effect on membrane fluidity and structure than acebutolol. In the current study, the obtained results were also correlated with the cardioprotective properties of the ß-blockers studied.