Ligand-based virtual screening and in silico design of new antimalarial compounds using nonstochastic and stochastic total and atom-type quadratic maps

Malaria has been one of the most significant public health problems for centuries. It affects many tropical and subtropical regions of the world. The increasing resistance of Plasmodium spp. to existing therapies has heightened alarms about malaria in the international health community. Nowadays, there is a pressing need for identifying and developing new drug-based antimalarial therapies. In an effort to overcome this problem, the main purpose of this study is to develop simple linear discriminant-based quantitative structure-activity relationship (QSAR) models for the classification and prediction of antimalarial activity using some of the TOMOCOMD-CARDD (TOpological MOlecular COMputer Design-Computer Aided "Rational" Drug Design) fingerprints, so as to enable computational screening from virtual combinatorial datasets. In this sense, a database of 1562 organic chemicals having great structural variability, 597 of them antimalarial agents and 965 compounds having other clinical uses, was analyzed and presented as a helpful tool, not only for theoretical chemists but also for other researchers in this area. This series of compounds was processed by a k-means cluster analysis in order to design training and predicting sets. Afterward, two linear classification functions were derived in order to discriminate between antimalarial and nonantimalarial compounds. The models (including nonstochastic and stochastic indices) correctly classify more than 93% of the compound set, in both training and external prediction datasets. They showed high Matthews' correlation coefficients, 0.889 and 0.866 for the training set and 0.855 and 0.857 for the test one. The models' predictivity was also assessed and validated by the random removal of 10% of the compounds to form a new test set, for which predictions were made using the models. The overall means of the correct classification for this process (leave group 10% full-out cross validation) using the equations with nonstochastic and stochastic atom-based quadratic fingerprints were 93.93% and 92.77%, respectively. The quadratic maps-based TOMOCOMD-CARDD approach implemented in this work was successfully compared with four of the most useful models for antimalarials selection reported to date. The developed models were then used in a simulation of a virtual search for Ras FTase (FTase = farnesyltransferase) inhibitors with antimalarial activity; 70% and 100% of the 10 inhibitors used in this virtual search were correctly classified, showing the ability of the models to identify new lead antimalarials. Finally, these two QSAR models were used in the identification of previously unknown antimalarials. In this sense, three synthetic intermediaries of quinolinic compounds were evaluated as active/inactive ones using the developed models. The synthesis and biological evaluation of these chemicals against two malaria strains, using chloroquine as a reference, was performed. An accuracy of 100% with the theoretical predictions was observed. Compound 3 showed antimalarial activity, being the first report of an arylaminomethylenemalonate having such behavior. This result opens a door to a virtual study considering a higher variability of the structural core already evaluated, as well as of other chemicals not included in this study. We conclude that the approach described here seems to be a promising QSAR tool for the molecular discovery of novel classes of antimalarial drugs, which may meet the dual challenges posed by drug-resistant parasites and the rapid progression of malaria illnesses.     

Assessment of ethanol and acetonitrile in 18F-FDG preparations by means of liquid chromatography

Introduction Acetonitrile (ACN) and ethanol (EtOH) are common solvents used in radiopharmaceutical production. In accordance to official compendia, the concentration of these solvents should be assessed by gas chromatography. In the present paper, an optimized method, based on Koziorowski (2010), is validated. Methods ACN and EtOH concentrations and retention times (Rt) were obtained by a HPLC system equipped with a refractive index detector (RID), an ion exclusion column and ultrapure water as mobile phase. The methodology was validated following the ICH Q2(R1) requirements. Results The solvents EtOH and ACN were eluted at 23.22 and 26.32 minutes, respectively, with a final run time of 30 minutes. The validation parameters (accuracy, precision, linearity, specificity, robustness, detection and quantification limits) were obtained. Conclusions A reproducible HPLC method for the quantification of residual solvents in preparations of 2-deoxy-2-[fluorine-18]fluoro-D-glucose (¹⁸F-FDG) was described and validated. The method was precise, accurate, selective, robust and linear over a wide range. In addition, this method showed a high sensitivity, with limits of detection and quantitation comparable to the usual methods by gas chromatography.     

Equivalences of the large deviation principle for Gibbs measures and critical balance in the Ising model

In this paper we obtain the equivalence of the large deviation principle for Gibbs measures with and without an external field. For the Ising model, the equivalence allows us to study the result of competing influences of a positive external fieldh and a negative boundary condition in the cube ((B/h) ash0 for variousB. We find a critical balance at a valueB ₀ ofB.     

Are metal-organic frameworks able to provide a new generation of solid-phase microextraction coatings? – A review

Solid-phase microextraction (SPME) is a powerful technique commonly used in sample preparation for extraction/preconcentration of analytes from a wide variety of samples. Among the trends in improving SPME applications, current investigations are focused on the development of novel coatings able to improve the extraction efficiency, sensitivity, and thermal and mechanical stability, within other properties, of current commercial SPME fibers. Metal-organic frameworks (MOFs) merit to be highlighted as promising sorbent materials in SPME schemes. MOFs are porous hybrid materials composed by metal ions and organic linkers, presenting the highest surface areas known, with ease synthesis and high tuneability, together with adequate chemical and thermal stability. For MOF based-SPME fibers, it results important to pretreat adequately the SPME supports to ensure the correct formation of the MOF onto the fiber or the attachment MOF-support. This, in turn, will increase the final stability of the fiber while generating uniform coatings. This review provides a critical overview of the current state of the use of MOFs as SPME coatings, not only highlighting the advantages of these materials versus commercial SPME coatings in terms of stability, selectivity, and sensitivity; but also insightfully describing the current methods to obtain reproducible MOF-based SPME coatings.     

Modelling of the impedimetric responses of an aflatoxin B1 immunosensor prepared on an electrosynthetic polyaniline platform

Aflatoxins are a group of mycotoxins that have deleterious effects on humans and are produced during fungal infection of plants or plant products. An electrochemical immunosensor for the determination of aflatoxin B₁ (AFB₁) was developed with AFB₁antibody (AFB₁-Ab) immobilized on Pt electrodes modified with polyaniline (PANi) and polystyrene sulphonic acid (PSSA). Impedimetric analysis shows that the electron transfer resistances of the Pt/PANi–PSSA electrode, the Pt/PANi–PSSA/AFB₁-Ab immunosensor and Pt/PANi–PSSA/AFB₁-Ab incubated in bovine serum albumin (BSA) were 0.458, 720 and 1,066 kΩ, respectively. These results indicate that electrochemical impedance spectroscopy (EIS) is a suitable method for monitoring the change in electron transfer resistance associated with the immobilization of the antibody. Modelling of EIS data gave equivalent circuits which showed that the electron transfer resistance increased from 0.458 kΩ for the Pt/PANi–PSSA electrode to 1,066 kΩ for the Pt/PANi–PSSA/AFB₁-Ab immunosensor, indicating that immobilization of the antibody and incubation in BSA introduced an electron transfer barrier. The AFB₁ immunosensor had a detection limit of 0.1 mg/L and a sensitivity of 869.6 kΩ L/mg.     

M?ssbauer Spectroscopy: an elegant tool for the active sites identification and quantification in Pt-Sn-In based naphta reforming catalysts

The reaction of Ln(ClO₄)₃· nH₂O with triphenylphosphine oxide (TPPO) in methanol has led to the formation of [Ln(ClO₄)₂(tppo)₄]ClO₄·MeOH (Ln = Nd, Eu, Gd, Dy, Yb), in which the perchlorate anion acts as a symmetric bidentate. The emission spectra of Eu(III)-TPPO complexes, showing enhancement in the intensity due to the phenyl group, indicate an isotropic electron distribution for the nitrato complex [Eu(NO₃)₃(tppo)₂(EtOH)]. ¹⁵¹Eu and ¹⁵⁵Gd M?ssbauer spectra of the TPPO complexes also lead to the same conclusion.     

The crowded environment of a reverse micelle induces the formation of β-strand seed structures for nucleating amyloid fibril formation

A hallmark of Alzheimer's disease is the accumulation of insoluble fibrils in the brain composed of amyloid beta (Aβ) proteins with parallel in-register cross-β-sheet structure. It has been suggested that the aggregation of monomeric Aβ proteins into fibrils is promoted by "seeds" that form within compartments of the brain that have limited solvent due to macromolecular crowding. To characterize these seeds, a crowded macromolecular environment was mimicked by encapsulating Aβ40 monomers into reverse micelles. Fourier-transform infrared spectroscopy revealed that monomeric Aβ proteins form extended β-strands in reverse micelles, while an analogue with a scrambled sequence does not. This is a remarkable finding, because the formation of extended β-strands by monomeric Aβ proteins suggests a plausible mechanism whereby the formation of amyloid fibrils may be nucleated in the human brain.     

Hybrid molecular dynamics simulations of living filaments

We propose a hybrid molecular dynamics/multi-particle collision dynamics model to simulate a set of self-assembled semiflexible filaments and free monomers. Further, we introduce a Monte Carlo scheme to deal with single monomer addition (polymerization) or removal (depolymerization), satisfying the detailed balance condition within a proper statistical mechanical framework. This model of filaments, based on the wormlike chain, aims to represent equilibrium polymers with distinct reaction rates at both ends, such as self-assembled adenosine diphosphate-actin filaments in the absence of adenosine triphosphate (ATP) hydrolysis and other proteins. We report the distribution of filament lengths and the corresponding dynamical fluctuations on an equilibrium trajectory. Potential generalizations of this method to include irreversible steps like ATP-actin hydrolysis are discussed.     

Construction of Equivalent Stochastic Differential Equation Models

Abstract

It is shown how different but equivalent Itô stochastic differential equation models of random dynamical systems can be constructed. Advantages and disadvantages of the different models are described. Stochastic differential equation models are derived for problems in chemistry, textile engineering, and epidemiology. Computational comparisons are made between the different stochastic models.