Biological activity of synthesized 5-{1-[(4-chlorophenyl)sulfonyl]piperidin-4-yl}-2-mercapto-1, 3, 4-oxadiazole derivatives demonstrated by in silico and BSA binding studies

We synthesized a series of compounds bearing pharmacologically important 1,3,4-oxadiazole and piperidine moieties. Spectral data analysis by 1H-NMR, 13C-NMR, IR and EI-MS was used to elucidate the structures of the synthesized molecules. Docking studies explained the different types of interaction of the compounds with amino acids, while bovine serum albumin (BSA) binding interactions showed their pharmacological effectiveness. Antibacterial screening of these compounds demonstrated moderate to strong activity against Salmonella typhi and Bacillus subtilis but only weak to moderate activity against the other three bacterial strains tested. Seven compounds were the most active members as acetyl cholinesterase inhibitors. All the compounds presented displayed strong inhibitory activity against urease. Compounds 7l, 7m, 7n, 7o, 7p, 7r, 7u, 7v, 7x and 7v were highly active, with respective IC50 values of 2.14±0.003, 0.63±0.001, 2.17±0.006, 1.13±0.003, 1.21±0.005, 6.28±0.003, 2.39±0.005, 2.15±0.002, 2.26±0.003 and 2.14±0.002 µM, compared to thiourea, used as the reference standard (IC50 = 21.25±0.15 µM). These new urease inhibitors could replace existing drugs after their evaluation in comprehensive in vivo studies.

Combinação dose fixa de hidroclorotiazida (12, 5 mg) e valsartana (160 mg): Desenvolvimento de metodologia de dissolução in vitro e in silico para avaliar os perfis de dissolução dos produtos comercializados no Brasil e Peru / Fixed dose combination of hydrochlorothiazide (12. 5 mg) and valsartan (160 mg): Development of in vitro and in silico dissolution methodology to evaluate the dissolution profiles of products marketed in Brazil and Peru

Hidroclorothiazida (HTZ) e valsartana (VAL) são fármacos pouco solúveis em meio aquoso e pertencem às classes IV e II do Sistema de Classificação Biofarmacêutica (SCB), respectivamente. O objetivo deste trabalho foi desenvolver um método para avaliar o perfil de dissolução de formas farmacêuticas sólidas de dose fixa combinada contendo HTZ (12,5 mg) e VAL (160 mg) usando ferramentas in silico para avaliar os perfis de dissolução de produtos comercializados no Brasil e Peru. O presente trabalho foi dividido em 4 capítulos. No Capítulo I, foi determinada a solubilidade da HTZ e VAL pelo método shake-flask e potenciométrico, no qual foi possível demonstrar que existe correlação entre ambos os métodos e que HTZ e VAL são solúveis em tampão fosfato pH 6,8. No Capítulo II, um método cromatográfico em HPLC foi desenvolvido com base em Quality by Design (QbD), com auxílio do software Fusion®, no qual foi estabelecido uma zona de confiança dos parâmetros, que garantiu a robustez do método. O Capítulo III descreve o desenvolvimento de um método de dissolução utilizando ferramenta in silico (DDDplus®) na qual foi definido um delineamento experimental do tipo fatorial completo 33 usando como fatores a formulação, utilização de âncora e velocidade de agitação. Para os ensaios de dissolução in vitro, foi proposto um outro delineamento fatorial 3(3-1) com o intuito de obter as constantes de calibração das simulações in silico. Através de uma análise estatística das eficiências de dissolução obtidas nas simulações, foram avaliados os efeitos e as interações entre os fatores. Assim, as condições finais do método de dissolução estabelecidas foram: 900 mL de tampão fosfato pH 6,8 como meio de dissolução, 75 rpm de velocidade de agitação, e utilização de âncora para evitar a flutuação das formulações. O método desenvolvido foi empregado, no contexto do Capítulo IV, para avaliar o perfil de dissolução dos produtos contendo HTZ e VAL comercializados no Brasil e no Peru. Por análise multivariada, a eficiência de dissolução (ED), tempo médio de dissolução (MDT) e as porcentagens de dissolução de 5 até 60 minutos foram utilizadas para agrupar as formulações em grupos distintos. Embora os perfis de dissolução mostrem similaridade entre todas as formulações avaliadas, o produto referência se destacou por apresentar uma maior ED comparado com as outras formulações, devido à maior liberação nos primeiros 5 minutos de ensaio. Concluiu-se que o método proposto, além de garantir a liberação total de HTZ e VAL a partir das formulações, possui adequado poder discriminativo

Hydrochlorothiazide (HTZ) and valsartan (VAL) are poorly soluble drugs in aqueous medium and belong to classes IV and II of the Biopharmaceutical Classification System (BCS), respectively. The objective of this study was to develop a dissolution method to evaluate the dissolution profile of solid pharmaceutical forms of combined dose containing HTZ (12.5 mg) and VAL (160 mg) using in silico tools to evaluate the dissolution profiles of products sold in Brazil and Peru. The present study was divided into four chapters. In Chapter I, the HTZ and VAL solubility were determined by the shake-flask and potentiometric methods, in which it was possible to demonstrate that there is a correlation between both methods and that HTZ and VAL are soluble in pH 6.8 phosphate buffer. In Chapter II, a chromatographic method in HPLC was developed based on Quality by Design (QbD), using the Fusion® software, in which a zone of confidence of the parameters was established, which ensured the robustness of the method. Chapter III presents the development of a dissolution method using in silico (DDDplusTM) as a tool, in which an experimental design of the complete factorial type 33 was defined using as factors: the formulation, use of sinker and agitation speed. For in vitro dissolution assays, another factor design 3(3-1) was proposed to obtain the calibration constants of the in silico simulations. Through a statistical analysis of the dissolution efficiencies obtained in the simulations, the effects and interactions between the factors were evaluated. Thus, the final conditions of the dissolution method established were: 900 mL of pH 6.8 phosphate buffer as a dissolution medium, 75 rpm of stirring speed, and use of sinker to avoid the fluctuation of the formulations. The method developed was used, in the context of Chapter IV, to evaluate the dissolution profile of HTZ and VAL products marketed in Brazil and Peru. By multivariate analysis, the dissolution efficiency (ED), mean dissolution time (MDT) and the dissolution percentages from 5 to 60 minutes were used to group the formulations in different groups. Although the dissolution profiles show a similarity between all the evaluated formulations, the reference product stood out for presenting a higher ED compared to the other formulations, due to the higher release in the first 5 minutes of the test. It was concluded that the proposed method, besides guaranteeing the total release of HTZ and VAL from the formulations, has adequate discriminatory capacity

On the Role of Cortex-Basal Ganglia Interactions for Category Learning: A Neurocomputational Approach.

In addition to the prefrontal cortex (PFC), the basal ganglia (BG) have been increasingly often reported to play a fundamental role in category learning, but the circuit mechanisms mediating their interaction remain to be explored. We developed a novel neurocomputational model of category learning that particularly addresses the BG-PFC interplay. We propose that the BG bias PFC activity by removing the inhibition of cortico-thalamo-cortical loop and thereby provide a teaching signal to guide the acquisition of category representations in the corticocortical associations to the PFC. Our model replicates key behavioral and physiological data of macaque monkey learning a prototype distortion task from Antzoulatos and Miller (2011) Our simulations allowed us to gain a deeper insight into the observed drop of category selectivity in striatal neurons seen in the experimental data and in the model. The simulation results and a new analysis of the experimental data based on the model's predictions show that the drop in category selectivity of the striatum emerges as the variability of responses in the striatum rises when confronting the BG with an increasingly larger number of stimuli to be classified. The neurocomputational model therefore provides new testable insights of systems-level brain circuits involved in category learning that may also be generalized to better understand other cortico-BG-cortical loops.SIGNIFICANCE STATEMENT Inspired by the idea that basal ganglia (BG) teach the prefrontal cortex (PFC) to acquire category representations, we developed a novel neurocomputational model and tested it on a task that was recently applied in monkey experiments. As an advantage over previous models of category learning, our model allows to compare simulation data with single-cell recordings in PFC and BG. We not only derived model predictions, but already verified a prediction to explain the observed drop in striatal category selectivity. When testing our model with a simple, real-world face categorization task, we observed that the fast striatal learning with a performance of 85% correct responses can teach the slower PFC learning to push the model performance up to almost 100%.

Identification of neprilysin as a potential target of arteannuin using computational drug repositioning

ABSTRACT The discovery of arteannuin (qinghaosu) in the 20th Century was a major advance for medicine. Besides functioning as a malaria therapy, arteannuin is a pharmacological agent in a range of other diseases, but its mechanism of action remains obscure. In this study, the reverse docking server PharmMapper was used to identify potential targets of arteannuin. The results were checked using the chemical-protein interactome servers DRAR-CPI and DDI-CPI, and verified by AutoDock Vina. The results showed that neprilysin (also known as CD10), a common acute lymphoblastic leukaemia antigen, was the top disease-related target of arteannuin. The chemical-protein interactome and docking results agreed with those of PharmMapper, further implicating neprilysin as a potential target. Although experimental verification is required, this study provides guidance for future pharmacological investigations into novel clinical applications for arteannuin.

Medical Devices; Cardiovascular Devices; Classification of the Coronary Vascular Physiologic Simulation Software Device. Final order.

The Food and Drug Administration (FDA) is classifying the coronary vascular physiologic simulation software device into class II (special controls). The special controls that will apply to the device are identified in this order and will be part of the codified language for the coronary vascular physiologic simulation software device's classification. The Agency is classifying the device into class II (special controls) in order to provide a reasonable assurance of safety and effectiveness of the device.

Rule-based multi-scale simulation for drug effect pathway analysis.

BACKGROUND: Biological systems are robust and complex to maintain stable phenotypes under various conditions. In these systems, drugs reported the limited efficacy and unexpected side-effects. To remedy this situation, many pharmaceutical laboratories have begun to research combination drugs and some of them have shown successful clinical results. Complementary action of multiple compounds could increase efficacy as well as reduce side-effects through pharmacological interactions. However, experimental approach requires vast cost of preclinical experiments and tests as the number of possible combinations of compound dosages increases exponentially. Computer model-based experiments have been emerging as one of the most promising solutions to cope with such complexity. Though there have been many efforts to model specific molecular pathways using qualitative and quantitative formalisms, they suffer from unexpected results caused by distant interactions beyond their localized models. RESULTS: In this work, we propose a rule-based multi-scale modelling platform. We have tested this platform with Type 2 diabetes (T2D) model, which involves the malfunction of numerous organs such as pancreas, circulation system, liver, and adipocyte. We have extracted T2D-related 190 rules by manual curation from literature, pathway databases and converting from different types of existing models. We have simulated twenty-two T2D drugs. The results of our simulation show drug effect pathways of T2D drugs and whether combination drugs have efficacy or not and how combination drugs work on the multi-scale model. CONCLUSIONS: We believe that our simulation would help to understand drug mechanism for the drug development and provide a new way to effectively apply existing drugs for new target. It also would give insight for identifying effective combination drugs.

A proposed classification of simulators.

This paper provides a coherent and comprehensive classification of simulators, using a five letter coding system, and is based on the characteristics of the user interface and the logic controller.

Hierarchical estimation of a dense deformation field for 3-D robust registration.

A new method for medical image registration is formulated as a minimization problem involving robust estimators. We propose an efficient hierarchical optimization framework which is both multiresolution and multigrid. An anatomical segmentation of the cortex is introduced in the adaptive partitioning of the volume on which the multigrid minimization is based. This allows to limit the estimation to the areas of interest, to accelerate the algorithm, and to refine the estimation in specified areas. At each stage of the hierarchical estimation, we refine current estimate by seeking a piecewise affine model for the incremental deformation field. The performance of this method is numerically evaluated on simulated data and its benefits and robustness are shown on a database of 18 magnetic resonance imaging scans of the head.

Classification criteria for simulation programs used in medical education.

Simulation programs are often used in medical education and their large variety allows a classification according to several criteria. A system of eight axes is proposed here for such a classification: topic area, system level, simulated feature, basic model, main purpose, results presentation, warnings, and evaluation.