Submitted by Maike Costa (maiksebas@gmail.com) on 2017-09-08T14:24:47Z No. of bitstreams: 1 arquivototal.pdf: 1265949 bytes, checksum: de2c53fd1f3937b88fb24a29f756845d (MD5) / Made available in DSpace on 2017-09-08T14:24:47Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 1265949 bytes, checksum: de2c53fd1f3937b88fb24a29f756845d (MD5) Previous issue date: 2017-02-10 / COSTA, A.O.C. In vitro and in silico evaluation of the antifungal activity of the R- (+) and S-(-) citronelal isomers, aginst fungi of the genus Cryptococcus. 2017. 52f. Dissertação (Pós-graduação em Produtos Naturais e Sintéticos Bioativos, Farmacologia). UFPB/CCS – João Pessoa – PB. Cryptococcus neoformans is an opportunistic pathogenic yeast with a wide geographical distribution, capable to infect the most varied types of animals. In humans, cryptococcosis mainly affects the central nervous system and lungs, less frequently the skin, presenting in general a serious and fatal evolution. Individuals with deficient immune systems are more likely to develop cryptococcosis, especially those afflicted with the human immunodeficiency virus. The conventional treatment of cryptococcosis uses potentially toxic antifungals for long periods and they have been target of resistance of these microorganisms, besides the high costs with the treatment. Given this panorama, the search for natural products with antifungal properties has been a promising alternative, with great attention of the students regarding the analysis of the essential oils and their constituents. Thus, the present research aimed to evaluate the biological effect of the R and S isomers of the citronellal phytoconstituent on fungi of the genus Cryptococcus, which could lead to the discovery of a molecule to the development of a new antifungal, besides contributing to obtain more information on the pharmacological potential of this phytoconstituent. MIC and MFC were determined, of the compounds, being 64 and 64 the values for R - (+) citronellal respectively, and 256 and 512, respectively, for citronellal S - (-), on fungi of the genus Cryptococcus; The antifungigram of the strains of Cryptococcus sp. was carried out with the antifungal agents amphotericin B, fluconazole and fluorocytosine where a resistance of fluconazole and flucytosine was observed; This study investigated the possible interference of monoterpenes in the study associated with the activity of these antifungal agents, noting that citronellal R did not present an apparent synergic effect, whereas S showed a much more synergistic effect, even capable of inhibiting the resistance caused by fluconazole; The microbial death curve of the R - (+) and S - (-) isomers of the citronellal phytoconstituent was determined on a previously chosen strain (FGF-3) and the fungicidal effects of the citronellal S isomer and concentration dependent fungicidal effect Of R citronelal; Its in silico variables were of good prospecting. In conclusion, the substances exhibited a good biological activity and correlation with other antifungal agents, showing synergistic effects in the association study and their in silico variables were well prospective, thus characterizing these fully viable substances to be continued their studies. / Cryptococcus neoformans é uma levedura patogênica oportunista, com ampla distribuição geográfica, capaz de infectar os mais variados tipos de animais. No homem, a criptococose acomete principalmente o sistema nervoso central e pulmões, com menor frequência a pele, apresentando-se de uma forma geral com evolução grave e fatal. Indivíduos com o sistema imunológico comprometido são mais susceptíveis de desenvolver a criptococose, principalmente os acometidos pelo vírus da imunodeficiência humana. O tratamento convencional da criptococose utiliza antifúngicos potencialmente tóxicos por longos períodos e que vêm sendo alvo de resistência desses micro-organismos, além dos elevados custos com o tratamento. Diante desse panorama, a busca por produtos naturais com propriedades antifúngicas têm sido uma alternativa promissora, com grande atenção dos estudiosos quanto à análise dos óleos essenciais e seus constituintes. Dessa forma, a atual pesquisa, teve por finalidade avaliar o efeito biológico dos isômeros R e S do fitoconstituinte citronelal, sobre fungos do gênero Cryptococcus, o que poderá conduzir à descoberta de uma molécula ao desenvolvimento de um novo antifúngico, além disso, contribuir para a obtenção de maiores informações sobre o potencial farmacológico desse fitoconstituinte. Foi determinada CIM e a CFM, dos compostos sendo 64 e 64 os valores para o R-(+) citronelal respectivamente, e 256 e 512, respectivamente, para o S-(-) citronelal, sobre fungos do gênero Cryptococcus; Foi realizado o antifungigrama das cepas de Cryptococcus Sp. com os antifúngicos anfotericina B, fluconazol e fluorcitosina onde observou-se uma resistência por parete do fluconazol e da flucitosina; Com isso foi investigado a possível interferência dos monoterpenos em estudo associados à atividade desses antifúngicos, observando que o R citronelal não apresentou efeito sinérgico aparente, enquanto o S apresentou um efeito bem mais sinérgico, capaz ate de inibir as resistências causadas com o fluconazol; Foi determinada a curva de morte microbiana dos isômeros R-(+) e S-(-) do fitoconstituinte citronelal, sobre uma cepa previamente escolhida (FGF-3) e foram observados os efeitos fungicidas do isômero S citronelal e efeito fungicida dependente de concentração do R citronelal; suas variáveis In silico foram de boa prospecção. Concluindo que as substancias exibiram uma boa atividade biológica e correlação com outros antifúngicos, apresentando efeitos sinérgicos no estudo de associação e suas variáveis In silico foram de boa prospecção, caracterizando assim essas substancias totalmente viáveis para que sejam continuados seus estudos.

Current excessive use and abuse of antibiotics has resulted in increasing bacterial resistance to common treatment options which is threatening to deprive us of a pillar of modern medicine. In this work methods to optimize the use of existing antibiotics and to help development of new antibiotics were developed and applied. Semi-mechanistic pharmacokinetic-pharmacodynamic (PKPD) models were developed to describe the time course of the dynamic effect and interaction of combinations of antibiotics. The models were applied to illustrate that colistin combined with a high dose of meropenem may overcome meropenem-resistant P. aeruginosa infections. The results from an in vivo dose finding study of meropenem was successfully predicted by the meropenem PKPD model in combination with a murine PK model, which supports model based dosage selection. However, the traditional PK/PD index based dose selection was predicted to have poor extrapolation properties from pre-clinical to clinical settings, and across patient populations. The precision of the model parameters, and hence the model predictions, is dependent on the experimental design. A limited study design is dictated by cost and, for in vivo studies, ethical reasons. In this work optimal design (OD) was demonstrated to be able to reduce the experimental effort in time-kill curve experiments and was utilized to suggest the experimental design for identification and estimation of an interaction between antibiotics. OD methods to handle inter occasion variability (IOV) in optimization of individual PK parameter estimates were proposed. The strategy was applied in the design of a sparse sampling schedule that aim to estimate individual exposures of colistin in a multi-centre clinical study. Plasma concentration samples from the first 100 patients have been analysed and indicate that the performance of the design is close to the predicted. The methods described in this thesis holds promise to facilitate the development of new antibiotics and to improve the use of existing antibiotics.

Antibiotics are among the most commonly prescribed drugs. Although the majority of these drugs were developed several decades ago, optimal dosage (dose, dosing interval and treatment duration) have still not been well defined. This thesis focuses on the development and evaluation of pharmacometric models that can be used as tools in the establishment of improved dosing strategies for novel and already clinically available antibacterial drugs. Infectious diseases are common causes of death in preterm and term newborn infants. A population pharmacokinetic (PK) model for gentamicin was developed based on data from a prospective study. Body-weight and age (gestational and post-natal age) were found to be major factors contributing to variability in gentamicin clearance and therefore important patient characteristics to consider for improved dosing regimens. A semi-mechanistic pharmacokinetic-pharmacodynamic (PKPD) model was also developed, to characterize in vitro bacterial growth and killing kinetics following exposure to six antibacterial drugs, representing a broad selection of mechanisms of action and PK as well as PD characteristics. The model performed well in describing a wide range of static and dynamic drug exposures and was easily applied to other bacterial strains and antibiotics. It is, therefore, likely to find application in early drug development programs. Dosing of antibiotics is usually based on summary endpoints such as the PK/PD indices. Predictions based on the PKPD model showed that the commonly used PK/PD indices were well identified for all investigated drugs, supporting that models based on in vitro data can be predictive of antibacterial effects observed in vivo. However, the PK/PD indices were sensitive to the study conditions and were not always consistent between patient populations. The PK/PD indices may therefore extrapolate poorly across sub-populations. A semi-mechanistic modeling approach, utilizing the type of models described here, may thus have higher predictive value in a dose optimization tailored to specific patient populations.