3D-QSAR study of microsomal prostaglandin E<Subscript>2</Subscript> synthase(mPGES-1) inhibitors

Microsomal prostaglandin E₂ synthase (mPGES-1) has been identified recently as a novel target for treating pain and inflammation. The aim of this study is to understand the binding affinities of reported inhibitors for mPGES-1 and further to design potential new mPGES-1 inhibitors. 3D-QSAR-CoMFA (comparative molecular field analysis) and CoMSIA (comparative molecular similarity indices analysis) - techniques were employed on a series of indole derivatives that act as selective mPGES-1 inhibitors. The lowest energy conformer of the most active compound obtained from systematic conformational search was used as a template for the alignment of 32 compounds. The models obtained were used to predict the activities of the test set of eight compounds, and the predicted values were in good agreement with the experimental results. The 3D-QSAR models derived from the training set of 24 compounds were all statistically significant (CoMFA; q ² = 0.89, r ² = 0.95, , and CoMSIA; q ² = 0.84, r ² = 0.93, , ). Contour plots generated for the CoMFA and CoMSIA models reveal useful clues for improving the activity of mPGES-1 inhibitors. In particular, substitutions of an electronegative fluorine atom or a bulky hydrophilic phenoxy group at the meta or para positions of the biphenyl rings might improve inhibitory activity. A plausible binding mode between the ligands and mPGES-1 is also proposed.     

Effect of the engineered indole pathway on accumulation of phenolic compounds in Catharanthus roseus hairy roots

Catharanthus roseus has been well-known to contain indole alkaloids effective for treatment of diverse cancers. We examined the intracellular accumulation profiles of phenolic compounds in response to ectopic overexpression of tryptophan feedback-resistant anthranilate synthase holoenzyme (ASalphabeta) in C. roseus hairy roots. Among 13 phenolic compounds measured, 6 phenolic compounds were detected in late exponential phase ASalphabeta hairy roots. Uninduced and induced ASalphabeta hairy roots accumulated up to 1.2 and 4.5 mg/g DW over a 72-h period, respectively. Upon induction, in parallel with a rapid increase in tryptophan in the first 48 h, accumulation of phenolic compounds tended to increase to a maximum level (4.5 mg/g DW) at 48 h, after which phenolic levels decreased back to the uninduced level by 72 h. Naringin was a predominant form that comprised about 72% and 36% of the total content of phenolic compounds in the uninduced and induced lines, respectively. Upon induction, accumulation of catechin drastically increased with the highest level (3.6 mg/g) occurring at 48 h, whereas that of all others except for salicylic acid showed no statistical difference. Catechin is a final product of the flavonoid pathway, and thus metabolic flux into this pathway is transiently increased by overexpression of AS. Like catechin, salicylic acid is very sensitive to induction as it began to increase to 5-fold within 4 h of induction, but unlike catechin, no significant accumulation of salicylic acid was noted after 4 h of induction. The results suggest differential regulation of this particular biosynthesis branch within the phenolic pathway.     

Characterization of an ethanol-inducible promoter system in Catharanthus roseus hairy roots

Efforts to engineer Catharanthus roseus hairy roots to produce commercially significant amounts of valuable compounds, such as the terpenoid indole alkaloids vinblastine and vincristine, require the development of tools to study the effects of overexpressing key metabolic and regulatory genes. The use of inducible promoters allows researchers to control the timing and level of expression of genes of interest. In addition, use of inducible promoters allows researchers to use a single transgenic line as both the control and experimental line, minimizing the problems associated with clonal variation. We have previously characterized the use of a glucocorticoid-inducible promoter system to study the effects of gene overexpression within the terpenoid indole alkaloid pathway on metabolite production. Here the feasibility of using an ethanol-inducible promoter within C. roseus hairy roots is reported. This ethanol-inducible promoter is highly sensitive to ethanol concentration with a concentration of 0.005% ethanol causing a 6-fold increase in CAT reporter activity after 24 h of induction. The ethanol-inducible CAT activity increased 24-fold over a 72-h induction period with 0.5% ethanol.     

Peripartum cardiomyopathy: a global effort to find the cause and cure for the rare and little understood disease

In this review, we present our current understanding of peripartum cardiomyopathy (PPCM) based on reports of the incidence, diagnosis and current treatment options. We summarise opinions on whether PPCM is triggered by vascular and/or hormonal causes and examine the influence of comorbidities such as preeclampsia. Two articles published in 2021 strongly support the hypothesis that PPCM may be a familial disease. Using large cohorts of PPCM patients, they summarised the available genomic DNA sequence data that are expressed in human cardiomyocytes. While PPCM is considered a disease predominately affecting the left ventricle, there are data to suggest that some cases also involve right ventricular failure. Finally, we conclude that there is sufficient evidence to warrant an RNAseq investigation and that this would be most informative if performed at the cardiomyocytes level rather than analysing genomic DNA from the peripheral circulation. Given the rarity of PPCM, the combined resources of international human heart tissue biobanks have assembled 30 ventricular tissue samples from PPCM patients, and we are actively seeking to enlarge this patient base by collaborating with human heart tissue banks and research laboratories who would like to join this endeavour.     

A network-based approach to integrate nutrient microenvironment in the prediction of synthetic lethality in cancer metabolism

Synthetic Lethality (SL) is currently defined as a type of genetic interaction in which the loss of function of either of two genes individually has limited effect in cell viability but inactivation of both genes simultaneously leads to cell death. Given the profound genomic aberrations acquired by tumor cells, which can be systematically identified with -omics data, SL is a promising concept in cancer research. In particular, SL has received much attention in the area of cancer metabolism, due to the fact that relevant functional alterations concentrate on key metabolic pathways that promote cellular proliferation. With the extensive prior knowledge about human metabolic networks, a number of computational methods have been developed to predict SL in cancer metabolism, including the genetic Minimal Cut Sets (gMCSs) approach. A major challenge in the application of SL approaches to cancer metabolism is to systematically integrate tumor microenvironment, given that genetic interactions and nutritional availability are interconnected to support proliferation. Here, we propose a more general definition of SL for cancer metabolism that combines genetic and environmental interactions, namely loss of gene functions and absence of nutrients in the environment. We extend our gMCSs approach to determine this new family of metabolic synthetic lethal interactions. A computational and experimental proof-of-concept is presented for predicting the lethality of dihydrofolate reductase (DHFR) inhibition in different environments. Finally, our approach is applied to identify extracellular nutrient dependences of tumor cells, elucidating cholesterol and myo-inositol depletion as potential vulnerabilities in different malignancies.     

Understanding photosynthetic biofilm productivity and structure through 2D simulation

We present a spatial model describing the growth of a photosynthetic microalgae biofilm. In this 2D-model we consider photosynthesis, cell carbon accumulation, extracellular matrix excretion, and mortality. The rate of each of these mechanisms is given by kinetic laws regulated by light, nitrate, oxygen and inorganic carbon. The model is based on mixture theory and the behaviour of each component is defined on one hand by mass conservation, which takes into account biological features of the system, and on the other hand by conservation of momentum, which expresses the physical properties of the components. The model simulates the biofilm structural dynamics following an initial colonization phase. It shows that a 75 μm thick active region drives the biofilm development. We then determine the optimal harvesting period and biofilm height which maximize productivity. Finally, different harvesting patterns are tested and their effect on biofilm structure are discussed. The optimal strategy differs whether the objective is to recover the total biofilm or just the algal biomass.