Novel Biginelli dihydropyrimidines with potential anticancer activity: A parallel synthesis and CoMSIA study

Novel Biginelli dihydropyrimidines of biological interest were prepared using p-toluene sulphonic acid as an efficient catalyst. All the thirty-two synthesised dihydropyrimidines were evaluated for their in vitro antioxidant activity using DPPH method. Only, compounds 28 and 29 exhibited reasonably good antioxidant activity. Furthermore, the synthesised Biginelli compounds were subjected for their in vitro anticancer activity against MCF-7 human breast cancer cells. The title compounds were tested at the concentration of 10 μg. Compounds exhibited activity ranging from weak to moderate and, from moderate to high in terms of percentage cytotoxicity. Among them, compounds 10 and 11 exhibited significant anticancer activity. In order to elucidate the three-dimensional structure–activity relationships (3D QSAR) towards their anticancer activity, we subjected them for comparative molecular similarity indices analysis (CoMSIA). Illustration regarding their synthesis, analysis, antioxidant activity, anticancer activity and 3D QSAR study is described.

Molecular Modelling of Estrogen-Producing Enzymes CYP450 Aromatase and 17beta-Hydroxysteroid Dehydrogenase Type 1

Breast cancer is the most common cancer in women in the western countries. Approximately two-thirds of breast cancer tumours are hormone dependent, requiring estrogens to grow. Estrogens are formed in the human body via a multistep route starting from cholesterol. The final steps in the biosynthesis include the CYP450 aromatase enzyme, converting the male hormones androgens (preferred substrate androstenedione ASD) into estrogens(estrone E1), and the 17beta-HSD1 enzyme, converting the biologically less active E1 into the active hormone 17beta-hydroxyestradiol E2. E2 is bound to the nuclear estrogen receptors causing a cascade of biochemical reactions leading to cell proliferation in normal tissue, and to tumour growth in cancer tissue. Aromatase and 17beta-HSD1 are expressed in or near the breast tumour, locally providing the tissue with estrogens. One approach in treating hormone dependent breast tumours is to block the local estrogen production by inhibiting these two enzymes. Aromatase inhibitors are already on the market in treating breast cancer, despite the lack of an experimentally solved structure. The structure of 17beta-HSD1, on the other hand, has been solved, but no commercial drugs have emerged from the drug discovery projects reported in the literature. Computer-assisted molecular modelling is an invaluable tool in modern drug design projects. Modelling techniques can be used to generate a model of the target protein and to design novel inhibitors for them even if the target protein structure is unknown. Molecular modelling has applications in predicting the activities of theoretical inhibitors and in finding possible active inhibitors from a compound database. Inhibitor binding at atomic level can also be studied with molecular modelling. To clarify the interactions between the aromatase enzyme and its substrate and inhibitors, we generated a homology model based on a mammalian CYP450 enzyme, rabbit progesterone 21-hydroxylase CYP2C5. The model was carefully validated using molecular dynamics simulations (MDS) with and without the natural substrate ASD. Binding orientation of the inhibitors was based on the hypothesis that the inhibitors coordinate to the heme iron, and were studied using MDS. The inhibitors were dietary phytoestrogens, which have been shown to reduce the risk for breast cancer. To further validate the model, the interactions of a commercial breast cancer drug were studied with MDS and ligand–protein docking. In the case of 17beta-HSD1, a 3D QSAR model was generated on the basis of MDS of an enzyme complex with active inhibitor and ligand–protein docking, employing a compound library synthesised in our laboratory. Furthermore, four pharmacophore hypotheses with and without a bound substrate or an inhibitor were developed and used in screening a commercial database of drug-like compounds. The homology model of aromatase showed stable behaviour in MDS and was capable of explaining most of the results from mutagenesis studies. We were able to identify the active site residues contributing to the inhibitor binding, and explain differences in coordination geometry corresponding to the inhibitory activity. Interactions between the inhibitors and aromatase were in agreement with the mutagenesis studies reported for aromatase. Simulations of 17beta-HSD1 with inhibitors revealed an inhibitor binding mode with hydrogen bond interactions previously not reported, and a hydrophobic pocket capable of accommodating a bulky side chain. Pharmacophore hypothesis generation, followed by virtual screening, was able to identify several compounds that can be used in lead compound generation. The visualisation of the interaction fields from the QSAR model and the pharmacophores provided us with novel ideas for inhibitor development in our drug discovery project.

Effective descriptions of molecular structures and the quantitative structure - Activity relationship studies

In this research. we found CoMFA alone could not obtain sufficiently a strong equation to allow confident prediction for aminobenzenes. When some other parameter. such as heat of molecular formation of the compounds, was introduced into the CoMFA model, the results Were improved greatly. It gives us a hint that a better description for molecular structures will yield a better prediction model, and this hint challenged us to look for another method-the projection areas of molecules in 3D space for 3D-QSAR. It is surprising that much better results than that obtained by using CoMFA Were achieved. Besides the CoMFA analysis. multiregression analysis and neural network methods for building the models were used in this paper.

广义二面角在定量结构/活性相关分析中的应用

化合物的结构与其活性具有相关性 .建立相关性需要由结构提取特征 ,并运用这些特征作为自变量去构造数学模型 ,以便预测未知的化合物及其活性 .目前 ,在诸多 3D- QSAR方法中 ,应用最为广泛的是 Co MFA( Comparasive Molecular Field Analysis)方法 [1～ 3] ,但新近的研究发现 ,Co MFA方法对于某类化合物 (如苯胺类化合物 )适应性较差 ,但分子在三维空间投影面积及量化参数的引入可大大改善所得结果[4 ] .本文从另一角度 (即广义二面角 )研究了分子在三维空间的形状 ,得到了满意的结果 .1　实验部分本文选用 34个 1 - [( 2 - Hydroxyethoxy) methyl]- 6- ( phenylthio) thymine( HEPT)类化合物 [5] ,通式见Scheme 1　 HEPT derivative substituted HEPTScheme 1 .表 1中分别列出了 34个分子对应的 R,X,Y基团 .该类化合物是具有较高生物活性的抗艾滋病药物 ,其活性以 EC50 表示 ( EC50 为降低 5 0 %T4细胞而被 HIV...

Three-dimensional quantitative structure-activity relationship of the opioid antagonist with potent anorectant activity of 3,4-dimethyl-4-(3-hydroxyphenyl) piperidine

A series of 3,4-dimethyl-4-(3-hydroxyphenyl) piperidine opioid antagonists with varying substituents on the nitrogen were evaluated for their effect on food consumption in obese Zucker rats. In developing three-dimensional quantitative structure-activity relationship (3D-QSAR) studies for this series of opioid antagonists, different structure alignments have been tested to predict the anorectant activities. The interaction energies between molecules and the probe atom were then correlated with anorectant activity using partial least squares (PLS) method. The steric and electrostatic features of the 3D-QSAR were presented in the form of standard deviation coefficient contour maps of steric and electrostatic fields. The results showed that 3D-QSAR results are much better than the results obtained by 2D-QSAR.

三维分子特征的提取及苯胺类化合物结构—毒性相关性研究

在环境中有许多污染物,如多氯联苯,多环芳烃,DDT等,这些化合物具有难降解性,高脂溶性及易生物储积,所以潜在的毒性很大。本文侧重研究的是苯胺类化合物结构与性质相关性(QSAR)。 该类研究的关键是如何有效地表征化合的结构。从80年代以来,在定量构效关系研究中,陆续出现一些考虑生物活性分子与受体结合时三维结构的研究方法,统称为三维定量构效关系(3D-QSAR)研究。其中,最典型应用最普遍的3D-QSAR、方法之一是CoMFA方法。新近,在我们的研究中发现对于某些类的化合物,CoMFA适应性

Studies on three-dimensional quantitative structure-activity relationship of PDE inhibitory activity of imidazopyridines

In recent years there has been a resurgence of interest in inhibitors of cyclic nucleotide phosphodiesterases (PDE) and enzymes responsible for the intracellular hydrolysis of the second messenger cAMP and cGMP. In this study, a series of 2-substituted phenyllimidazo[4,5-b]pyridines have been made to investigate 3D-QSAR of PDE activity using CoMFA. CoMFA resulted in a quantitative description of the major steric and electrostatic field effects, and gave significant new insights to factors governing PDE inhibition activity. The model was used to predict the PDE inhibition activity of imidazopyridines with satisfactory results.

Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

Accurate in silico models for the quantitative prediction of the activity of G protein-coupled receptor (GPCR) ligands would greatly facilitate the process of drug discovery and development. Several methodologies have been developed based on the properties of the ligands, the direct study of the receptor-ligand interactions, or a combination of both approaches. Ligand-based three-dimensional quantitative structure-activity relationships (3D-QSAR) techniques, not requiring knowledge of the receptor structure, have been historically the first to be applied to the prediction of the activity of GPCR ligands. They are generally endowed with robustness and good ranking ability; however they are highly dependent on training sets. Structure-based techniques generally do not provide the level of accuracy necessary to yield meaningful rankings when applied to GPCR homology models. However, they are essentially independent from training sets and have a sufficient level of accuracy to allow an effective discrimination between binders and nonbinders, thus qualifying as viable lead discovery tools. The combination of ligand and structure-based methodologies in the form of receptor-based 3D-QSAR and ligand and structure-based consensus models results in robust and accurate quantitative predictions. The contribution of the structure-based component to these combined approaches is expected to become more substantial and effective in the future, as more sophisticated scoring functions are developed and more detailed structural information on GPCRs is gathered.

CoMFA and homology-based models of the glycine binding site of N-methyl-D-aspartate receptor

Homology modeling was used to build 3D models of the N-methyl-D-aspartate (NMDA) receptor glycine binding site on the basis of an X-ray structure of the water-soluble AMPA-sensitive receptor. The docking of agonists and antagonists to these models was used to reveal binding modes of ligands and to explain known structure-activity relationships. Two types of quantitative models, 3D-QSAR/CoMFA and a regression model based on docking energies, were built for antagonists (derivatives of 4-hydroxy-2-quinolone, quinoxaline-2,3-dione, and related compounds). The CoMFA steric and electrostatic maps were superimposed on the homology-based model, and a close correspondence was marked. The derived computational models have permitted the evaluation of the structural features crucial for high glycine binding site affinity and are important for the design of new ligands.

Volatile terpenoids and C13 norisoprenoids in wines: development of rapid methods of analysis and evaluation of the sesquiterpenoids biological potential

Vitis vinifera L., the most widely cultivated fruit crop in the world, was the starting point for the development of this PhD thesis. This subject was exploited following on two actual trends: i) the development of rapid, simple, and high sensitive methodologies with minimal sample handling; and ii) the valuation of natural products as a source of compounds with potential health benefits. The target group of compounds under study were the volatile terpenoids (mono and sesquiterpenoids) and C13 norisoprenoids, since they may present biological impact, either from the sensorial point of view, as regards to the wine aroma, or by the beneficial properties for the human health. Two novel methodologies for quantification of C13 norisoprenoids in wines were developed. The first methodology, a rapid method, was based on the headspace solid-phase microextraction combined with gas chromatography-quadrupole mass spectrometry operating at selected ion monitoring mode (HS-SPME/GC-qMS-SIM), using GC conditions that allowed obtaining a C13 norisoprenoid volatile signature. It does not require any pre-treatment of the sample, and the C13 norisoprenoid composition of the wine was evaluated based on the chromatographic profile and specific m/z fragments, without complete chromatographic separation of its components. The second methodology, used as reference method, was based on the HS-SPME/GC-qMS-SIM, allowing the GC conditions for an adequate chromatographic resolution of wine components. For quantification purposes, external calibration curves were constructed with β-ionone, with regression coefficient (r2) of 0.9968 (RSD 12.51 %) and 0.9940 (RSD of 1.08 %) for the rapid method and for the reference method, respectively. Low detection limits (1.57 and 1.10 μg L-1) were observed. These methodologies were applied to seventeen white and red table wines. Two vitispirane isomers (158-1529 L-1) and 1,1,6-trimethyl-1,2-dihydronaphthalene (TDN) (6.42-39.45 μg L-1) were quantified. The data obtained for vitispirane isomers and TDN using the two methods were highly correlated (r2 of 0.9756 and 0.9630, respectively). A rapid methodology for the establishment of the varietal volatile profile of Vitis vinifera L. cv. 'Fernão-Pires' (FP) white wines by headspace solid-phase microextraction combined with comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (HS-SPME/GCxGC-TOFMS) was developed. Monovarietal wines from different harvests, Appellations, and producers were analysed. The study was focused on the volatiles that seem to be significant to the varietal character, such as mono and sesquiterpenic compounds, and C13 norisoprenoids. Two-dimensional chromatographic spaces containing the varietal compounds using the m/z fragments 93, 121, 161, 175 and 204 were established as follows: 1tR = 255-575 s, 2tR = 0,424-1,840 s, for monoterpenoids, 1tR = 555-685 s, 2tR = 0,528-0,856 s, for C13 norisoprenoids, and 1tR = 695-950 s, 2tR = 0,520-0,960 s, for sesquiterpenic compounds. For the three chemical groups under study, from a total of 170 compounds, 45 were determined in all wines, allowing defining the "varietal volatile profile" of FP wine. Among these compounds, 15 were detected for the first time in FP wines. This study proposes a HS-SPME/GCxGC-TOFMS based methodology combined with classification-reference sample to be used for rapid assessment of varietal volatile profile of wines. This approach is very useful to eliminate the majority of the non-terpenic and non-C13 norisoprenic compounds, allowing the definition of a two-dimensional chromatographic space containing these compounds, simplifying the data compared to the original data, and reducing the time of analysis. The presence of sesquiterpenic compounds in Vitis vinifera L. related products, to which are assigned several biological properties, prompted us to investigate the antioxidant, antiproliferative and hepatoprotective activities of some sesquiterpenic compounds. Firstly, the antiradical capacity of trans,trans-farnesol, cis-nerolidol, α-humulene and guaiazulene was evaluated using chemical (DPPH• and hydroxyl radicals) and biological (Caco-2 cells) models. Guaiazulene (IC50= 0.73 mM) was the sesquiterpene with higher scavenger capacity against DPPH•, while trans,trans-farnesol (IC50= 1.81 mM) and cis-nerolidol (IC50= 1.48 mM) were more active towards hydroxyl radicals. All compounds, with the exception of α-humulene, at non-cytotoxic levels (≤ 1 mM), were able to protect Caco-2 cells from oxidative stress induced by tert-butyl hydroperoxide. The activity of the compounds under study was also evaluated as antiproliferative agents. Guaiazulene and cis-nerolidol were able to more effectively arrest the cell cycle in the S-phase than trans,trans-farnesol and α-humulene, being the last almost inactive. The relative hepatoprotection effect of fifteen sesquiterpenic compounds, presenting different chemical structures and commonly found in plants and plant-derived foods and beverages, was assessed. Endogenous lipid peroxidation and induced lipid peroxidation with tert-butyl hydroperoxide were evaluated in liver homogenates from Wistar rats. With the exception of α-humulene, all the sesquiterpenic compounds under study (1 mM) were effective in reducing the malonaldehyde levels in both endogenous and induced lipid peroxidation up to 35% and 70%, respectively. The developed 3D-QSAR models, relating the hepatoprotection activity with molecular properties, showed good fit (R2LOO > 0.819) with good prediction power (Q2 > 0.950 and SDEP < 2%) for both models. A network of effects associated with structural and chemical features of sesquiterpenic compounds such as shape, branching, symmetry, and presence of electronegative fragments, can modulate the hepatoprotective activity observed for these compounds. In conclusion, this study allowed the development of rapid and in-depth methods for the assessment of varietal volatile compounds that might have a positive impact on sensorial and health attributes related to Vitis vinifera L. These approaches can be extended to the analysis of other related food matrices, including grapes and musts, among others. In addition, the results of in vitro assays open a perspective for the promising use of the sesquiterpenic compounds, with similar chemical structures such as those studied in the present work, as antioxidants, hepatoprotective and antiproliferative agents, which meets the current challenges related to diseases of modern civilization.

Estructura computacional i aplicacions de la semblança molecular quàntica

La tesis tracta diferents aspectes relacionats amb el càlcul de la semblança quàntica, així com la seva aplicació en la racionalització i predicció de l'activitat de fàrmacs. Es poden destacar dos progressos importants en el desenvolupament de noves metodologies que faciliten el càlcul de les mesures de semblança quàntica. En primer lloc, la descripció de les molècules mitjançant les funciones densitat aproximades PASA (Promolecular Atomic Shell Approximation) ha permès descriure amb suficient precisió la densitat electrònica dels sistemes moleculars analitzats, reduint substancialment el temps de càlcul de les mesures de semblança. En segon lloc, el desenvolupament de tècniques de superposició molecular específiques de les mesures de semblança quàntica ha permès resoldre el problema de l'alineament en l'espai dels compostos comparats. El perfeccionament d'aquests nous procediments i algoritmes matemàtics associats a les mesures de semblança molecular quàntica, ha estat essencial per poder progressar en diferents disciplines de la química computacional, sobretot les relacionades amb les anàlisis quantitatives entre les estructures moleculars i les seves activitats biològiques, conegudes amb les sigles angleses QSAR (Quantitative Structure-Activity Relationships). Precisament en l'àrea de les relacions estructura-activitat s'han presentat dues aproximacions fonamentades en la semblança molecular quàntica que s'originen a partir de dues representacions diferents de les molècules. La primera descripció considera la densitat electrònica global de les molècules i és important, entre altres, la disposició dels objectes comparats en l'espai i la seva conformació tridimensional. El resultat és una matriu de semblança amb les mesures de semblança de tots els parells de compostos que formen el conjunt estudiat. La segona descripció es fonamenta en la partició de la densitat global de les molècules en fragments. S'utilitzen mesures d'autosemblança per analitzar els requeriments bàsics d'una determinada activitat des del punt de vista de la semblança quàntica. El procés permet la detecció de les regions moleculars que són responsables d'una alta resposta biològica. Això permet obtenir un patró amb les regions actives que és d'evident interès per als propòsits del disseny de fàrmacs. En definitiva, s'ha comprovat que mitjançant la simulació i manipulació informàtica de les molècules en tres dimensions es pot obtenir una informació essencial en l'estudi de la interacció entre els fàrmacs i els seus receptors macromoleculars.

Synthesis and structure-activity relationship studies of CD4 down-modulating cyclotriazadisulfonamide (CADA) analogues

HIV attachment via the CD4 receptor is an important target for developing novel approaches to HIV chemotherapy. Cyclotriazadisulfonamide (CADA) inhibits HIV at submicromolar levels by specifically down-modulating cell-surface and intracellular CD4. An effective five-step synthesis of CADA in 30% overall yield is reported. This synthesis has also been modified to produce more than 50 analogues. Many tail-group analogues have been made by removing the benzyl tail of CADA and replacing it with various alkyl, acyl, alkoxycarbonyl and aminocarbonyl substituents. A series of sidearm analogues, including two unsymmetrical compounds, have also been prepared by modifying the CADA synthesis, replacing the toluenesulfonyl sidearms with other sulfonyl groups. Testing 30 of these compounds in MT-4 cells shows a wide range of CD4 down-modulation potency, which correlates with ability to inhibit HIV-1. Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were constructed using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches. The X-ray crystal structures of four compounds, including CADA, show the same major conformation of the central 12-membered ring. The solid-state structure of CADA was energy minimized and used to generate the remaining 29 structures, which were similarly minimized and aligned to produce the 3D-QSAR models. Both models indicate that steric bulk of the tail group, and, to a lesser extent, the sidearms mainly determine CD4 down-modulation potency in this series of compounds.

Quantitative structure-activity relationships for a series of inhibitors of cruzain from Trypanosoma cruzi: Molecular modeling, CoMFA and CoMSIA studies

Human parasitic diseases are the foremost threat to human health and welfare around the world. Trypanosomiasis is a very serious infectious disease against which the currently available drugs are limited and not effective. Therefore, there is an urgent need for new chemotherapeutic agents. One attractive drug target is the major cysteine protease from Trypanosoma cruzi, cruzain. In the present work, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) studies were conducted on a series of thiosemicarbazone and semicarbazone derivatives as inhibitors of cruzain. Molecular modeling studies were performed in order to identify the preferred binding mode of the inhibitors into the enzyme active site, and to generate structural alignments for the three-dimensional quantitative structure-activity relationship (3D QSAR) investigations. Statistically significant models were obtained (CoMFA. r(2) = 0.96 and q(2) = 0.78; CoMSIA, r(2) = 0.91 and q(2) = 0.73), indicating their predictive ability for untested compounds. The models were externally validated employing a test set, and the predicted values were in good agreement with the experimental results. The final QSAR models and the information gathered from the 3D CoMFA and CoMSIA contour maps provided important insights into the chemical and structural basis involved in the molecular recognition process of this family of cruzain inhibitors, and should be useful for the design of new structurally related analogs with improved potency. (C) 2009 Elsevier Inc. All rights reserved.

Structure-Based Approach for the Study of Estrogen Receptor Binding Affinity and Subtype Selectivity

Estrogens exert important physiological effects through the modulation of two human estrogen receptor (hER) subtypes, alpa (hER alpha) and beta (hER beta). Because the levels and relative proportion of hER alpha and hER beta differ significantly in different target cells, selective hER ligands could target specific tissues or pathways regulated by one receptor subtype without affecting the other. To understand the structural and chemical basis by which small molecule modulators are able to discriminate between the two subtypes, we have applied three-dimensional target-based approaches employing a series of potent hER-ligands. Comparative molecular field analysis (CoMFA) studies were applied to a data set of 81 hER modulators, for which binding affinity values were collected for both hER alpha and hER beta. Significant statistical coefficients were obtained (hER alpha, q(2) = 0.76; hER beta, q(2) = 0.70), indicating the internal consistency of the models. The generated models were validated using external test sets, and the predicted values were in good agreement with the experimental results. Five hER crystal structures were used in GRID/PCA investigations to generate molecular interaction fields (MIF) maps. hER alpha and hER beta were separated using one factor. The resulting 3D information was integrated with the aim of revealing the most relevant structural features involved in hER subtype selectivity. The final QSAR and GRID/PCA models and the information gathered from 3D contour maps should be useful for the design or novel hER modulators with improved selectivity.

Quantitative structure-activity studies on a series of migrastatin analogs as inhibitors of cancer cell metastasis

Migrastatin, a macrolide natural product, and its structurally related analogs are potent inhibitors of cancer cell metastasis, invasion and migration. In the present work, a specialized fragment-based method was employed to develop QSAR models for a series of migrastatin and isomigrastatin analogs. Significant correlation coefficients were obtained (best model, q(2) = 0.76 and r(2) = 0.91) indicating that the QSAR models possess high internal consistency. The best model was then used to predict the potency of an external test set, and the predicted values were in good agreement with the experimental results (R(2) (pred) = 0.85). The final model and the corresponding contribution maps, combined with molecular modeling studies, provided important insights into the key structural features for the anticancer activity of this family of synthetic compounds based on natural products.