Structure-based analysis of the molecular recognitions between HIV-1 TAR-RNA and transcription factor nuclear factor-kappaB (NFkB).

In this paper we applied the "macromolecular docking" procedure to perform molecular modeling with the aim of screening transcription factor sequences for possible interaction to the HIV-1 TAR-RNA, employing the software Hex version 4.2. The molecular modeling data were compared with electrophoretic mobility shift assays (EMSA) and surface plasmon resonance (SPR) based biospecific interaction analysis (BIA) using an optical biosensor. Finally the specific interactions between NF-κB and RNA have been calculated utilizing the AMBER-MM and FMO calculations. The results obtained clearly indicate that (a) NF-kB p50 transcription factor can bind TAR-RNA; (b) this binding efficiency is lower than that displayed by NF-kB factor in respect to DNA sequences; (c) other structured RNAs used as controls do not bind to NF-kB; (d) TAR-RNA is capable to bind pre-formed NF-kB/DNA complexes. Despite the fact that our data do not indicate whether NF-kB/TAR-RNA complexes play a role in the early steps of HIV-1 transcriptional activation, the results presented strongly indicate that interactions between transcription factors recruited at the level of HIV-1 LTR might interact with the TAR-RNA and deserve further studies aimed to determine its role in the HIV-1 life cycle.

Potential benefits of the 19-nor-clerodane trans-dehydrocrotonin on the central nervous system / Potenciais benefícios do 19-nor-clerodano trans-desidrocrotonina isolado de Croton cajucara sobre o sistema nervoso central

This study examined the effect of trans-dehydrocrotonin (DCTN), a 19-nor-clerodane diterpene isolated from Croton cajucara Benth (Euphorbiaceae), as analgesic and its effect on the central nervous system (CNS) of rodents using different animal models. The DCTN intraperitoneally exhibited mild analgesic activity on hot-plate test, but exhibited strong antinociceptive activity against acetic acid-induced abdominal writhing and the ED50 was calculated to be 44.88 mg/kg. At higher doses (100 mg/kg) it exhibited mild CNS depressant activities in laboratory animals. Moreover, it has negligible antidepressant activity. After taking consideration of the drug interaction, the DCTN can be used as a potent analgesic agent in case of peripheral algesia, without affecting the CNS.

Neste estudo avaliou-se o efeito analgésico do diterpeno 19-nor-clerodano trans-desidrocrotonina (DCTN) isolado de Croton cajucara Benth (Euphorbiaceae), bem como seu efeito no sistema nervoso central utilizando-se diferentes tipos de modelos de animais roedores. A administração intraperitoneal deste diterpeno, no teste da placa quente, revelou sua atividade analgésica moderada. No entanto, no teste de contrações abdominais desencadeadas por ácido acético, a DCTN apresentou forte atividade antinociceptiva com DE50 de 44,88 mg/kg. Doses elevadas de DCTN (100 mg/kg) apresentaram moderada atividade depressiva do sistema nervoso central (SNC), não tendo sido evidenciado ação antidepressiva. Após algumas considerações da ação de DCTN em algesia periférica, concluiu-se que esta substância pode ser utilizada como um potente agente analgésico, sem afetar o SNC.

Potentials of phenolic molecules of natural origin and their derivatives as anti-HIV agents.

Identification of phenolic compounds and their derivatives interfering the several steps of the viral life cycle of the human immunodeficiency virus type 1 (HIV-1) is focused for the development of novel molecules for the treatment of AIDS. Several phenolic compounds isolated and characterized from natural sources have been studied in detail and found to exhibit inhibitory effects against different steps of the HIV-1 life cycle, including virus-cell fusion and virus absorption, reverse transcription, integration (IN) and proteolytic cleavage. In the review, we are summarizing some strong evidences demonstrating several phenolic molecules and their derivatives from natural sources display promising anti-HIV-1 activities. The anti-HIV compounds have been organized in this review according to their mechanism of action in the life cycle of HIV. We also mentioned some findings using in silico approaches, like virtual screening, docking, neural network, etc., and even the chemogenomics and/or functional genomics approaches could be useful for the quick identifying promising new lead anti-HIV molecules without having any other unwanted pharmacological effects. Plants having large amount of phenolic compounds, can be considered as strong sources of molecules for the treatment of HIV-1. Despite the continuous advances made in antiretroviral combination therapy, AIDS has become the leading cause of death in Africa and the fourth worldwide. Today, many research groups are exploring the bio- and chemo-diversity of the plant kingdom to find new and better anti-HIV drugs with novel mechanisms of action.

Dragon method for finding novel tyrosinase inhibitors: Biosilico identification and experimental in vitro assays.

QSAR (quantitative structure-activity relationship) studies of tyrosinase inhibitors employing Dragon descriptors and linear discriminant analysis (LDA) are presented here. A data set of 653 compounds, 245 with tyrosinase inhibitory activity and 408 having other clinical uses were used. The active data set was processed by k-means cluster analysis in order to design training and prediction series. Seven LDA-based QSAR models were obtained. The discriminant functions applied showed a globally good classification of 99.79% for the best model Class=-96.067+1.988 x 10(2)X0Av +9 1.907 BIC3 + 6.853 CIC1 in the training set. External validation processes to assess the robustness and predictive power of the obtained model were carried out. This external prediction set had an accuracy of 99.44%. After that, the developed models were used in ligand-based virtual screening of tyrosinase inhibitors from the literature and never considered in either training or predicting series. In this case, all screened chemicals were correctly classified by the LDA-based QSAR models. As a final point, these fitted models were used in the screening of new bipiperidine series as new tyrosinase inhibitors. These methods are an adequate alternative to the process of selection/identification of new bioactive compounds. The biosilico assays and in vitro results of inhibitory activity on mushroom tyrosinase showed good correspondence. It is important to stand out that compound BP4 (IC(50)=1.72 microM) showed higher activity in the inhibition against the enzyme than reference compound kojic acid (IC(50)=16.67 microM) and l-mimosine (IC(50)=3.68 microM). These results support the role of biosilico algorithm for the identification of new tyrosinase inhibitor compounds.

Bond-based 2D TOMOCOMD-CARDD approach for drug discovery: aiding decision-making in 'in silico' selection of new lead tyrosinase inhibitors.

In this paper, we present a new set of bond-level TOMOCOMD-CARDD molecular descriptors (MDs), the bond-based bilinear indices, based on a bilinear map similar to those defined in linear algebra. These novel MDs are used here in Quantitative Structure-Activity Relationship (QSAR) studies of tyrosinase inhibitors, for finding functions that discriminate between the tyrosinase inhibitor compounds and inactive ones. In total 14 models were obtained and the best two discriminant functions (Eqs. 32 and 33) shown globally good classification of 91.00% and 90.17%, respectively, in the training set. The test set had accuracies of 93.33% and 88.89% for the models 32 and 33, correspondingly. A simulated virtual screening was also carried out to prove the quality of the determined models. In a final step, the fitted models were used in the biosilico identification of new synthesized tetraketones, where a good agreement could be observed between the theoretical and experimental results. Four compounds of the novel bioactive chemicals discovered as tyrosinase inhibitors: TK10 (IC(50) = 2.09 microM), TK11 (IC(50) = 2.61 microM), TK21 (IC(50) = 2.06 microM), TK23 (IC(50) = 3.19 microM), showed more potent activity than L-mimose (IC(50) = 3.68 microM). Besides, for this study a heterogeneous database of tyrosinase inhibitors was collected, and could be a useful tool for the scientist in the domain of tyrosinase enzyme researches. The current report could help to shed some clues in the identification of new chemicals that inhibits enzyme tyrosinase, for entering in the pipeline of drug discovery development.

Prediction of tyrosinase inhibition activity using atom-based bilinear indices.

A set of novel atom-based molecular fingerprints is proposed based on a bilinear map similar to that defined in linear algebra. These molecular descriptors (MDs) are proposed as a new means of molecular parametrization easily calculated from 2D molecular information. The nonstochastic and stochastic molecular indices match molecular structure provided by molecular topology by using the kth nonstochastic and stochastic graph-theoretical electronic-density matrices, M(k) and S(k), respectively. Thus, the kth nonstochastic and stochastic bilinear indices are calculated using M(k) and S(k) as matrix operators of bilinear transformations. Chemical information is coded by using different pair combinations of atomic weightings (mass, polarizability, vdW volume, and electronegativity). The results of QSAR studies of tyrosinase inhibitors using the new MDs and linear discriminant analysis (LDA) demonstrate the ability of the bilinear indices in testing biological properties. A database of 246 structurally diverse tyrosinase inhibitors was assembled. An inactive set of 412 drugs with other clinical uses was used; both active and inactive sets were processed by hierarchical and partitional cluster analyses to design training and predicting sets. Twelve LDA-based QSAR models were obtained, the first six using the nonstochastic total and local bilinear indices and the last six with the stochastic MDs. The discriminant models were applied; globally good classifications of 99.58 and 89.96 % were observed for the best nonstochastic and stochastic bilinear indices models in the training set along with high Matthews correlation coefficients (C) of 0.99 and 0.79, respectively, in the learning set. External prediction sets used to validate the models obtained were correctly classified, with accuracies of 100 and 87.78 %, respectively, yielding C values of 1.00 and 0.73. This subset contains 180 active and inactive compounds not considered to fit the models. A simulated virtual screen demonstrated this approach in searching tyrosinase inhibitors from compounds never considered in either training or predicting series. These fitted models permitted the selection of new cycloartane compounds isolated from herbal plants as new tyrosinase inhibitors. A good correspondence between theoretical and experimental inhibitory effects on tyrosinase was observed; compound CA6 (IC(50)=1.32 microM) showed higher activity than the reference compounds kojic acid (IC(50)=16.67 microM) and L-mimosine (IC(50)=3.68 microM).

TOMOCOMD-CARDD descriptors-based virtual screening of tyrosinase inhibitors: evaluation of different classification model combinations using bond-based linear indices.

A new set of bond-level molecular descriptors (bond-based linear indices) are used here in QSAR (quantitative structure-activity relationship) studies of tyrosinase inhibitors, for finding functions that discriminate between the tyrosinase inhibitor compounds and inactive ones. A database of 246 compounds was collected for this study; all organic chemicals were reported as tyrosinase inhibitors; they had great structural diversity. This dataset can be considered as a helpful tool, not only for theoretical chemists but also for other researchers in this area. The set used as inactive has 412 drugs with other clinical uses. Twelve LDA-based QSAR models were obtained, the first six using the non-stochastic total and local bond-based linear indices as well as the last six ones, the stochastic molecular descriptors. The best two discriminant models computed using the non-stochastic and stochastic molecular descriptors (Eqs. , respectively) had globally good classifications of 98.95% and 89.75% in the training set, with high Matthews correlation coefficients (C) of 0.98 and 0.78. The external prediction sets had accuracies of 98.89% and 89.44%, and (C) values of 0.98 and 0.78, for models 7 and 13, respectively. A virtual screening of compounds reported in the literature with such activity was carried out, to prove the ability of present models to search for tyrosinase inhibitors, not included in the training or test set. At the end, the fitted discriminant functions were used in the selection/identification of new ethylsteroids isolated from herbal plants, looking for tyrosinase inhibitory activity. A good behavior is shown between the theoretical and experimental results on mushroom tyrosinase enzyme. It might be highlighted that all the compounds showed values under 10microM and that ES2 (IC(50)=1.25microM) showed higher activity in the inhibition against the enzyme than reference compounds kojic acid (IC(50)=16.67microM) and l-mimosine (IC(50)=3.68microM). In addition, a comparison with other established methods was carried to prove the adequate discriminatory performance of the molecular descriptors used here. The present algorithm provided useful clues that can be used to speed up in the identification of new tyrosinase inhibitor compounds.

Tyrosinase inhibitory cycloartane type triterpenoids from the methanol extract of the whole plant of Amberboa ramosa Jafri and their structure-activity relationship.

New tyrosinase inhibitory cycloartane triterpenoids have been discovered from the methanol extract of the whole plant of Amberboa ramosa (Roxb.) Jafri, which is a member from the Compositae family. Utilizing the conventional spectroscopic techniques, including 1D and 2D NMR analysis, and also by comparing the experimental with literature data, the isolated compounds proved to be cycloartane type triterpenoids. These cycloartanes are: (22R)-cycloart-20, 25-dien-2alpha3beta22alpha triol (1), (22R)-cycloart-23-ene-3beta, 22alpha, 25-triol (2), cycloartenol (3), cycloart-23-ene-3beta, 25-diol (4), cycloart-20-ene-3beta, 25-diol (5), cycloart-25-ene-3beta, (22R) 22-diol (6), 3beta, 21, 22, 23-tetrahydroxy-cycloart-24 (31), 25 (26)-diene (7), and (23R)-5alpha-cycloart-24-ene-3beta, 21, 23-triol (8). Out of these eight compounds, compound 3 did not show any activity against the enzyme tyrosinase. Among them compound 7 was found to be the most potent (1.32 microM) when compared with the standard tyrosinase inhibitors kojic acid (16.67 microM) and L-mimosine (3.68 microM). Finally in this paper, we have discussed the structure-activity relationships of these molecules.

New tyrosinase inhibitors selected by atomic linear indices-based classification models.

In the present report, the use of the atom-based linear indices for finding functions that discriminate between the tyrosinase inhibitor compounds and inactive ones is presented. In this sense, discriminant models were applied and globally good classifications of 93.51% and 92.46% were observed for non-stochastic and stochastic linear indices best models, respectively, in the training set. The external prediction sets had accuracies of 91.67% and 89.44%. In addition, these fitted models were used in the screening of new cycloartane compounds isolated from herbal plants. A good behavior is shown between the theoretical and experimental results. These results provide a tool that can be used in the identification of new tyrosinase inhibitor compounds.

Expression of estrogen receptor alpha gene in breast cancer cells treated with transcription factor decoy is modulated by Bangladeshi natural plant extracts.

The aim of the present study was to determine whether the expression of the estrogen receptor alpha (ERalpha) gene may be a possible target for compounds present in plant extracts from Aegle marmelos and Emblica officinalis, used in traditional Asian medicine in the treatment of tissue inflammation and cancer. To this aim, we evaluated the potential of the selected plant extracts to affect proliferation and differentiation of ERalpha-negative MDA-MB-231 breast cancer cells, which become ERalpha positive after treatment with a decoy molecule against a regulatory region of the human ERalpha gene. All the plant extracts inhibited cell proliferation and showed no effect on ERalpha gene expression, but when they were added in combination with the decoy molecule, a modulatory effect was observed, depending on the extract employed. The extracts exhibiting the greatest effects were those obtained from Aegle marmelos. Gas-chromatography/mass-spectrometry (GC/ MS) analysis enabled us to identify lupeol, a known triterpenoid, as the major bioactive component of A. marmelos plant extracts. Similar to the Aegle marmelos extracts, lupeol was found to stimulate the decoy effect of RA4 DNA sequence, increasing at a high level ERa gene expression in MDA-MB-231 ERalpha-negative breast cancer cells, and also inhibited cell proliferation.

Extracts and molecules from medicinal plants against herpes simplex viruses.

Herpes simplex viruses (HSV-1 and -2) are important pathogens for humans, especially in the case of highly susceptible adults. Moreover, HSV-2 has been reported to be a high risk factor for HIV infection. Therefore, the discovery of novel anti-HSV drugs deserves great efforts. In this paper, we review anti-HSV substances from natural sources, including both extracts and pure compounds from herbal medicines, reported in studies from several laboratories. The role of traditional medicine for the development of anti-HSV compounds is also discussed. Interestingly, it was found that traditional medicines, like Ayurvedic, traditional Chinese (TCM), Chakma medicines, are good and potential sources for promising anti-HSV drugs. A second objective of this review is to discuss several anti-HSV compounds with respect to their structure-activity relationship (SAR). A large number of small molecules, like phenolics, polyphenols, terpenes (e.g., mono-, di-, tri-), flavonoids, sugar-containing compounds, were found to be promising anti-herpetic agents. Our major conclusion is that natural products from medicinal plant extracts are very important source of anti-HSV agents.

Effects of vanadium complexes on cell growth of human leukemia cells and protein-DNA interactions.

Vanadium complexes are known to possess potent insulin-mimetic effects, high affinity for several enzymes and anticancer activity, which deserve increasing attention for application to biomedical sciences. Different vanadium complexes have been found to be more effective than the simple vanadium-(IV) and -(V) salts in experiments performed both in vitro and in vivo. Application of polyoxometalates as potential drugs against Herpes Simplex Virus and AIDS have also increased the interest to study the association between vanadium containing species and proteins. The aim of our research was to investigate the in vitro antiproliferative activity of a variety of vanadium-containing compounds, and study their ability to interfere with the molecular interactions between GATA-1 and NF-kappaB transcription factors and target DNA elements, employing electrophoretic mobility shift assays. All of the used vanadium compounds were found to exhibit antiproliferative activity, despite with differences in efficacy. Inhibition of K562 cell growth was not associated with differentiation, but with activation of apoptosis. Vanadium complexes with a +5 oxidation state and their discrete anionic units appear essential for the respective effects on K562 cells; a +4 oxidation state appears to be important in inhibiting transcription factors/DNA interactions.

Studies of the anticancer potential of plants used in Bangladeshi folk medicine.

The present study evaluated the anticancer potential of 11 plants used in Bangladeshi folk medicine. The extracts were tested for cytotoxicity using the brine shrimp lethality assay, sea urchin eggs assay, hemolysis assay and MTT assay using tumor cell lines. The extract of Oroxylum indicum showed the highest toxicity on all tumor cell lines tested, with an IC(50) of 19.6 microg/ml for CEM, 14.2 microg/ml for HL-60, 17.2 microg/ml for B-16 and 32.5 microg/ml for HCT-8. On the sea urchin eggs, it inhibited the progression of cell cycle since the frist cleavage (IC(50)=13.5 microg/ml). The extract of Aegle marmelos exhibited toxicity on all used assays, but in a lower potency than Oroxylum indicum. In conclusion, among all tested extracts, only the extracts of Oroxylum indicum, Moringa oleifera and Aegles marmelos could be considered as potential sources of anticancer compounds. Further studies are necessary for chemical characterization of the active principles and more extensive biological evaluations.