Luciana Scotti

Synthesis, Structure-Activity Relationships (SAR) and in Silico Studies of Coumarin Derivatives with Antifungal Activity

The increased incidence of opportunistic fungal infections, associated with greater resistance to the antifungal drugs currently in use has highlighted the need for new solutions. In this study twenty four coumarin derivatives were screened in vitro for antifungal activity against strains of Aspergillus. Some of the compounds exhibited significant antifungal activity with MICs values ranging between 16 and 32 μg/mL. The structure-activity relationships (SAR) study demonstrated that O-substitutions are essential for antifungal activity. It also showed that the presence of a short aliphatic chain and/or electron withdrawing groups (NO2 and/or acetate) favor activity. These findings were confirmed using density functional theory (DFT), when calculating the LUMO density. In Principal Component Analysis (PCA), two significant principal components (PCs) explained more than 60% of the total variance. The best Partial Least Squares Regression (PLS) model showed an r2 of 0.86 and q2cv of 0.64 corroborating the SAR observations as well as demonstrating a greater probe N1 interaction for active compounds. Descriptors generated by TIP correlogram demonstrated the importance of the molecular shape for antifungal activity.

Self-organizing maps of molecular descriptors for sesquiterpene lactones and their application to the chemotaxonomy of the Asteraceae family.

The Asteraceae, one of the largest families among angiosperms, is chemically characterised by the production of sesquiterpene lactones (SLs). A total of 1,111 SLs, which were extracted from 658 species, 161 genera, 63 subtribes and 15 tribes of Asteraceae, were represented and registered in two dimensions in the SISTEMATX, an in-house software system, and were associated with their botanical sources. The respective 11 block of descriptors: Constitutional, Functional groups, BCUT, Atom-centred, 2D autocorrelations, Topological, Geometrical, RDF, 3D-MoRSE, GETAWAY and WHIM were used as input data to separate the botanical occurrences through self-organising maps. Maps that were generated with each descriptor divided the Asteraceae tribes, with total index values between 66.7% and 83.6%. The analysis of the results shows evident similarities among the Heliantheae, Helenieae and Eupatorieae tribes as well as between the Anthemideae and Inuleae tribes. Those observations are in agreement with systematic classifications that were proposed by Bremer, which use mainly morphological and molecular data, therefore chemical markers partially corroborate with these classifications. The results demonstrate that the atom-centred and RDF descriptors can be used as a tool for taxonomic classification in low hierarchical levels, such as tribes. Descriptors obtained through fragments or by the two-dimensional representation of the SL structures were sufficient to obtain significant results, and better results were not achieved by using descriptors derived from three-dimensional representations of SLs. Such models based on physico-chemical properties can project new design SLs, similar structures from literature or even unreported structures in two-dimensional chemical space. Therefore, the generated SOMs can predict the most probable tribe where a biologically active molecule can be found according Bremer classification.

Chemometric Studies on Natural Products as Potential Inhibitors of the NADH Oxidase from Trypanosoma cruzi Using the VolSurf Approach

Natural products have widespread biological activities, including inhibition of mitochondrial enzyme systems. Some of these activities, for example cytotoxicity, may be the result of alteration of cellular bioenergetics. Based on previous computer-aided drug design (CADD) studies and considering reported data on structure-activity relationships (SAR), an assumption regarding the mechanism of action of natural products against parasitic infections involves the NADH-oxidase inhibition. In this study, chemometric tools, such as: Principal Component Analysis (PCA), Consensus PCA (CPCA), and partial least squares regression (PLS), were applied to a set of forty natural compounds, acting as NADH-oxidase inhibitors. The calculations were performed using the VolSurf+ program. The formalisms employed generated good exploratory and predictive results. The independent variables or descriptors having a hydrophobic profile were strongly correlated to the biological data.

Experimental Methodologies and Evaluations of Computer-Aided Drug Design Methodologies Applied to a Series of 2-Aminothiophene Derivatives with Antifungal Activities

Fifty 2-[(arylidene)amino]-4,5-cycloalkyl[b]thiophene-3-carbonitrile derivatives were screened for their in vitro antifungal activities against Candida krusei and Cryptococcus neoformans. Based on experimentally determined minimum inhibitory concentration (MIC) values, we conducted computer-aided drug design studies [molecular modelling, chemometric tools (CPCA, PCA, PLS) and QSAR-3D] that enable the prediction of three-dimensional structural characteristics that influence the antifungal activities of these derivatives. These predictions provide direction with regard to the syntheses of new derivatives with improved biological activities, which can be used as therapeutic alternatives for the treatment of fungal infections.

Modelagem molecular aplicada ao desenvolvimento de moléculas com atividade antioxidante visando ao uso cosmético

Varias hipoteses e constantes estudos sao realizados com o intuito de elucidar o envelhecimento cutâneo. Para prevenir e contornar este processo torna-se necessario reforcar nossas defesas naturais antioxidantes endogenas. Diversas substâncias antioxidantes exogenas, como vitaminas, extratos vegetais, dentre outras, sao utilizadas pela Cosmetologia nos produtos antienvelhecimento. O objetivo deste artigo e apresentar de que forma a Modelagem Molecular pode ser uma ferramenta util na pesquisa por novas substâncias cosmeticas antioxidantes para combater o envelhecimento cutâneo.

Computer-Aided Drug Design Using Sesquiterpene Lactones as Sources of New Structures with Potential Activity against Infectious Neglected Diseases

This review presents an survey to the biological importance of sesquiterpene lactones (SLs) in the fight against four infectious neglected tropical diseases (NTDs)—leishmaniasis, schistosomiasis, Chagas disease, and sleeping sickness—as alternatives to the current chemotherapies that display several problems such as low effectiveness, resistance, and high toxicity. Several studies have demonstrated the great potential of some SLs as therapeutic agents for these NTDs and the relationship between the protozoal activities with their chemical structure. Recently, Computer-Aided Drug Design (CADD) studies have helped increase the knowledge of SLs regarding their mechanisms, the discovery of new lead molecules, the identification of pharmacophore groups and increase the biological activity by employing in silico tools such as molecular docking, virtual screening and Quantitative-Structure Activity Relationship (QSAR) studies.

Chemometric studies on potential larvicidal compounds against Aedes aegypti.

The mosquito Aedes aegypti (Diptera, Culicidae) is the vector of yellow and dengue fever. In this study, chemometric tools, such as, Principal Component Analysis (PCA), Consensus PCA (CPCA), and Partial Least Squares Regression (PLS), were applied to a set of fifty five active compounds against Ae. aegypti larvae, which includes terpenes, cyclic alcohols, phenolic compounds, and their synthetic derivatives. The calculations were performed using the VolSurf+ program. CPCA analysis suggests that the higher weight blocks of descriptors were SIZE/SHAPE, DRY, and H2O. The PCA was generated with 48 descriptors selected from the previous blocks. The scores plot showed good separation between more and less potent compounds. The first two PCs accounted for over 60% of the data variance. The best model obtained in PLS, after validation leave-one-out, exhibited q(2) = 0.679 and r(2) = 0.714. External prediction model was R(2) = 0.623. The independent variables having a hydrophobic profile were strongly correlated to the biological data. The interaction maps generated with the GRID force field showed that the most active compounds exhibit more interaction with the DRY probe.

Hybrid Compounds as Direct Multitarget Ligands: A Review

Molecular Hybridization is an approach in rational drug design where new chemical entities are obtained by combining two or more pharmacophoric units from different bioactive compounds into a single molecule. Through this approach, medicinal chemists hope that the new hybrid derivative presents: better affinity and efficacy when compared to the parent drugs; a modified selectivity profile with improvement over pharmacokinetic and pharmacodynamic restrictions; dual or multiple modes of action; reduction of undesirable side effects; decreases in drug-drug interactions; reduced emergence or spread of drug resistance in microorganisms and protozoans; and lower cost. The approach has been successfully used by many research groups around the world and has had very promising results with diseases having multifactorial profiles, like Alzheimer´s, Parkinson´s disease, cancer, inflammation, and hypertension among others. The purpose of this paper is to conduct an updated review of molecular hybridization and multitarget profiling (a rational drug design approach), and its applications to the design and discovery of novel hybrid compounds with anti-inflammatory, antimicrobial, anticancer and antiprotozoal (leishmaniasis, malaria, and schistosomiasis) activities over the last six years.

Comparative computational studies of 3,4-dihydro-2,6-diaryl-4-oxo-pyrimidine-5-carbonitrile derivatives as potential antinociceptive agents.

In this study, the antinociceptive properties of 3,4-dihydro-2,6-diaryl-4-oxo-pyrimidine-5-carbonitrile derivatives 5a–i at doses of 25 and 50 mg/kg were evaluated in mice, using the abdominal constriction test. Molecular modeling studies were also performed using density functional theory calculations. These data provided information about the electrostatic and ionization potentials and were used to compare the antinociceptive activity of the title compounds. The most active compounds were 3,4-dihydro-2-(4-chlorophenyl)-6-(4-methoxyphenyl)-4-oxo-pyrimidine-5-carbonitrile (5b) and 3,4-dihydro-2,6-diphenyl-4-oxo-pyrimidine-5-carbonitrile (5i), which inhibited the number of abdominal constrictions, at 50 mg/kg dose, in 88.6% and 88% of the sample, respectively. A preliminary SAR study demonstrated that halogen replacement in the phenyl rings of the compounds under study reduces the antinociceptive activity. DFT calculations showed that there is a high correlation between the ionization potentials and the analgesic properties of the compounds. It was found that compounds with a positive ionization potential (compounds 5b and 5i) were found to be the best analgesic drugs in this series.

Docking and PLS Studies on a Set of Thiophenes RNA Polymerase Inhibitors Against Staphylococcus aureus

Staphylococcus aureus lives in commensalism with the majority of the population, being recognized as an important pathogen in patients with chronic liver diseases and can cause a deadly infection. The use of antibiotics as rifampin for the chemotherapy of infections caused by S. aureus has resulted in the selection of mutants with resistance. In an attempt to combat resistant strains new research is continuously conducted, as example searching new biological targets or new inhibitors such as tiophenes derivatives that can inhibit the RNA polymerase enzyme. This work investigated the set of tiophenes, selected from of literature and with RNA polymerase enzyme inhibitory activity of S. aureus. After seeking further information on existing scientific literature, the compounds under study were applied the methodologies of PLS, docking and calculation of Molecular Interaction Fields (MIFs) using Pentacle and VolSurf programmes. In addition, a comparison was made with two tiophenes synthesized in our laboratory and which have been tested against the bacteria. Docking studies showed that active compounds had more interactions with the amino acids on active site when compared with rifampicin. The best model obtained in PLS, considering two LVs (latent variables), after leave-one-outvalidation, exhibited the statistical parameters qcv(2) = 0.68 and r(2) = 0.85. External prediction model presented a rext(2) = 0.67. The obtained model through PLS analyses was able to predict the behavior of compounds synthesized by us. So we extract structural features important for the activity of these compounds. In this paper, first we discussed the topics: S. aureus, tiophenes, RNA polymerase, docking and QSAR methodologies. Then we have selected a series of 56 tiophenes from literature, which have their biological activity tested against the RNA polymerase enzyme of S. aureus. The compounds were subsequently carried out for Partial Least Squares (PLS) Analysis.