Eugenio Uriarte

Simple coumarins and analogues in medicinal chemistry: occurrence, synthesis and biological activity.

Coumarins, also known as benzopyrones, are present in remarkable amounts in plants, although their presence has also been detected in microorganisms and animal sources. The structural diversity found in this family of compounds led to the division into different categories, from simple coumarins to many other kinds of policyclic coumarins, such as furocoumarins and pyranocoumarins. Simple coumarins and analogues are a large class of compounds that have attracted their interest for a long time due to their biological activities: they have shown to be useful as antitumoural, anti-HIV agents and as CNS-active compounds. Furthermore, they have been reported to have multiple biological activities (anticoagulant, anti-inflammatory), although all these properties have not been evaluated systematically. In addition, their enzyme inhibition properties, antimicrobial and antioxidant activities are other foremost topics of this field of research. The present work is to survey the information published or abstracted from 1990 till 2003, which is mainly related to the occurrence, synthesis and biological importance of simple coumarins and some analogues, such as biscoumarins and triscoumarins. Data are also highlighted, concerning the development of new synthetic strategies that could help in drug design and in the work on SAR or QSAR.

Recent advances on the role of topological indices in drug discovery research

The role of topological indices in drug development research is updated. A series of definitions in the fields of topological indices and drug discovery technologies are introduced. In all cases where it is possible the IUPAC recommendations for terms used in medicinal chemistry and in computational drug design are used. Recent advances on the use of topological indices in the lead discovery process are reviewed making emphasis on two approaches: combined use of connectivity and charge indices and TOSS-MODE approach. Studies of similarity/dissimilarity and rational combinatorial library design are also updated. The use of these descriptors in lead optimization process is critically analyzed. Topological indices QSAR, the problem of 2D QSAR versus 3D QSAR, strategies of orthogonalization and the use of linear combination and semiempirical connectivity indices are also described. The main directions of progress for these indices in QSAR and drug research are analyzed with examples of application of novel statistical techniques, such as artificial neural networks, genetic algorithms and partial least squares. Future outlooks of development in this area of research are also given.

Proteomics, networks and connectivity indices

Describing the connectivity of chemical and/or biological systems using networks is a straight gate for the introduction of mathematical tools in proteomics. Networks, in some cases even very large ones, are simple objects that are composed at least by nodes and edges. The nodes represent the parts of the system and the edges geometric and/or functional relationships between parts. In proteomics, amino acids, proteins, electrophoresis spots, polypeptidic fragments, or more complex objects can play the role of nodes. All of these networks can be numerically described using the so‐called Connectivity Indices (CIs). The transformation of graphs (a picture) into CIs (numbers) facilitates the manipulation of information and the search for structure‐function relationships in Proteomics. In this work, we review and comment on the challenges and new trends in the definition and applications of CIs in Proteomics. Emphasis is placed on 1‐D‐CIs for DNA and protein sequences, 2‐D‐CIs for RNA secondary structures, 3‐D‐topographic indices (TPGIs) for protein function annotation without alignment, 2‐D‐CIs and 3‐D‐TPGIs for the study of drug‐protein or drug‐RNA quantitative structure‐binding relationships, and pseudo 3‐D‐CIs for protein surface molecular recognition. We also focus on CIs to describe Protein Interaction Networks or RNA co‐expression networks. 2‐D‐CIs for patient blood proteome 2‐DE maps or mass spectra are also covered.

Chromone: a valid scaffold in Medicinal Chemistry

This work was supported by the Foundation for Science and Technology (FCT), Portugal (projects PTDC/QUI-QUI/113687/2009 and PEst-C/QUI/UI0081/2013). A.G. (SFRH/BD/43531/2008) and M.J.M. (SFRH/BD/61262/2009) thank FCT for grants.

Effects of cis-resveratrol on inflammatory murine macrophages: antioxidant activity and down-regulation of inflammatory genes.

This study investigated for the first time the effects of the cis isomer of resveratrol (c‐RESV) on the responses of inflammatory murine peritoneal macrophages, namely on the production of reactive oxygen species (ROS) and reactive nitrogen species (RNS) during the respiratory burst; on the biosynthesis of other mediators of inflammation such prostaglandins; and on the expression of inflammatory genes such as inducible nitric oxide synthase (NOS)‐2 and inducible cyclooxygenase (COX)‐2. Treatment with 1–100 μM c‐RESV significantly inhibited intracellular and extracellular ROS production, and c‐RESV at 10–100 μM significantly reduced RNS production. c‐RESV at 1–100 μM was ineffective for scavenging superoxide radicals (O2•−), generated enzymatically by a hypoxanthine (HX)/xanthine oxidase (XO) system and/or for inhibiting XO activity. However, c‐RESV at 10–100 μM decreased nicotinamide adenine dinucleotide/nicotinamide adenine dinucleotide phosphate (NADH/NADPH) oxidase activity in macrophage homogenates. c‐RESV at 100 μM decreased NOS‐2 and COX‐2 mRNA levels in lipopolysaccharide (LPS) interferon gamma (IFN‐γ)‐treated macrophages. At 10–100 μM, c‐RESV also significantly inhibited NOS‐2 and COX‐2 protein synthesis and decreased prostaglandin E2 (PGE2) production. These results indicate that c‐RESV at micromolar concentrations significantly attenuates several components of the macrophage response to proinflammatory stimuli (notably, production of O2•− and of the proinflammatory mediators NO• and PGE2).

Synthesis and study of a series of 3-arylcoumarins as potent and selective monoamine oxidase B inhibitors.

New series of 6-substituted-3-arylcoumarins displaying several alkyl, hydroxyl, halogen, and alkoxy groups in the two benzene rings have been designed, synthesized, and evaluated in vitro as human monoamine oxidase A and B (hMAO-A and hMAO-B) inhibitors. Most of the studied compounds showed a high affinity and selectivity to the hMAO-B isoenzyme, with IC(50) values on nanomolar and picomolar range. Ten of the 22 described compounds displayed higher MAO-B inhibitory activity and selectivity than selegiline. Coumarin 7 is the most active compound of this series, being 64 times more active than selegiline and also showing the highest hMAO-B specificity. In addition, docking experiments were carried out on hMAO-A and h-MAO-B structures. This study provided new information about the enzyme-inhibitor interaction and the potential therapeutic application of this 3-arylcoumarin scaffold.

A new series of 3-phenylcoumarins as potent and selective MAO-B inhibitors

6-Methyl-3-phenylcoumarins 3-6 were designed, synthesized and evaluated as monoamine oxidase A and B (MAO-A and MAO-B) inhibitors. The synthesis of these new compounds (resveratrol-coumarin hybrids) was carried out with good yield by a Perkin reaction, from the 5-methylsalicylaldehyde and the corresponding phenylacetic acid. They show high selectivity to the MAO-B isoenzyme, with IC(50) values in the nanomolar range. Compound 5 is the most active compound and is several times more potent and selective than the reference compound, R-(-)-deprenyl.

Coumarin as attractive casein kinase 2 (CK2) inhibitor scaffold: an integrate approach to elucidate the putative binding motif and explain structure-activity relationships.

Casein kinase 2 (CK2) is an ubiquitous, essential, and highly pleiotropic protein kinase whose abnormally high constitutive activity is suspected to underlie its pathogenic potential in neoplasia and other diseases. Recently, using different virtual screening approaches, we have identified several novel CK2 inhibitors. In particular, we have discovered that coumarin moiety can be considered an attractive CK2 inhibitor scaffold. In the present work, we have synthetized and tested a small library of coumarins (more than 60), rationalizing the observed structure-activity relationship. Moreover, the most promising inhibitor, 3,8-dibromo-7-hydroxy-4-methylchromen-2-one (DBC), has been also crystallized in complex with CK2, and the experimental binding mode has been used to derive a linear interaction energy (LIE) model.

Novel 2D maps and coupling numbers for protein sequences. The first QSAR study of polygalacturonases; isolation and prediction of a novel sequence from Psidium guajava L.

The development of 2D graph‐theoretic representations for DNA sequences was very important for qualitative and quantitative comparison of sequences. Calculation of numeric features for these representations is useful for DNA–QSAR studies. Most of all graph‐theoretic representations identify each one of the four bases with a unitary walk in one axe direction in the 2D space. In the case of proteins, twenty amino acids instead of four bases have to be considered. This fact has limited the introduction of useful 2D Cartesian representations and the corresponding sequences descriptors to encode protein sequence information. In this study, we overcome this problem grouping amino acids into four groups: acid, basic, polar and non‐polar amino acids. The identification of each group with one of the four axis directions determines a novel 2D representation and numeric descriptors for proteins sequences. Afterwards, a Markov model has been used to calculate new numeric descriptors of the protein sequence. These descriptors are called herein the sequence 2D coupling numbers (ζ k ). In this work, we calculated the ζ k values for 108 sequences of different polygalacturonases (PGs) and for 100 sequences of other proteins. A Linear Discriminant Analysis model derived here (PG = 5.36 · ζ 1 − 3.98 · ζ 3 − 42.21) successfully discriminates between PGs and other proteins. The model correctly classified 100% of a subset of 81 PGs and 75 non‐PG proteins sequences used to train the model. The model also correctly classified 51 out of 52 (98.07%) of proteins sequences used as external validation series. The uses of different group of amino acids and/or axes orientation give different results, so it is suggested to be explored for other databases. Finally, to illustrates the use of the model we report the isolation and prediction of the PG action for a novel sequence (AY908988) isolated by our group from Psidium guajava L. This prediction coincides very well with sequence alignment results found by the BLAST methodology. These findings illustrate the possibilities of the sequence descriptors derived for this novel 2D sequence representation in proteins sequence QSAR studies.

Quantitative structure-activity relationship and complex network approach to monoamine oxidase A and B inhibitors.

The work provides a new model for the prediction of the MAO-A and -B inhibitor activity by the use of combined complex networks and QSAR methodologies. On the basis of the obtained model, we prepared and assayed 33 coumarin derivatives, and the theoretical prediction was compared with the experimental activity data. The model correctly predicted 27 compounds, and most of the active derivatives showed IC 50 values in the muM-nM range against both the MAO-A and MAO-B isoforms. Compound 14 shows the same MAO-A inhibitory activity (IC 50 = 7.2 nM), as clorgyline used as a reference inhibitor and has the highest MAO-A specificity (1000-fold higher compared to MAO-B). On the other hand, compounds 24 (IC 50 = 1.2 nM) and 28 (IC 50 = 1.5 nM) show higher activity than selegiline (IC 50 = 19.6 nM) and high MAO-B selectivity with 100-fold and 1600-fold inhibition levels, with respect to the MAO-A isoform.