M. Concepción Lozada

1) H and (13) C NMR characterization of new cycloartane triterpenes from Mangifera indica.

From the stem bark of Mangifera indica, seven cycloartane‐type secondary metabolites were isolated. Compound 1 has been isolated for the first time from M. indica, whereas compounds 2 (2a and 2b, as an epimeric mixture), 3, and 4 are new triterpenoid‐type cycloartanes. Unambiguous 13C and 1H NMR assignments for these compounds and the known compounds mangiferonic acid (compound 5), isomangiferolic acid (compound 6), ambolic acid (compound 7), and friedelin (compound 8) are reported; the latter because full NMR data for these compounds are not available in the literature. Copyright

CASE plots for the chemotype-based activity and selectivity analysis: a CASE study of cyclooxygenase inhibitors.

Structure–activity characterization of molecular databases plays a central role in drug discovery. However, the characterization of large databases containing structurally diverse molecules with several end‐points represents a major challenge. For this purpose, the use of chemoinformatic methods plays an important role to elucidate structure–activity relationships. Herein, a general methodology, namely Chemotype Activity and Selectivity Enrichment plots, is presented. Chemotype Activity and Selectivity Enrichment plots provide graphical information concerning the activity and selectivity patterns of particular chemotypes contained in structurally diverse databases. As a case study, we analyzed a set of 658 compounds screened against cyclooxygenase‐1 and cyclooxygenase‐2. Chemotype Activity and Selectivity Enrichment plots analysis highlighted chemotypes enriched with active and selective molecules against cyclooxygenase‐2; all this in a simple 2D graphical representation. Additionally, the most active and selective chemotypes detected in Chemotype Activity and Selectivity Enrichment plots were analyzed separately using the previously reported dual activity–difference maps. These findings indicate that Chemotype Activity and Selectivity Enrichment plots and dual activity–difference maps are complementary chemoinformatic tools to explore the structure–activity relationships of structurally diverse databases screened against two biological end‐points.

Synthesis, cytotoxic and antioxidant evaluations of amino derivatives from perezone

A series of eight amino derivatives (3a-h) from perezone 1 were prepared by nucleophilic addition of bioactive amines v.gr. melatonin, acetyl tryptamine, tryptophan and other amino acids esters (valine, leucine and methionine). Their structures were elucidated by spectroscopy data. The cytotoxic evaluation against four human tumor cell lines PC-3, K-562, HCT-15 and SKLU-1 was performed as well as the TBARS assay for antioxidant activity. The results suggest that 1 and its isomer 4 were highly active against all cell lines, 4 was twice as potent than 1 against PC-3 and HCT-15. The derivative 3a (IC(50)=7.5 ± 0.3 μM) was more active than 1 against HCT-15 whereas 3h was selective against K-562 with IC(50)=4.5 ± 0.4 μM. The TBARS assay has shown that 3c with IC(50)=5.564 ± 0.24 μM is a potent antioxidant with superior effect comparing to α-tocopherol and moreover was more active than the precursor molecule 1.

Synthesis and Structure of New Heterocyclic Derivatives of Curcumin

New heterocyclic derivatives of curcumin (3) of different ring size were synthesized by reaction of a key intermediate, 1,7-bis(4-acetoxy-3-methoxyphenyl)hepta-3,5-dione (5) with some bi-nucleophilic molecules. These new synthetic derivatives were obtained in good yields and the structure of all compounds was supported by MS, IR, ID and 2D 1 H and 1 3 C NMR spectra and elemental analysis.

Cyclic Systems Distribution Along Similarity Measures: Insights for an Application to Activity Landscape Modeling

The emerging concept of the activity landscape has been widely applied for structureactivity relationships (SAR) characterization. Since chemical space representation plays a crucial role in activity landscape modeling, an adequate selection of similarity measures is desirable. Herein a set of 658 cyclooxygenase inhibitors were structurally analyzed using 12 molecular similarity representations and two levels of chemotype classification. Then, three uncorrelated similarity measures and mean similarity (obtained with data fusion) were combined with chemotype information using the herein proposed chemotypesimilarity graphs. Chemotype‐similarity graphs showed the cumulative distribution of molecular pairs with the same and different chemotype along similarity values; leading to establish an interpretable, quantitative and activity independent threshold in similarity measures based on chemotype distributions. This approach gave additional information to similarity measures and can be considered as an interpretable criterion to define high and low similar compounds. The results were applied to model the activity landscape using StructureActivity Similarity (SAS)‐like maps. Some examples of pairs in each region of the SAS‐like maps were analyzed which showed valuable SAR information for cyclooxygenase inhibitors.