The development of blowouts and foredunes in the Ilha Comprida barrier (Southeastern Brazil): the influence of Late Holocene climate changes on coastal sedimentation

Middle to Late Holocene barriers are conspicuous landforms in southeastern and southern Brazilian regions. The barriers in the coastal zones of northern Santa Catarina, Parana and Sao Paulo states (27 degrees 19`-24 degrees 00`S) are formed mainly by beach ridge alignments and many barriers present foredune and blowout alignments in their seaward portion. The development of these eolian landforms appears to record a regional shift in coastal dynamics and barrier building. In this context, the Ilha Comprida barrier stands out for its well-developed and well-preserved foredunes and blowouts. Based on the presence or not and type of eolian landforms, the Ilha Comprida barrier can be divided seaward into inner, middle and outer units. The inner unit is formed entirely by beach ridges. The middle unit comprises a narrow belt of blowouts (up to 15 m high) aligned alongshore. Blowout lobes pointing NNW are indicative of their generation by southern winds. The outer unit is represented by low (<= 1 m high) active or stabilized foredunes and a small transgressive dunefield (similar to 1 km(2)). Twenty-seven luminescence ages (SAR protocol) obtained for the beach ridges, foredunes, and blowouts of these three units allow definition of a precise chronology of these landforms and calculation of rates of coastal progradation. The inner unit presents ages greater than 1004 +/- 88 years. The blowouts of the middle unit show ages from 575 +/- 47 to 172 +/- 18 years. The ages of the outer unit are less than 108 +/- 10 years. Rates of coastal progradation for the inner and outer units are 0.71-0.82 m/year and 0.86-2.23 m/year, respectively. The main phase of blowout development correlates well with the Little Ice Age (LIA) climatic event. These results indicate that southern winds in subtropical Brazil became increasingly more intense and/or frequent during the LIA. These conditions persist to the present and are responsible for the development of the eolian landforms in the outer unit. Thus, barrier geomorphology can record global climatic events. The sensitivity of barrier systems in subtropical Brazil to Late Holocene climate changes was favored by the relative sea level stillstand during this time. Luminescence dating makes it possible to analyze barrier geomorphology during Late Holocene climate changes operating on timescales of a hundred to thousand years. These results improve our knowledge of barrier building and will help in the evaluation of the impact of future climate changes on coastal settings. (C) 2008 Elsevier Ltd. All rights reserved.

Three-Dimensional Quantitative Structure-Activity Relationship Study of Antitumor 2-Formylpyridine Thiosemicarbazones Derivatives as Inhibitors of Ribonucleotide Reductase

In order to extend previous SAR and QSAR studies, 3D-QSAR analysis has been performed using CoMFA and CoMSIA approaches applied to a set of 39 alpha-(N)-heterocyclic carboxaldehydes thiosemicarbazones with their inhibitory activity values (IC(50)) evaluated against ribonucleotide reductase (RNR) of H.Ep.-2 cells (human epidermoid carcinoma), taken from selected literature. Both rigid and field alignment methods, taking the unsubstituted 2-formylpyridine thiosemicarbazone in its syn conformation as template, have been used to generate multiple predictive CoMFA and CoMSIA models derived from training sets and validated with the corresponding test sets. Acceptable predictive correlation coefficients (Q(cv)(2) from 0.360 to 0.609 for CoMFA and Q(cv)(2) from 0.394 to 0.580 for CoMSIA models) with high fitted correlation coefficients (r` from 0.881 to 0.981 for CoMFA and r(2) from 0.938 to 0.993 for CoMSIA models) and low standard errors (s from 0.135 to 0.383 for CoMFA and s from 0.098 to 0.240 for CoMSIA models) were obtained. More precise CoMFA and CoMSIA models have been derived considering the subset of thiosemicarbazones (TSC) substituted only at 5-position of the pyridine ring (n=22). Reasonable predictive correlation coefficients (Q(cv)(2) from 0.486 to 0.683 for CoMFA and Q(cv)(2) from 0.565 to 0.791 for CoMSIA models) with high fitted correlation coefficients (r(2) from 0.896 to 0.997 for CoMFA and r(2) from 0.991 to 0.998 for CoMSIA models) and very low standard errors (s from 0.040 to 0.179 for CoMFA and s from 0.029 to 0.068 for CoMSIA models) were obtained. The stability of each CoMFA and CoMSIA models was further assessed by performing bootstrapping analysis. For the two sets the generated CoMSIA models showed, in general, better statistics than the corresponding CoMFA models. The analysis of CoMFA and CoMSIA contour maps suggest that a hydrogen bond acceptor near the nitrogen of the pyridine ring can enhance inhibitory activity values. This observation agrees with literature data, which suggests that the nitrogen pyridine lone pairs can complex with the iron ion leading to species that inhibits RNR. The derived CoMFA and CoMSIA models contribute to understand the structural features of this class of TSC as antitumor agents in terms of steric, electrostatic, hydrophobic and hydrogen bond donor and hydrogen bond acceptor fields as well as to the rational design of this key enzyme inhibitors.

A chemometric study of the 5-HT1A receptor affinities presented by arylpiperazine compounds

Arylpiperazine compounds are promising 5-HT1A receptor ligands that can contribute for accelerating the onset of therapeutic effect of selective serotonin reuptake inhibitors. In the present work, the chemometric methods HCA, PCA, KNN, SIMCA and PLS were employed in order to obtain SAR and QSAR models relating the structures of arylpiperazine compounds to their 5-HT1A receptor affinities. A training set of 52 compounds was used to construct the models and the best ones were obtained with nine topological descriptors. The classification and regression models were externally validated by means of predictions for a test set of 14 compounds and have presented good quality, as verified by the correctness of classifications, in the case of pattern recognition studies, and b, the high correlation coefficients (q(2) = 0.76, r(2) = 0.83) and small prediction errors for the PLS regression. Since the results are in good agreement with previous SAR studies, we can suggest that these findings can help in the search for 5-HT1A receptor ligands that are able to improve antidepressant treatment. (c) 2007 Elsevier Masson SAS. All rights reserved.

Structural and Electronic Properties of Dipyridamole and Derivatives

Quantum mechanical calculations at the B3LYP theory level, together with the 6-31G* basis set, were employed to obtain the energy, ionization potential, and polarizabilites for dipyridamole and derivatives, which are compared with their biological activity. Density functional calculations of the spin densities were performed for radical formed by electron abstraction of dipyridamole and derivatives. The unpaired electron remains in dipyridamole is localized on the nitrogen atoms in the substituent positions 1, 3, 5, 7, 11, 12, 13, 14, with participation of the 9 and 10 carbons in the pyrimido-pyrimidine ring. The antioxidant activity is related with ionization potential, polarizability and Log P.

Artificial Neural Networks and the Study of the Psychoactivity of Cannabinoid Compounds

Cannabinoid compounds have widely been employed because of its medicinal and psychotropic properties. These compounds are isolated from Cannabis sativa (or marijuana) and are used in several medical treatments, such as glaucoma, nausea associated to chemotherapy, pain and many other situations. More recently, its use as appetite stimulant has been indicated in patients with cachexia or AIDS. In this work, the influence of several molecular descriptors on the psychoactivity of 50 cannabinoid compounds is analyzed aiming one obtain a model able to predict the psychoactivity of new cannabinoids. For this purpose, initially, the selection of descriptors was carried out using the Fisher`s weight, the correlation matrix among the calculated variables and principal component analysis. From these analyses, the following descriptors have been considered more relevant: E(LUMO) (energy of the lowest unoccupied molecular orbital), Log P (logarithm of the partition coefficient), VC4 (volume of the substituent at the C4 position) and LP1 (Lovasz-Pelikan index, a molecular branching index). To follow, two neural network models were used to construct a more adequate model for classifying new cannabinoid compounds. The first model employed was multi-layer perceptrons, with algorithm back-propagation, and the second model used was the Kohonen network. The results obtained from both networks were compared and showed that both techniques presented a high percentage of correctness to discriminate psychoactive and psychoinactive compounds. However, the Kohonen network was superior to multi-layer perceptrons.

Studies toward the structural optimization of novel thiazolylhydrazone-based potent antitrypanosomal agents

In previous studies, we identified promising anti-Trypanosoma cruzi cruzain inhibitors based on thiazolylhydrazones. To optimize this series, a number of medicinal chemistry directions were explored and new thiazolylhydrazones and thiosemicarbazones were thus synthesized. Potent cruzain inhibitors were identified, such as thiazolylhydrazones 3b and 3j, which exhibited IC(50) of 200-400 nM. Furthermore, molecular docking studies showed concordance with experimentally derived structure-activity relationships (SAR) data. In the course of this work, lead compounds exhibiting in vitro activity against both the epimastigote and trypomastigote forms of T. cruzi were identified and in vivo general toxicity analysis was subsequently performed. Novel SAR were documented, including the importance of the thiocarbonyl carbon attached to the thiazolyl ring and the direct comparison between thiosemicarbazones and thiazolylhydrazones. (C) 2010 Elsevier Ltd. All rights reserved.