Biomedical subjects

Magaly Girão Albuquerque

Publications and source records attributed to Magaly Girão Albuquerque.

5 recordsLinked to original sources

PubMed2006

Structure-function inferences based on molecular modeling, sequence-based methods and biological data analysis of snake venom lectins.

Lectins are a structurally and functionally diverse group of proteins from different sources, capable to recognize and bind specifically carbohydrates. Several snake venoms contain calcium-dependent true lectins (SVLs) that recognize galactose. Herein, in order to enlighten some of the structure-function relationships of snake venom lectins (SVLs), we constructed theoretical models for 10 SVLs based on the Crotalus atrox lectin (CaL), the only SVL crystal structure available, and compared with other animal and plant lectins, and C-type lectin-like proteins (CLPs) that do not bind carbohydrates. Although these are theoretical structures, we could identify some SVL features, including: (i) a singular intrachain disulfide bond (Cys(38)-Cys(133)) that is not present in CLPs; (ii) a significant reorientation (39-41A) of the 80's loop position that folds back to the globular domain, assists the carbohydrate recognition domain (CRD), and orients the dimer formation, even in BfL-1 and BfL-2, which did not present the Cys(86) interchain; (iii) a CRD presenting a negative and concave surface that allows the interaction with the specific saccharide hydroxyl groups and calcium ion; (iv) the role of water molecules in some interchain interactions, similar to other animal and plant lectins; and (v) the inability of forming oligomers in contrast to CaL and some CLPs, such as convulxin.

Amino Acid Sequence↗

PubMed2006

Free-energy force-field three-dimensional quantitative structure-activity relationship analysis of a set of p38-mitogen activated protein kinase inhibitors.

The p38-mitogen-activated protein kinases (p38-MAPKs) belong to a family of serine-threonine kinases activated by pro-inflammatory or stressful stimuli that are known to be involved in several diseases. Their biological importance, related to the release of inflammatory pro-cytokines such as tumor necrosis factor-alpha (TNF-alpha) and interleukin-1 (IL-1), has generated many studies aiming at the development of selective inhibitors for the treatment of inflammatory diseases. In this work, we developed receptor-based three dimensional (3D) quantitative structure-activity relationship (QSAR) models for a series of 33 pyridinyl imidazole compounds [Liverton et al. (1999) 42:2180], using a methodology named free-energy force-field (FEFF) [Tokarski and Hopfinger (1997) 37:792], in which scaled intra- and intermolecular energy terms of the Assisted Model Building Energy Refinement (AMBER) force field combined with a hydration-shell solvation model are the independent variables used in the QSAR studies. Multiple temperature molecular-dynamics simulations (MDS) of ligand-protein complexes and genetic-function approximation (GFA) were employed using partial least squares (PLS) as the fitting functions to develop FEFF-3D-QSAR models for the binding process. The best model obtained in the FEFF-3D-QSAR receptor-dependent (RD) method shows the importance of the van der Waals energy change upon binding and the electrostatic energy in the interaction of ligands with the receptor. The QSAR equations described here show good predictability and may be regarded as representatives of the binding process of ligands to p38-MAPK. Additionally, we have compared the top FEFF-3D-QSAR model with receptor independent (RI) 4D-QSAR models developed in a recent study [Romeiro et al. (2005) 19:385].

Hydrophobic and Hydrophilic Interactions↗

PubMed2005

Construction of 4D-QSAR models for use in the design of novel p38-MAPK inhibitors.

The p38-mitogen-activated protein kinase (p38-MAPK) plays a key role in lipopolysaccharide-induced tumor necrosis factor-alpha (TNF-alpha) and interleukin-1 (IL-1) release during the inflammatory process, emerging as an attractive target for new anti-inflammatory agents. Four-dimensional quantitative structure-activity relationship (4D-QSAR) analysis [Hopfinger et al., J. Am. Chem. Soc., 119 (1997) 10509] was applied to a series of 33 (a training set of 28 and a test set of 5) pyridinyl-imidazole and pyrimidinyl-imidazole inhibitors of p38-MAPK, with IC50 ranging from 0.11 to 2100 nM [Liverton et al., J. Med. Chem., 42 (1999) 2180]. Five thousand conformations of each analogue were sampled from a molecular dynamics simulation (MDS) during 50 ps at a constant temperature of 303 K. Each conformation was placed in a 2 angstroms grid cell lattice for each of three trial alignments. 4D-QSAR models were constructed by genetic algorithm (GA) optimization and partial least squares (PLS) fitting, and evaluated by leave-one-out cross-validation technique. In the best models, with three to six terms, the adjusted cross-validated squared correlation coefficients, Q2adj, ranged from 0.67 to 0.85. Model D (Q2adj = 0.84) was identified as the most robust model from alignment 1, and it is representative of the other best models. This model encompasses new molecular regions as containing pharmacophore sites, such as the amino-benzyl moiety of pyrimidine analogs and the N1-substituent in the imidazole ring. These regions of the ligands should be further explored to identify better anti-inflammatory inhibitors of p38-MAPK.

Anti-Inflammatory Agents, Non-Steroidal↗

PubMed2004

LIV-3D-QSAR models for PGI2 receptor ligands using multiple conformations.

A new 3D descriptor, the local intersection volume (LIV), was developed by our group and applied to the construction of 3D-QSAR models for ligands of the PGI(2) receptor (IP). The target compounds are a set of 42 aromatic heterocyclic derivatives [Meanwell et al., J. Med. Chem. 36 (1993), 3884], which show agonist activities in the IP receptor and are inhibitors of platelet aggregation. The LIV-3D-QSAR models were obtained through the analysis of 30% of the generated conformations for each compound, using a combined Genetic Algorithm (GA) and Partial Least Square (PLS) approach [Rogers and Hopfinger, J. Inf. Comput. Sci. 34 (1994) 854]. Statistically, Model 3 is the best as well as the most comprehensive in a mechanistic sense. Furthermore, it can be applied to design new IP ligands.

Algorithms↗

PubMed2002

Local intersection volume: a new 3D descriptor applied to develop a 3D-QSAR pharmacophore model for benzodiazepine receptor ligands.

In this work, we have developed a new descriptor, named local intersection volume (LIV), in order to compose a 3D-QSAR pharmacophore model for benzodiazepine receptor ligands. The LIV can be classified as a 3D local shape descriptor in contraposition to the global shape descriptors. We have selected from the literature 49 non-benzodiazepine compounds as a training data set and the model was obtained and evaluated by genetic algorithms (GA) and partial least-squares (PLS) methods using LIVs as descriptors. The LIV 3D-QSAR model has a good predictive capacity according the cross-validation test by "leave-one-out" procedure (Q(2)=0.72). The developed model was compared to a comprehensive and extensive SAR pharmacophore model, recently proposed by Cook and co-workers, for benzodiazepine receptor ligands [J. Med. Chem. 43 (2000) 71]. It showed a relevant correlation with the pharmacophore groups pointed out in that work. Our LIV 3D-QSAR model was also able to predict affinity values for a series of nine compounds (test data set) that was not included into the training data set.

Algorithms↗