Biomedical subjects

Magdalena Bacilieri

Publications and source records attributed to Magdalena Bacilieri.

5 recordsLinked to original sources

PubMed2006

The application of a 3D-QSAR (autoMEP/PLS) approach as an efficient pharmacodynamic-driven filtering method for small-sized virtual library: application to a lead optimization of a human A3 adenosine receptor antagonist.

We have recently reported that the combination of molecular electrostatic potential (MEP) surface properties (autocorrelation vectors) with the conventional partial least squares (PLS) analysis can be used to produce a robust ligand-based 3D structure-activity relationship (autoMEP/PLS) for the prediction of the human A3 receptor antagonist activities. Here, we present the application of the 3D-QSAR (autoMEP/PLS) approach as an efficient and alternative pharmacodynamic filtering method for small-sized virtual library. For this purpose, a small-sized combinatorial library (841 compounds) was derived from the scaffold of the known human A3 antagonist pyrazolo-triazolo-pyrimidines. The most interesting analogues were further prioritized for synthesis and pharmacological characterization. Remarkably, we have found that all the newly synthetized compounds are correctly predicted as potent human A3 antagonists. In particular, two of them are correctly predicted as sub-nanomolar inhibitors of the human A3 receptor.

Adenosine A3 Receptor Antagonists↗

PubMed2006

Ligand-based homology modeling as attractive tool to inspect GPCR structural plasticity.

G protein-coupled receptors (GPCRs) represent the largest family known of signal-transducing molecules. They convey signals for light and many extracellular regulatory molecules. GPCRs have been found to be dysfunctional/dysregulated in a growing number of human diseases and they have been estimated to be the targets of more than 40% of the drugs used in clinical medicine today. The crystal structure of rhodopsin provides the first three-dimensional GPCR information, which now supports homology modeling studies and structure-based drug design approaches. Here, we review our recent work on adenosine receptors, a family of GPCRs and, in particular, on A(3) adenosine receptor subtype antagonists. We will focus on an alternative approach to computationally explore the multi-conformational space of the antagonist-like state of the human A(3) receptor. We define ligand-based homology modeling as new approach to simulate the reorganization of the receptor induced by the ligand binding. The success of this approach is due to the synergic interaction between theory and experiment.

Adenosine A3 Receptor Antagonists↗

PubMed2005

Autocorrelation of molecular electrostatic potential surface properties combined with partial least squares analysis as new strategy for the prediction of the activity of human A(3) adenosine receptor antagonists.

The combination of molecular electrostatic potential (MEP) surface properties (autocorrelation vectors) with the conventional partial least squares (PLS) analysis has been used for the prediction of the human A(3) receptor antagonist activities. Three-hundred-fifty-eight structurally diverse human A(3) receptor antagonists have been utilized to generate a novel ligand-based three-dimensional structure-activity relationship. Remarkably, our chemical library includes all 21 important chemical classes of human A(3) antagonists currently discovered, and it represents the largest molecular collection used to generate a general human A(3) antagonist structure-activity relationship. A robust quantitative model has been obtained as described by both cross-validated correlation coefficient (r(cv) = 0.81) and prediction capability (r(pred) = 0.82). The proposed MEP/PLS approach can be considered as an alternative hit identification tool in virtual screening applications.

Adenosine A3 Receptor Antagonists↗

PubMed2005

A2B adenosine receptor antagonists: recent developments.

There are pharmacological evidences that A(2B) receptors are involved in inflammatory processes, such as asthma. For this reason, many efforts has been made for identifying selective A(2B) antagonists as anti-asthmatic agents. The updated material related to this field has been rationalised and arranged in order to offer an overview of the topic.

Adenosine A2 Receptor Antagonists↗

PubMed2005

Autocorrelation of molecular electrostatic potential surface properties combined with partial least squares analysis as alternative attractive tool to generate ligand-based 3D-QSARs.

A database of 106 human A3 adenosine receptor antagonists was used to derive two alternative PLS models: one starting from CoMFA descriptors and the other starting from the autocorrelation descriptors. The peculiarity of this work is the introduction of autocorrelation vectors as molecular descriptors for the PLS analysis. The autocorrelation allows comparing molecules (and their properties) with different structures and with different spatial orientation without any previous alignment. In particular, Molecular Electrostatic Potential (MEP) was the property computed and its information encoded in autocorrelation vectors. The 3D spatial distribution and the values of the electrostatic potential is in fact largely responsible for the binding of a substrate to its receptor binding site. Validation was done with an external test set and the results of the two models were compared. Interestingly, our preliminary results seem to indicate that this new alternative approach could robustly compete with the already well consolidated CoMFA approach. In particular, we have suggested that it could be a very interesting tool to filter large structural database in several virtual screening applications.

Adenosine A3 Receptor Antagonists↗