Tandem 3D-QSARs approach as a valuable tool to predict binding affinity data: design of new Gly/NMDA receptor antagonists as a key study.

Quantitative structure-activity relationships (QSARs) represent a very well consolidated computational approach to correlate structural or property descriptors of chemical compounds with their chemical or biological activities. We have recently reported that autocorrelation Molecular Electrostatic Potential (autoMEP) vectors in combination to Partial Least-Square (PLS) analysis or to Response Surface Analysis (RSA) can represent an interesting alternative 3D-QSAR strategy. In the present paper, we would like to present how the applicability of in tandem linear and nonlinear 3D-QSAR methods (autoMEP/PLS&RSA) can help to predict binding affinity data of a new set of N-methyl-d-aspartate (Gly/NMDA) receptor antagonists.

Novel strategies for the design of new potent and selective human A3 receptor antagonists: an update.

A computer-aided approach has been developed in order to understand the molecular pharmacology of human A3R, and specifically, to lead to the discovery and structural refinement of new, potent and selective human A3R antagonists. This review focuses on our combined target-based and ligand-based drug design strategy, recently applied to provide more accurate information about the recognition mode on human A3R of some pyrazolotriazolopyrimidine and triazoloquinoxalinone analogs. The 3D rhodopsin-based homology model of human A3R has represented the starting point of our approach. A high throughput molecular docking method on the considered antagonists has allowed us to generate a receptor-based pharmacophore model. A novel "Y-shaped" pharmacophore binding motif has been proposed for both pyrazolotriazolopyrimidine and triazoloquinoxalinone derivatives. Moreover, related receptor-based 3D-QSAR analysis has been carried out to provide a suitable tool for prediction of the antagonists binding affinity on human A3R.

CD34(+) cell subsets and long-term culture colony-forming cells evaluated on both autologous and normal bone marrow stroma predict long-term hematopoietic engraftment in patients undergoing autologous peripheral blood stem cell transplantation.

OBJECTIVE: The aim of this study was to evaluate which CD34(+) cell subset contained in leukapheresis products could be regarded as the most predictive of long-term hematopoietic recovery after autologous peripheral blood stem cell transplantation (auto-PBSCT). MATERIALS AND METHODS: Based on data from 34 patients with hematologic malignancies, doses of CD34(+) cells and CD34(+) cell subsets, defined by the expression of HLA-DR, CD38, CD117 (c-kit/R), CD123 (alpha subunit of IL-3/R), CD133 (AC133), and CD90 (Thy-1) antigens, were correlated with the number of short-term (i.e., colony-forming cells [CFC]) and long-term culture CFC (LTC-CFC) (generated at week 5 of culture) and with the kinetics of hematopoietic engraftment following auto-PBSCT. The capacity of autologous stroma (AS), normal human bone marrow stroma, and M2-10B4 murine cell line to sustain CD34(+) cell growth was comparatively evaluated in the LTC assay. RESULTS: Our data demonstrated that some of the most primitive progenitor subsets (CD34(+)CD117(-)HLA-DR(-), and CD34(+)CD38(+)HLA-DR(-)) showed the strongest correlation with LTC-CFC numbers generated within the AS, whereas no significant correlation was noted using normal bone marrow stroma. Multivariate analysis showed that the only CD34 cell subset independently associated with long-term (3 to 6 months) platelet engraftment after auto-bone marrow transplantation was the CD34(+)CD117(-)HLA-DR(-) phenotype; long-term erythrocyte engraftment was correlated with CD34(+)CD38(+)HLA-DR(-) cell content. The latter further influenced platelet engraftment in the first 3 months after auto-PBSCT. The most predictive parameters for neutrophil engraftment were CD34(+)CD38(+)HLA-DR(-) cell subtype and the total LTC-CFC quantity infused. CONCLUSIONS: These data further support the hypothesis that the type of stromal feeders influences the frequency of LTC-CFC, possibly because they differ in their ability to interact with distinct subsets of hematopoietic stem cells. Furthermore, as the use of AS in LTC assay can mimic in vitro the human bone marrow microenvironment, it can be speculated that this culture system could be a useful means to study the kinetics of recovery of bone marrow stroma following chemotherapy and PBSCT. From these results, it can be concluded that some CD34(+) cell subsets appear to be more reliable predictors of long-term hematopoietic recovery rates than total CD34(+) cell quantity.