Biomedical subjects

Andrea Zaliani

Publications and source records attributed to Andrea Zaliani.

5 recordsLinked to original sources

PubMed2005

A novel glucokinase activator modulates pancreatic islet and hepatocyte function.

The glucose-sensing enzyme glucokinase (GK) plays a key role in glucose metabolism. We report here the effects of a novel glucokinase activator, LY2121260. The activator enhanced GK activity via binding to the allosteric site located in the hinge region of the enzyme. LY2121260 stimulated insulin secretion in a glucose-dependent manner in pancreatic beta-cells and increased glucose use in rat hepatocytes. In addition, incubation of beta-cells with the GK activator resulted in increased GK protein levels, suggesting that enhanced insulin secretion on chronic treatment with a GK activator may be due to not only changed enzyme kinetics but also elevated enzyme levels. Animals treated with LY2121260 showed an improved glucose tolerance after oral glucose challenge. These results support the concept that GK activators represent a new class of compounds that increase both insulin secretion and hepatic glucose use and in doing so may prove to be effective agents for the control of blood glucose levels in patients with type 2 diabetes.

Animals↗

PubMed2004

Identifying the binding mode of a molecular scaffold.

We describe a method for docking of a scaffold-based series and present its advantages over docking of individual ligands, for determining the binding mode of a molecular scaffold in a binding site. The method has been applied to eight different scaffolds of protein kinase inhibitors (PKI). A single analog of each of these eight scaffolds was previously crystallized with different protein kinases. We have used FlexX to dock a set of molecules that share the same scaffold, rather than docking a single molecule. The main mode of binding is determined by the mode of binding of the largest cluster among the docked molecules that share a scaffold. Clustering is based on our 'nearest single neighbor' method [J. Chem. Inf. Comput. Sci., 43 (2003) 208-217]. Additional criteria are applied in those cases in which more than one significant binding mode is found. Using the proposed method, most of the crystallographic binding modes of these scaffolds were reconstructed. Alternative modes, that have not been detected yet by experiments, could also be identified. The method was applied to predict the binding mode of an additional molecular scaffold that was not yet reported and the predicted binding mode has been found to be very similar to experimental results for a closely related scaffold. We suggest that this approach be used as a virtual screening tool for scaffold-based design processes.

Binding Sites↗

PubMed2002

The antitumor histone deacetylase inhibitor suberoylanilide hydroxamic acid exhibits antiinflammatory properties via suppression of cytokines.

Suberoylanilide hydroxamic acid (SAHA) is a hydroxamic acid-containing hybrid polar molecule; SAHA specifically binds to and inhibits the activity of histone deacetylase. Although SAHA, like other inhibitors of histone deacetylase, exhibits antitumor effects by increasing expression of genes regulating tumor survival, we found that SAHA reduces the production of proinflammatory cytokines in vivo and in vitro. A single oral administration of SAHA to mice dose-dependently reduced circulating TNF-alpha, IL-1-beta, IL-6, and IFN-gamma induced by lipopolysaccharide (LPS). Administration of SAHA also reduced hepatic cellular injury in mice following i.v. injection of Con A. SAHA inhibited nitric oxide release in mouse macrophages stimulated by the combination of TNF-alpha plus IFN-gamma. Human peripheral blood mononuclear cells stimulated with LPS in the presence of SAHA released less TNF-alpha, IL-1-beta, IL-12, and IFN-gamma (50% reduction at 100-200 nM). The production of IFN-gamma stimulated by IL-18 plus IL-12 was also inhibited by SAHA (85% at 200 nM). However, SAHA did not affect LPS-induced synthesis of the IL-1-beta precursor, the IL-1 receptor antagonist, or the chemokine IL-8. In addition, IFN-gamma induced by anti-CD3 was not suppressed by SAHA. Steady-state mRNA levels for LPS-induced TNF-alpha and IFN-gamma in peripheral blood mononuclear cells were markedly decreased, whereas IL-8 and IL-1-beta mRNA levels were unaffected. Because SAHA exhibits antiinflammatory properties in vivo and in vitro, inhibitors of histone deacetylase may stimulate the expression of genes that control the synthesis of cytokines and nitric oxide or hyperacetylate other targets.

Animals↗

PubMedDate not supplied

A knowledge-based weighting approach to ligand-based virtual screening.

On the basis of the recently introduced reduced graph concept of ErG (extending reduced graphs), a straightforward weighting approach to include additional (e.g., structural or SAR) knowledge into similarity searching procedures for virtual screening (wErG) is proposed. This simple procedure is exemplified with three data sets, for which interaction patterns available from X-ray structures of native or peptidomimetic ligands with their target protein are used to significantly improve retrieval rates of known actives from the MDL Drug Report database. The results are compared to those of other virtual screening techniques such as Daylight fingerprints, FTrees, UNITY, and various FlexX docking protocols. Here, it is shown that wErG exhibits a very good and stable performance independent of the target structure. On the basis of this (and the fact that ErG retrieves structurally more dissimilar compounds due to its potential to perform scaffold-hopping), the combination of wErG and FlexX is successfully explored. Overall, wErG is not only an easily applicable weighting procedure that efficiently identifies actives in large data sets but it is also straightforward to understand for both medicinal and computational chemists and can, therefore, be driven by several aspects of project-related knowledge (e.g., X-ray, NMR, SAR, and site-directed mutagenesis) in a very early stage of the hit identification process.

Computational Biology↗

PubMedDate not supplied

ErG: 2D pharmacophore descriptions for scaffold hopping.

An extended reduced graph approach (ErG) is presented that uses pharmacophore-type node descriptions to encode the relevant molecular properties. The basic idea of the method can be described as a hybrid approach of reduced graphs (Gillet et al. J. Chem. Inf. Comput. Sci. 2003, 43, 338-345) and binding property pairs (Kearsley et al. J. Chem. Inf. Comput. Sci. 1996, 36, 118-127). However, specific extension modifications to correctly describe the pharmacophoric properties, size, and shape of the molecules under study result in a very stable and good performance as compared to DAYLIGHT fingerprints (DFP). This is exemplified for 11 activity classes of the MDL Drug Data Report database, for which ErG performs as well or better than DFP in 10 cases. On the basis of the example data sets, the ability of ErG to switch from one chemotype to another (often referred to as "scaffold hopping") is highlighted. Additionally, possible pitfalls of reduced graph approaches as well as suitable solutions are discussed with the help of example structures. Overall, it is shown that ErG is a widely applicable method capable of identifying structurally diverse actives for a given active search query. This diversity is achieved by a high degree of molecular abstraction, which in turn results in a low dimensional descriptor vector that allows very low computation times for similarity searches.

Journal Article↗