Three-Dimensional Models of the Oligomeric Human Asialoglycoprotein Receptor (ASGP-R)

The work presented here is aimed at suggesting plausible hypotheses for functional oligomeric forms of the human asialoglycoprotein receptor (ASGP-R), by applying a combination of different computational techniques. The functional ASGP-R is a hetero-oligomer, that comprises of several subunits of two different kinds (H1 and H2), which are highly homologous. Its stoichiometry is still unknown. An articulated step-wise modeling protocol was used in order to build the receptor model in a minimal oligomeric form, necessary for it to bind multi-antennary carbohydrate ligands. The ultimate target of the study is to contribute to increasing the knowledge of interactions between the human ASGP-R and carbohydrate ligands, at the molecular level, pertinent to applications in the field of hepatic tissue engineering

Development of Classification Models for Identifying “True” P-glycoprotein (P-gp) Inhibitors Through Inhibition, ATPase Activation and Monolayer Efflux Assays

P-glycoprotein (P-gp) is an efflux pump involved in the protection of tissues of several organs by influencing xenobiotic disposition. P-gp plays a key role in multidrug resistance and in the progression of many neurodegenerative diseases. The development of new and more effective therapeutics targeting P-gp thus represents an intriguing challenge in drug discovery. P-gp inhibition may be considered as a valid approach to improve drug bioavailability as well as to overcome drug resistance to many kinds of tumours characterized by the over-expression of this protein. This study aims to develop classification models from a unique dataset of 59 compounds for which there were homogeneous experimental data on P-gp inhibition, ATPase activation and monolayer efflux. For each experiment, the dataset was split into a training and a test set comprising 39 and 20 molecules, respectively. Rational splitting was accomplished using a sphere-exclusion type algorithm. After a two-step (internal/external) validation, the best-performing classification models were used in a consensus predicting task for the identification of compounds named as “true” P-gp inhibitors, i.e., molecules able to inhibit P-gp without being effluxed by P-gp itself and simultaneously unable to activate the ATPase function

Cell-specific pattern of berberine pleiotropic effects on different human cell lines

The natural alkaloid berberine has several pharmacological properties and recently received attention as a potential anticancer agent. In this work, we investigated the molecular mechanisms underlying the anti-Tumor effect of berberine on glioblastoma U343 and pancreatic carcinoma MIA PaCa-2 cells. Human dermal fibroblasts (HDF) were used as non-cancer cells. We show that berberine differentially affects cell viability, displaying a higher cytotoxicity on the two cancer cell lines than on HDF. Berberine also affects cell cycle progression, senescence, caspase-3 activity, autophagy and migration in a cell-specific manner. In particular, in HDF it induces cell cycle arrest in G2 and senescence, but not autophagy; in the U343 cells, berberine leads to cell cycle arrest in G2 and induces both senescence and autophagy; in MIA PaCa-2 cells, the alkaloid induces arrest in G1, senescence, autophagy, it increases caspase-3 activity and impairs migration/invasion. As demonstrated by decreased citrate synthase activity, the three cell lines show mitochondrial dysfunction following berberine exposure. Finally, we observed that berberine modulates the expression profile of genes involved in different pathways of tumorigenesis in a cell line-specific manner. These findings have valuable implications for understanding the complex functional interactions between berberine and specific cell types

Binding free energy calculations of Adenosine Deaminase inhibitors

The interactions between four inhibitors and adenosine deaminase (ADA) were examined by calculating their binding free energies after molecular dynamics simulations. A bonded model was used to represent the electrostatic potentials of the zinc coordination site. The charge distribution of the model was derived by using a two-stage electrostatic potential fitting calculations. The calculated binding free energies are in good agreement with the experimental data and the ranking of binding affinities is well reproduced. Notably, our findings suggest that non-polar contributions play an important role for ADA-inhibitor interactions

Enhancer and Competitive Allosteric Modulation Model for G-protein Coupled Receptors

A new mathematical model, referred to as Enhancer and Competitive Allosteric Modulator (ECAM) model, developed with the aim of quantitatively describing the interaction of an allosteric modulator with both enhancer and competitive properties towards G-protein-coupled receptors is described here. Model simulations for equilibrium (displacement-like and saturation-like), and kinetic (association and dissociation) binding experiments were performed. The results showed the ability of the model to interpret a number of possible ligand-receptor binding behaviors. In particular, the binding properties of PD81723, an enhancer and competitive allosteric modulator for the adenosine A(1) receptor, were experimentally evaluated by radioligand binding assays and interpreted by the ECAM model. The results also offer a theoretical background enabling the design and optimization of compounds endowed with allosteric enhancer, competitive, agonist, antagonist, and inverse agonist properties

Application of Cascade-Correlation Networks for Structures to Chemistry

none4We present the application of Cascade Correlation for structures to QSPR (quantitative structure-property relationships) and QSAR (quantitative structure-activity relationships) analysis. Cascade Correlation for structures is a neural network model recently proposed for the processing of structured data. This allows the direct treatment of chemical compounds as labeled trees, which constitutes a novel approach to QSPR/QSAR. We report the results obtained for QSPR on Alkanes (predicting the boiling point) and QSAR of a class of Benzodiazepines. Our approach compares favorably versus the traditional QSAR treatment based on equations and it is competitive with 'ad hoc' MLPs for the QSPR problem.noneBIANUCCI A.M; MICHELI A; SPERDUTI A.; STARITA ABIANUCCI A., M; Micheli, A; Sperduti, Alessandro; Starita, A