Cannabinoid derivatives exert a potent anti-myeloma activity both in vitro and in vivo.

Although hematopoietic and immune system show high levels of the cannabinoid receptor CB2, the potential effect of cannabinoids on hematologic malignancies has been poorly determined. Here we have investigated their anti-tumor effect in multiple myeloma (MM). We demonstrate that cannabinoids induce a selective apoptosis in MM cell lines and in primary plasma cells of MM patients, while sparing normal cells from healthy donors, including hematopoietic stem cells. This effect was mediated by caspase activation, mainly caspase-2, and was partially prevented by a pan-caspase inhibitor. Their pro-apoptotic effect was correlated with an increased expression of Bax and Bak, a decrease of Bcl-xL and Mcl-1, a biphasic response of Akt/PKB and an increase in the levels of ceramide in MM cells. Inhibition of ceramide synthesis partially prevented apoptosis, indicating that these sphingolipids play a key role in the pro-apoptotic effect of cannabinoids in MM cells. Remarkably, blockage of the CB2 receptor also inhibited cannabinoid-induced apoptosis. Cannabinoid derivative WIN-55 enhanced the anti-myeloma activity of dexamethasone and melphalan overcoming resistance to melphalan in vitro. Finally, administration of cannabinoid WIN-55 to plasmacytoma-bearing mice significantly suppressed tumor growth in vivo. Together, our data suggest that cannabinoids may be considered as potential therapeutic agents in the treatment of MM.

QSAR Modelling to Identify LRRK2 Inhibitors for Parkinson's Disease.

Parkinson's disease is one of the most common neurodegenerative illnesses in older persons and the leucine-rich repeat kinase 2 (LRRK2) is an auspicious target for its pharmacological treatment. In this work, quantitative structure-activity relationship (QSAR) models for identification of putative inhibitors of LRRK2 protein are developed by using an in-house chemical library and several machine learning techniques. The methodology applied in this paper has two steps: first, alternative subsets of molecular descriptors useful for characterizing LRRK2 inhibitors are chosen by a multi-objective feature selection method; secondly, QSAR models are learned by using these subsets and three different strategies for supervised learning. The qualities of all these QSAR models are compared by classical metrics and the best models are discussed in statistical and physicochemical terms.

Homology models of the cannabinoid CB1 and CB2 receptors. A docking analysis study.

The 3D models of both CB1 and CB2 human receptors have been established by homology modeling using as template the X-ray structure of bovine Rhodopsin (code pdb: 1F88) a G-protein-coupled receptor (GPCR). A recursive approach comprising sequence alignment and model building was used to build both models, followed by the refinement of non-conserved regions. The cannabinoid system has been studied by means of docking techniques, using the 3D models of both CB1 and CB2 and well known reference inverse agonist/antagonist compounds. An approach based on the flexibility of the structures has been used to model the receptor-ligand complexes. The structural effects of ligand binding were studied and analyzed on the basis of hydrogen bond interactions, and binding energy calculations. Potential interaction sites of the receptor were determined from analysis of the difference accessible surface area (DASA) study of the protein with and without ligand.

Exploring the binding sites of glycogen synthase kinase 3. Identification and characterization of allosteric modulation cavities.

Glycogen synthase kinase 3 (GSK-3) is an important drug target for human severe unmet diseases. Discovery and/or design of allosteric kinase modulators are gaining importance in this field not only for the increased selectivity of this kind of compounds but also for the subtle modulation of the target. This last point is of utmost importance for the GSK-3 inhibition as a therapeutic approach. GSK-3 activity is completely necessary for life, and only the aberrant overactivity found in the pathologies should be inhibited with its inhibitors treatment. We performed here a search for the druggable sites on the enzyme using the fpocket algorithm with the aim to provide allosteric potential binding sites on it and new clues for further drug discoveries. Moreover, our results allowed us to determine the binding sites of different GSK-3 ATP noncompetitive inhibitors, such as manzamine A and the new small molecule VP 0.7, providing evidence for potential allosteric inhibition of GSK-3.

Tacrine-melatonin hybrids as multifunctional agents for Alzheimer's disease, with cholinergic, antioxidant, and neuroprotective properties.

Tacrine-melatonin hybrids were designed and synthesized as new multifunctional drug candidates for Alzheimer's disease. These compounds may simultaneously palliate intellectual deficits and protect the brain against both beta-amyloid (A beta) peptide and oxidative stress. They show improved cholinergic and antioxidant properties, and are more potent and selective inhibitors of human acetylcholinesterase (hAChE) than tacrine. They also capture free radicals better than melatonin. Molecular modeling studies show that these hybrids target both the catalytic active site (CAS) and the peripheral anionic site (PAS) of AChE. At sub-micromolar concentrations they efficiently displace the binding of propidium iodide from the PAS and could thus inhibit A beta peptide aggregation promoted by AChE. Moreover, they also inhibit A beta self-aggregation and display neuroprotective properties in a human neuroblastoma line against cell death induced by various toxic insults, such as A beta(25-35), H(2)O(2), and rotenone. Finally, they exhibit low toxicity and may be able to penetrate the central nervous system according to an in vitro parallel artificial membrane permeability assay for the blood-brain barrier (PAMPA-BBB).

Homology modelling and active-site-mutagenesis study of the catalytic domain of the pneumococcal phosphorylcholine esterase.

Streptococcus pneumoniae is among the major human pathogens. Several interactions of this bacterium with its host appear to have been mediated by bacterial cell wall components. Specifically, phosphorylcholine residues covalently attached to teichoic and lipoteichoic acids serve as anchors for many surface-located proteins (choline-binding proteins CBPs), including cell-adhesion and virulence factors, and are also recognized by host response components through choline-binding receptors. In this study, we have performed modelling of the catalytic domain of pneumococcal phosphorylcholine esterase (Pce), a modular enzyme that is capable of removing phosphorycholine residues from teichoic and lipoteichoic acids, remodelling their distribution on the bacterial envelope. We wish to contribute to the structural knowledge of Pce. In this pursuit, 3D models of Pce have been established by homology modelling, using the X-ray structure of enzymes from the alpha/beta metallo-lactamase family fold as templates. Theoretical models of pneumococcal phosphorylcholine esterase (Pce) catalytic modules obtained by homology modelling, and corresponding docking studies employed to find out the residues involved in the binding of Zn ions, are discussed according to mutational studies and ab initio calculations. The presence of a binuclear Zn cluster in the catalytic domain of Pce and a likely coordination model are proposed.