Drug Delivery Systems Based on Modified Polysaccharides: Synthesis and Characterization.

Common chemotherapeutic drugs exhibit no specificity for cancer cells and destroy simultaneously healthy cells exhibiting high toxicity and reduced efficacy. The use of nanotechnology, especially of drug delivery systems to the size of the nanoscale, provides rational drug design solutions. Such nanomaterials may have a range of desired characteristics (lack of toxicity, response to certain characteristics of the cancer cells, antimicrobial properties, specific activity, etc.) in order to achieve targeted cancer therapy. In this chapter, polymeric systems with core-shell structure are synthesized, characterized, and studied as potent drug delivery devices for targeted cancer therapy. These polymeric systems are based on natural polysaccharides like cellulose, chitosan, and their derivatives, in combination with synthetic polymer. Polymethylmethacrylate (PMMA) nanospheres are used as a core in order to coat the surface with multiple layers of polysaccharides via layer-by-layer deposition. This design is advantageous due to the use of water as the appropriate solvent. Fabricated polymeric carriers are characterized structurally by AT-IR spectroscopy and morphologically by transmission (TEM) and scanning electron microscopy (SEM). Finally, daunorubicin, an anticancer agent, was encapsulated as a drug model into the carriers.

Pharmacological characterisation of novel adenosine A3 receptor antagonists.

The adenosine A3 receptor (A3R) belongs to a family of four adenosine receptor (AR) subtypes which all play distinct roles throughout the body. A3R antagonists have been described as potential treatments for numerous diseases including asthma. Given the similarity between (adenosine receptors) orthosteric binding sites, obtaining highly selective antagonists is a challenging but critical task. Here we screen 39 potential A3R, antagonists using agonist-induced inhibition of cAMP. Positive hits were assessed for AR subtype selectivity through cAMP accumulation assays. The antagonist affinity was determined using Schild analysis (pA2 values) and fluorescent ligand binding. Structure-activity relationship investigations revealed that loss of the 3-(dichlorophenyl)-isoxazolyl moiety or the aromatic nitrogen heterocycle with nitrogen at α-position to the carbon of carboximidamide group significantly attenuated K18 antagonistic potency. Mutagenic studies supported by molecular dynamic simulations combined with Molecular Mechanics-Poisson Boltzmann Surface Area calculations identified the residues important for binding in the A3R orthosteric site. We demonstrate that K18, which contains a 3-(dichlorophenyl)-isoxazole group connected through carbonyloxycarboximidamide fragment with a 1,3-thiazole ring, is a specific A3R (< 1 µM) competitive antagonist. Finally, we introduce a model that enables estimates of the equilibrium binding affinity for rapidly disassociating compounds from real-time fluorescent ligand-binding studies. These results demonstrate the pharmacological characterisation of a selective competitive A3R antagonist and the description of its orthosteric binding mode. Our findings may provide new insights for drug discovery.

Insights to the Binding of a Selective Adenosine A3 Receptor Antagonist Using Molecular Dynamic Simulations, MM-PBSA and MM-GBSA Free Energy Calculations, and Mutagenesis.

Adenosine A3 receptor (A3R) is a promising drug target cancer and for a number of other conditions like inflammatory diseases, including asthma and rheumatoid arthritis, glaucoma, chronic obstructive pulmonary disease, and ischemic injury. Currently, there is no experimentally determined structure of A3R. We explored the binding profile of O4-{[3-(2,6-dichlorophenyl)-5-methylisoxazol-4-yl]carbonyl}-2-methyl-1,3-thiazole-4-carbohydroximamide (K18), which is a new specific and competitive antagonist at the orthosteric binding site of A3R. MD simulations and MM-GBSA calculations of the WT A3R in complex with K18 combined with in vitro mutagenic studies show that the most plausible binding conformation for the dichlorophenyl group of K18 is oriented toward trans-membrane helices (TM) 5, 6 and reveal important residues for binding. Further, MM-GBSA calculations distinguish mutations that reduce or maintain or increase antagonistic activity. Our studies show that selectivity of K18 toward A3R is defined not only by direct interactions with residues within the orthosteric binding area but also by remote residues playing a significant role. Although V1695.30 is considered to be a selectivity filter for A3R binders, when it was mutated to glutamic acid, K18 maintained antagonistic potency, in agreement with our previous results obtained for agonists binding profile investigation. Mutation of the direct interacting residue L903.32 in the low region and the remote L2647.35 in the middle/upper region to alanine increases antagonistic potency, suggesting an empty space in the orthosteric area available for increasing antagonist potency. These results approve the computational model for the description of K18 binding at A3R, which we previously performed for agonists binding to A3R, and the design of more effective antagonists based on K18.

Structural Characterization of Agonist Binding to an A3 Adenosine Receptor through Biomolecular Simulations and Mutagenesis Experiments.

The adenosine A3 receptor (A3R) binds adenosine and is a drug target against cancer cell proliferation. Currently, there is no experimental structure of A3R. Here, we have generated a molecular model of A3R in complex with two agonists, the nonselective 1-(6-amino-9H-purin-9-yl)-1-deoxy-N-ethyl-ß-d-ribofuranuronamide (NECA) and the selective 1-deoxy-1-[6-[[(3-iodophenyl)methyl]amino]-9H-purin-9-yl]-N-methyl-ß-d-ribofuranuronamide (IB-MECA). Molecular dynamics simulations of the wild-type A3R in complex with both agonists, combined with in vitro mutagenic studies revealed important residues for binding. Further, molecular mechanics-generalized Born surface area calculations were able to distinguish mutations that reduce or negate agonistic activity from those that maintained or increased the activity. Our studies reveal that selectivity of IB-MECA toward A3R requires not only direct interactions with residues within the orthosteric binding area but also with remote residues. Although V1695.30 is considered to be a selectivity filter for A3R binders, when it was mutated to glutamic acid or alanine, the activity of IB-MECA increased by making new van der Waals contacts with TM5. This result may have implications in the design of new A3R agonists.

Discovery of Novel Adenosine Receptor Antagonists through a Combined Structure- and Ligand-Based Approach Followed by Molecular Dynamics Investigation of Ligand Binding Mode.

An intense effort is made by pharmaceutical and academic research laboratories to identify and develop selective antagonists for each adenosine receptor (AR) subtype as potential clinical candidates for "soft" treatment of various diseases. Crystal structures of subtypes A2A and A1ARs offer exciting opportunities for structure-based drug design. In the first part of the present work, Maybridge HitFinder library of 14400 compounds was utilized to apply a combination of structure-based against the crystal structure of A2AAR and ligand-based methodologies. The docking poses were rescored by CHARMM energy minimization and calculation of the desolvation energy using Poisson-Boltzmann equation electrostatics. Out of the eight selected and tested compounds, five were found positive hits (63% success). Although the project was initially focused on targeting A2AAR, the identified antagonists exhibited low micromolar or micromolar affinity against A2A/A3, ARs, or A3AR, respectively. Based on these results, 19 compounds characterized by novel chemotypes were purchased and tested. Sixteen of them were identified as AR antagonists with affinity toward combinations of the AR family isoforms (A2A/A3, A1/A3, A1/A2A/A3, and A3). The second part of this work involves the performance of hundreds of molecular dynamics (MD) simulations of complexes between the ARs and a total of 27 ligands to resolve the binding interactions of the active compounds, which were not achieved by docking calculations alone. This computational work allowed the prediction of stable and unstable complexes which agree with the experimental results of potent and inactive compounds, respectively. Of particular interest is that the 2-amino-thiophene-3-carboxamides, 3-acylamino-5-aryl-thiophene-2-carboxamides, and carbonyloxycarboximidamide derivatives were found to be selective and possess a micromolar to low micromolar affinity for the A3 receptor.

Integrating computational methods to predict mutagenicity of aromatic azo compounds.

Azo dyes have several industrial uses. However, these azo dyes and their degradation products showed mutagenicity, inducing damage in environmental and human systems. Computational methods are proposed as cheap and rapid alternatives to predict the toxicity of azo dyes. A benchmark dataset of Ames data for 354 azo dyes was employed to develop three classification strategies using knowledge-based methods and docking simulations. Results were compared and integrated with three models from the literature, developing a series of consensus strategies. The good results confirm the usefulness of in silico methods as a support for experimental methods to predict the mutagenicity of azo compounds.

Development of a Predictive Pharmacophore Model and a 3D-QSAR Study for an in silico Screening of New Potent Bcr-Abl Kinase Inhibitors.

Chronic myelogenous leukemia (CML) is a myeloproliferative disorder, characterized, in most cases, by the presence of the Bcr-Abl fusion oncogene. Bcr-Abl is a constitutively active tyrosine kinase that is responsible for the malignant transformation. Targeting the Bcr-Abl kinase is an attractive treatment strategy for CML. First and second generation Bcr-Abl inhibitors have focused on targeting the ATP-binding domain of the kinase. Mutations in that region are relatively resistant to drug manipulation. Therefore, non-ATP-competitive agents have been recently developed and tested. In the present study, in an attempt to aid the design of new chemotypes with enhanced cytotoxicity against K562 cells, 3D pharmacophore models were generated and 3D-QSAR CoMFA and CoMSIA studies were carried out on the 33 novel Abl kinase inhibitors (E)-α-benzylthio chalcones synthesized by Reddy et al. A five-point pharmacophore with a hydrogen bond acceptor, two hydrophobic groups and two aromatic rings as pharmacophore features, and a statistically significant 3D-QSAR model with excellent predictive power were developed. The pharmacophore model was also used for alignment of the 33 compounds in a CoMFA/CoMSIA analysis. The contour maps of the fields of CoMFA and CoMSIA models were utilized to provide structural insight into how these molecules promote their toxicity. The possibility of using this model for the design of drugs for the treatment of β-thalassemia and sickle cell disease (SCD), since several Bcr-Abl inhibitors are able to promote erythroid differentiation and γ-globin expression in CML cell lines and primary erythroid cells is discussed.

Searching for Novel Janus Kinase-2 Inhibitors Using a Combination of Pharmacophore Modeling, 3D-QSAR Studies and Virtual Screening.

The Janus kinases (JAKs) play a pivotal role in cytokine receptor signaling pathways via activation of downstream signal transducers and activators of transcription (STAT) pathway. Intracellular pathways that include JAKs are critical to immune cell activation and pro-inflammatory cytokine production. Selective inhibitors of JAKs are potentially disease-modifying anti-inflammatory drugs for the treatment of rheumatoid arthritis (RA). Each of the four members of the JAK family plays an individual role in the oncogenesis of the immune system, and therefore, the development of potent and specific inhibitors for each member is needed. Although there is a high sequence homology and structural identity of JAK1 and JAK2, such as a very similar binding mode of inhibitors at the ATPbinding site of enzymes, obvious differences surrounding the JAK1 and JAK2 ATP-binding sites provide a platform for the rational design of JAK2- and JAK1-specific inhibitors. In the present study, a dataset of 33 compounds characterized by a common scaffold of 2-amino-[1,2,4]triazolo[1,5-α]pyridine with well-defined in vitro activity values was computationally explored. Most of the compounds included in the dataset had higher ligand efficiency against JAK2 than JAK1. To improve further the selectivity of these triazolopyridines, Common Pharmacophore Hypotheses (CPHs) were generated and 3D-QSAR studies were carried out on them, in order to comprehend on the molecular features responsible for their selectivity. The proposed computational approach was applied in order to perform an in silico database virtual screening study with the aim to discover novel potent and selective JAK2 inhibitors.