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

Benchmarking Australian enabling programs for a national framework of standards

Enabling education programs in Australia assist students, who would otherwise have been excluded from higher education, to transition into undergraduate study. These programs emerged independently in response to the needs of individual universities and the varying cohorts of students they serve. The exclusion of these programs from the Australian Qualifications Framework (AQF) has meant they remain unregulated, with no national framework for standards. The development of academic standards is a dynamic, consensus driven process, and benchmarking provides a method through which academics from across institutions can work in partnership to reach shared understandings and improve and align practices. This practice report outlines the results of the first comprehensive cross-institutional benchmarking project involving nine Australian universities and demonstrates there is shared understanding of the standards of enabling programs between institutions. These findings will contribute to the establishment of national standards for enabling programs in Australia

Structure of eukaryotic purine/H(+) symporter UapA suggests a role for homodimerization in transport activity

The uric acid/xanthine H(+) symporter, UapA, is a high-affinity purine transporter from the filamentous fungus Aspergillus nidulans. Here we present the crystal structure of a genetically stabilized version of UapA (UapA-G411VΔ1-11) in complex with xanthine. UapA is formed from two domains, a core domain and a gate domain, similar to the previously solved uracil transporter UraA, which belongs to the same family. The structure shows UapA in an inward-facing conformation with xanthine bound to residues in the core domain. Unlike UraA, which was observed to be a monomer, UapA forms a dimer in the crystals with dimer interactions formed exclusively through the gate domain. Analysis of dominant negative mutants is consistent with dimerization playing a key role in transport. We postulate that UapA uses an elevator transport mechanism likely to be shared with other structurally homologous transporters including anion exchangers and prestin

Contribution of Deep Learning in the Investigation of Possible Dual LOX-3 Inhibitors/DPPH Scavengers: The Case of Recently Synthesized Compounds

Even though non-steroidal anti-inflammatory drugs are the most effective treatment for inflammatory conditions, they have been linked to negative side effects. A promising approach to mitigating potential risks, is the development of new compounds able to combine anti-inflammatory with antioxidant activity to enhance activity and reduce toxicity. The implication of reactive oxygen species in inflammatory conditions has been extensively studied, based on the pro-inflammatory properties of generated free radicals. Drugs with dual activity (i.e., inhibiting inflammation related enzymes, e.g., LOX-3 and scavenging free radicals, e.g., DPPH) could find various therapeutic applications, such as in cardiovascular or neurodegenerating disorders. The challenge we embarked on using deep learning was the creation of appropriate classification and regression models to discriminate pharmacological activity and selectivity as well as to discover future compounds with dual activity prior to synthesis. An accurate filter algorithm was established, based on knowledge from compounds already evaluated in vitro, that can separate compounds with low, moderate or high activity. In this study, we constructed a customized highly effective one dimensional convolutional neural network (CONV1D), with accuracy scores up to 95.2%, that was able to identify dual active compounds, being LOX-3 inhibitors and DPPH scavengers, as an indication of simultaneous anti-inflammatory and antioxidant activity. Additionally, we created a highly accurate regression model that predicted the exact value of effectiveness of a set of recently synthesized compounds with anti-inflammatory activity, scoring a root mean square error value of 0.8. Eventually, we succeeded in observing the manner in which those newly synthesized compounds differentiate from each other, regarding a specific pharmacological target, using deep learning algorithms

Design of Multifaceted Antioxidants: Shifting towards Anti-Inflammatory and Antihyperlipidemic Activity

Oxidative stress and inflammation are two conditions that coexist in many multifactorial diseases such as atherosclerosis and neurodegeneration. Thus, the design of multifunctional compounds that can concurrently tackle two or more therapeutic targets is an appealing approach. In this study, the basic NSAID structure was fused with the antioxidant moieties 3,5-di-tert-butyl-4-hydroxybenzoic acid (BHB), its reduced alcohol 3,5-di-tert-butyl- 4-hydroxybenzyl alcohol (BHBA), or 6-hydroxy-2,5,7,8-tetramethylchromane-2-carboxylic acid (Trolox), a hydrophilic analogue of α-tocopherol. Machine learning algorithms were utilized to validate the potential dual effect (anti-inflammatory and antioxidant) of the designed analogues. Derivatives 1–17 were synthesized by known esterification methods, with good to excellent yields, and were pharmacologically evaluated both in vitro and in vivo for their antioxidant and anti-inflammatory activity, whereas selected compounds were also tested in an in vivo hyperlipidemia protocol. Furthermore, the activity/binding affinity of the new compounds for lipoxygenase-3 (LOX-3) was studied not only in vitro but also via molecular docking simulations. Experimental results demonstrated that the antioxidant and anti-inflammatory activities of the new fused molecules were increased compared to the parent molecules, while molecular docking simulations validated the improved activity and revealed the binding mode of the most potent inhibitors. The purpose of their design was justified by providing a potentially safer and more efficient therapeutic approach for multifactorial diseases

Identification of the substrate recognition and transport pathway in a eukaryotic member of the nucleobase-ascorbate transporter (NAT) family.

Using the crystal structure of the uracil transporter UraA of Escherichia coli, we constructed a 3D model of the Aspergillus nidulans uric acid-xanthine/H(+) symporter UapA, which is a prototype member of the Nucleobase-Ascorbate Transporter (NAT) family. The model consists of 14 transmembrane segments (TMSs) divided into a core and a gate domain, the later being distinctly different from that of UraA. By implementing Molecular Mechanics (MM) simulations and quantitative structure-activity relationship (SAR) approaches, we propose a model for the xanthine-UapA complex where the substrate binding site is formed by the polar side chains of residues E356 (TMS8) and Q408 (TMS10) and the backbones of A407 (TMS10) and F155 (TMS3). In addition, our model shows several polar interactions between TMS1-TMS10, TMS1-TMS3, TMS8-TMS10, which seem critical for UapA transport activity. Using extensive docking calculations we identify a cytoplasm-facing substrate trajectory (D360, A363, G411, T416, R417, V463 and A469) connecting the proposed substrate binding site with the cytoplasm, as well as, a possible outward-facing gate leading towards the substrate major binding site. Most importantly, re-evaluation of the plethora of available and analysis of a number of herein constructed UapA mutations strongly supports the UapA structural model. Furthermore, modeling and docking approaches with mammalian NAT homologues provided a molecular rationale on how specificity in this family of carriers might be determined, and further support the importance of selectivity gates acting independently from the major central substrate binding site