Structure-based identification of dual ligands at the A2AR and PDE10A with anti-proliferative effects in lung cancer cell-lines.

Enhanced/prolonged cAMP signalling has been suggested as a suppressor of cancer proliferation. Interestingly, two key modulators that elevate cAMP, the A2A receptor (A2AR) and phosphodiesterase 10A (PDE10A), are differentially co-expressed in various types of non-small lung cancer (NSCLC) cell-lines. Thus, finding dual-target compounds, which are simultaneously agonists at the A2AR whilst also inhibiting PDE10A, could be a novel anti-proliferative approach. Using ligand- and structure-based modelling combined with MD simulations (which identified Val84 displacement as a novel conformational descriptor of A2AR activation), a series of known PDE10A inhibitors were shown to dock to the orthosteric site of the A2AR. Subsequent in-vitro analysis confirmed that these compounds bind to the A2AR and exhibit dual-activity at both the A2AR and PDE10A. Furthermore, many of the compounds exhibited promising anti-proliferative effects upon NSCLC cell-lines, which directly correlated with the expression of both PDE10A and the A2AR. Thus, we propose a structure-based methodology, which has been validated in in-vitro binding and functional assays, and demonstrated a promising therapeutic value.

Synthesis of CC, CN coupled novel substituted dibutyl benzothiazepinone derivatives and evaluation of their thrombin inhibitory activity.

The formation of a thrombus is a key event in thromboembolic disorders, that contribute to high mortality and morbidity in affected patients. In the present study, we synthesized a library of novel substituted 3,3-dibutyl-8-methoxy-2,3-dihydrobenzo [b] [1,4] thiazepin-4(5H)-one derivatives which were tested for their platelet aggregation and thrombin inhibitory activity. Among the tested compounds, 3,3-dibutyl-7-(2-chlorophenyl)-8-methoxy-2,3-dihydrobenzo[b] [1,4]thiazepin-4(5H)-one (DCT) displayed the maximum thrombin inhibition with an IC50 value of 3.85 µM and thus DCT was chosen for further studies. Next, the effect of DCT on primary hemostasis was evaluated using agonist-induced platelet aggregation model. The lead compound inhibited the collagen- or ADP- or thrombin-induced platelet aggregation in a dose-dependent manner. Furthermore, DCT prolonged the process of clot formation when evaluating plasma re-calcification time (320 ±â€¯11 sec at 5 µg DCT), activated partial thromboplastin time (58.0 ±â€¯0.01 sec at 2 µg), and prothrombin time (14.7 ±â€¯0.01 sec at 5 µg). Molecular docking studies suggested that the benzothiazepinones evaluated here consistently display hydrogen bonding with Ser214 of thrombin, which is similar to that of the co-crystallized ligand (1-(2R)-2-amino-3-phenyl-propanoyl-N-(2,5dichlorophenyl)methylpyrrolidine-2-carboxamide). DCT displayed additional hydrogen bonding to Ser195 and π-π interactions between its methoxyphenyl groups and Trp60, thereby providing a structural rationale for the observed biological effect.

Structure-based design of allosteric calpain-1 inhibitors populating a novel bioactivity space.

Dimeric calpains constitute a promising therapeutic target for many diseases such as cardiovascular, neurodegenerative and ischaemic disease. The discovery of selective calpain inhibitors, however, has been extremely challenging. Previously, allosteric inhibitors of calpains, such as PD150606, which included a specific α-mercaptoacrylic acid sub-structure, were reported to bind to the penta-EF hand calcium binding domain, PEF(S) of calpain. Although these are selective to calpains over other cysteine proteases, their mode of action has remained elusive due to their ability to inhibit the active site domain with and without the presence of PEF(S), with similar potency. These findings have led to the question of whether the inhibitory response can be attributed to an allosteric mode of action or alternatively to inhibition at the active site. In order to address this problem, we report a structure-based virtual screening protocol as a novel approach for the discovery of PEF(S) binders that populate a novel chemical space. We have identified compound 1, Vidupiprant, which is shown to bind to the PEF(S) domain by the TNS displacement method, and it exhibited specificity in its allosteric mode of inhibition. Compound 1 inhibited the full-length calpain-1 complex with a higher potency (IC50 = 7.5 µM) than the selective, cell-permeable non-peptide calpain inhibitor, PD150606 (IC50 = 19.3 µM), where the latter also inhibited the active site domain in the absence of PEF(S) (IC50 = 17.8 µM). Hence the method presented here has identified known compounds with a novel allosteric mechanism for the inhibition of calpain-1. We show for the first time that the inhibition of enzyme activity can be attributed to an allosteric mode of action, which may offer improved selectivity and a reduced side-effects profile.

Synthesis of Structurally Diverse N-Substituted Quaternary-Carbon-Containing Small Molecules from α,α-Disubstituted Propargyl Amino Esters.

N-containing quaternary stereocenters represent important motifs in medicinal chemistry. However, due to their inherently sterically hindered nature, they remain underrepresented in small molecule screening collections. As such, the development of synthetic routes to generate small molecules that incorporate this particular feature are highly desirable. Herein, we describe the diversity-oriented synthesis (DOS) of a diverse collection of structurally distinct small molecules featuring this three-dimensional (3D) motif. The subsequent derivatisation and the stereoselective synthesis exemplified the versatility of this strategy for drug discovery and library enrichment. Chemoinformatic analysis revealed the enhanced sp3 character of the target library and demonstrated that it represents an attractive collection of biologically diverse small molecules with high scaffold diversity.

Orthologue chemical space and its influence on target prediction.

Motivation: In silico approaches often fail to utilize bioactivity data available for orthologous targets due to insufficient evidence highlighting the benefit for such an approach. Deeper investigation into orthologue chemical space and its influence toward expanding compound and target coverage is necessary to improve the confidence in this practice. Results: Here we present analysis of the orthologue chemical space in ChEMBL and PubChem and its impact on target prediction. We highlight the number of conflicting bioactivities between human and orthologues is low and annotations are overall compatible. Chemical space analysis shows orthologues are chemically dissimilar to human with high intra-group similarity, suggesting they could effectively extend the chemical space modelled. Based on these observations, we show the benefit of orthologue inclusion in terms of novel target coverage. We also benchmarked predictive models using a time-series split and also using bioactivities from Chemistry Connect and HTS data available at AstraZeneca, showing that orthologue bioactivity inclusion statistically improved performance. Availability and implementation: Orthologue-based bioactivity prediction and the compound training set are available at www.github.com/lhm30/PIDGINv2. Contact: ab454@cam.ac.uk. Supplementary information: Supplementary data are available at Bioinformatics online.

Computer-aided design of multi-target ligands at A1R, A2AR and PDE10A, key proteins in neurodegenerative diseases.

Compounds designed to display polypharmacology may have utility in treating complex diseases, where activity at multiple targets is required to produce a clinical effect. In particular, suitable compounds may be useful in treating neurodegenerative diseases by promoting neuronal survival in a synergistic manner via their multi-target activity at the adenosine A1 and A2A receptors (A1R and A2AR) and phosphodiesterase 10A (PDE10A), which modulate intracellular cAMP levels. Hence, in this work we describe a computational method for the design of synthetically feasible ligands that bind to A1 and A2A receptors and inhibit phosphodiesterase 10A (PDE10A), involving a retrosynthetic approach employing in silico target prediction and docking, which may be generally applicable to multi-target compound design at several target classes. This approach has identified 2-aminopyridine-3-carbonitriles as the first multi-target ligands at A1R, A2AR and PDE10A, by showing agreement between the ligand and structure based predictions at these targets. The series were synthesized via an efficient one-pot scheme and validated pharmacologically as A1R/A2AR-PDE10A ligands, with IC50 values of 2.4-10.0 µM at PDE10A and Ki values of 34-294 nM at A1R and/or A2AR. Furthermore, selectivity profiling of the synthesized 2-amino-pyridin-3-carbonitriles against other subtypes of both protein families showed that the multi-target ligand 8 exhibited a minimum of twofold selectivity over all tested off-targets. In addition, both compounds 8 and 16 exhibited the desired multi-target profile, which could be considered for further functional efficacy assessment, analog modification for the improvement of selectivity towards A1R, A2AR and PDE10A collectively, and evaluation of their potential synergy in modulating cAMP levels.

Routes to fractality and entropy in Liesegang systems.

Liesegang bands are formed when solutions of co-precipitate ions interdiffuse in a 1D gel matrix. In a recent study [R. F. Sultan, Acta. Mech. Sin. 27, 119 (2011)], Liesegang patterns have been characterized as fractal structures. In addition to experimentally obtained patterns, geometric Liesegang patterns were constructed in conformity with the well-known empirical laws. Both mathematical fractal dimensions and box count dimensions for images of PbF2 and PbI2 Liesegang patterns have been calculated. Liesegang patterns can also be described by the entropy state function, and categorized as more or less ordered structures. We revisit the relation between entropy and fractal dimension, and apply it to simulated geometrical Liesegang patterns. We have resort to three different routes for the estimation of the entropy of a Liesegang pattern. The HarFA software enabled the calculation of the Hausdorff dimension and the topological entropy, then the information dimension and the Shannon entropy. In a third pathway, analytical calculations were carried out by estimating the probability of occurrence of a fractal element or coverage. The product of Shannon entropy and Boltzmann constant yields the thermodynamic entropy. The values for PbF2 and PbI2 Liesegang patterns attained the order of magnitude of the reported Third Law entropies, but yet remained lower, in conformity with the more ordered Liesegang structures.