Target Hop Research Articles

Pharmacological characterization of second generation FXR agonists as effective EphA2 antagonists: A successful application of target hopping approach

It is well demonstrated the key role of Eph-ephrin system, specifically of EphA2 receptor, in supporting tumor growth, invasion, metastasis and neovascularization. We previously identified FXR agonists as eligible antagonists of Eph-ephrin system. Herein we characterize new commercially available FXR (Farnesoid X Receptor) agonists as potential Eph ligands including Cilofexor, Nidufexor, Tropifexor, Turofexorate isopropyl and Vonafexor. Our exploration based on molecular modelling investigations and binding assays shows that Cilofexor binds specifically and reversibly to EphA2 receptor with a Ki value in the low micromolar range. Furthermore, Cilofexor interferes with the phosphorylation of EphA2 and the cell retraction and rounding in PC3 prostate cancer cells, both events depending on EphA2 activation. In conclusion, we can confirm that target hopping can be a successful approach to discover new moiety of protein–protein inhibitors.

De Novo Prediction of Drug Targets and Candidates by Chemical Similarity-Guided Network-Based Inference.

Identifying drug–target interactions is a crucial step in discovering novel drugs and for drug repositioning. Network-based methods have shown great potential thanks to the straightforward integration of information from different sources and the possibility of extracting novel information from the graph topology. However, despite recent advances, there is still an urgent need for efficient and robust prediction methods. Here, we present SimSpread, a novel method that combines network-based inference with chemical similarity. This method employs a tripartite drug–drug–target network constructed from protein–ligand interaction annotations and drug–drug chemical similarity on which a resource-spreading algorithm predicts potential biological targets for both known or failed drugs and novel compounds. We describe small molecules as vectors of similarity indices to other compounds, thereby providing a flexible means to explore diverse molecular representations. We show that our proposed method achieves high prediction performance through multiple cross-validation and time-split validation procedures over a series of datasets. In addition, we demonstrate that our method performed a balanced exploration of both chemical ligand space (scaffold hopping) and biological target space (target hopping). Our results suggest robust and balanced performance, and our method may be useful for predicting drug targets, virtual screening, and drug repositioning.

Evaluation of yield and alpha acid content in selected hop varieties

The stability of the agricultural and technological properties of hop varieties over the course of time and under changing climate is essential for both growers and brewers. This study is a typical case of monitoring 12 hop varieties selected from a collection of hop genetic resources, that were evaluated in the years 2009 to 2021. The assessed parameters were the hop yield and content of alpha acids with a focus on the variability/stability of this characteristics. Only the Pilgrim and Target hop varieties from England showed exceptional hop yield above 3 kg/plant. On the other hand, the lowest hop yield was obtained from the Saaz and Bramling Cross hop varieties, i.e. below 1.5 kg/plant. The lowest variability of hop yield – below 30% – was found in the Savinjski Golding, Bramling Cross and Saaz hop varieties. In contrast, the Bobek, Aurora, Pioneer and Phoenix hop varieties demonstrated the highest variability of hop yield, i.e. above 50%. Further, also Target and Phoenix have the highest content of alpha acids, namely 9.68% w/w and 9.56% w/w, respectively. The lowest content of alpha acids was determined in Saaz, which was the only hop variety with an alpha acid content below 3.0% w/w. The Premiant, Target and Aurora hop varieties exhibited a variability of alpha acid content below 20%. On the contrary, the Bobek and Pilgrim hop varieties had the highest variability of alpha acid content, namely above 30%.

ShinyDepMap, a tool to identify targetable cancer genes and their functional connections from Cancer Dependency Map data

Individual cancers rely on distinct essential genes for their survival. The Cancer Dependency Map (DepMap) is an ongoing project to uncover these gene dependencies in hundreds of cancer cell lines. To make this drug discovery resource more accessible to the scientific community, we built an easy-to-use browser, shinyDepMap (https://labsyspharm.shinyapps.io/depmap). shinyDepMap combines CRISPR and shRNA data to determine, for each gene, the growth reduction caused by knockout/knockdown and the selectivity of this effect across cell lines. The tool also clusters genes with similar dependencies, revealing functional relationships. shinyDepMap can be used to (1) predict the efficacy and selectivity of drugs targeting particular genes; (2) identify maximally sensitive cell lines for testing a drug; (3) target hop, that is, navigate from an undruggable protein with the desired selectivity profile, such as an activated oncogene, to more druggable targets with a similar profile; and (4) identify novel pathways driving cancer cell growth and survival.

Discovery of novel tRNA-amino acid dual-site inhibitors against threonyl-tRNA synthetase by fragment-based target hopping

Threonyl-tRNA synthetase (ThrRS) is a key member of the aminoacyl-tRNA synthetase (aaRS) family that plays essential roles in protein biosynthesis, and ThrRS inhibitors have potential in the therapy of multiple diseases, such as microbial infections and cancers. Based on a unique tRNA-amino acid dual-site inhibitory mechanism identified recently with the herb-derived prolyl-tRNA synthetase (ProRS) inhibitor halofuginone (HF), a series of compounds have been designed and synthesized by employing a fragment-based target hopping approach to simultaneously target the tRNAThr and l-threonine binding pockets of ThrRS. Among them, compound 30d showed an IC50 value of 1.4 μM against Salmonella enterica ThrRS (SeThrRS) and MIC values of 16–32 μg/mL against the tested bacterial strains. The cocrystal structure of SeThrRS in complex with 30d was determined at high resolution, revealing that 30d simultaneously occupies both binding pockets for the nucleotide A76 of tRNAThr and l-threonine in an ATP-independent manner, a novel mechanism compared to all other reported ThrRS inhibitors. Our study provides a new class of ThrRS inhibitors, and more importantly, it presents the first experimental evidence that the tRNA-amino acid dual-site inhibitory mechanism could apply to other aaRSs beyond ProRS, thus providing great opportunities for designing new mechanistic inhibitors for aaRS-based therapeutics.

Pharmacological relationships and ligand discovery of G protein-coupled receptors revealed by simultaneous ligand and receptor clustering

Conventional ligand and receptor similarity methods have been extensively used for exposing pharmacological relationships and drug lead discovery. They may in some cases neglect minor relationships useful for target hopping particularly against the remote family members. To complement the conventional methods for capturing these minor relationships, we developed a new method that uses a SLARC (Simultaneous Ligand And Receptor Clustering) 2D map to simultaneously characterize the ligand structural and receptor binding-site sequence relationships of a receptor family. The SLARC maps of the rhodopsin-like GPCR family comprehensively revealed scaffold hopping, target hopping, and multi-target relationships for the ligands of both homologous and remote family members. Their usefulness in new ligand discovery was validated by guiding the prospective discovery of novel indole piperazinylpyrimidine dual-targeting adenosine A2A receptor antagonist and dopamine D2 agonist compounds. The SLARC approach is useful for revealing pharmacological relationships and discovering new ligands at target family levels.

Trisubstituted Imidazoles with a Rigidized Hinge Binding Motif Act As Single Digit nM Inhibitors of Clinically Relevant EGFR L858R/T790M and L858R/T790M/C797S Mutants: An Example of Target Hopping.

The high genomic instability of non-small cell lung cancer tumors leads to the rapid development of resistance against promising EGFR tyrosine kinase inhibitors (TKIs). A recently detected triple mutation compromises the activity of the gold standard third-generation EGFR inhibitors. We have prepared a set of trisubstituted imidazoles with a rigidized 7-azaindole hinge binding motif as a new structural class of EGFR inhibitors by a target hopping approach from p38α MAPK inhibitor templates. On the basis of an iterative approach of docking, compound preparation, biological testing, and SAR interpretation, robust and flexible synthetic routes were established. As a result, we report two reversible inhibitors 11d and 11e of the clinically challenging triple mutant L858R/T790M/C797S with IC50 values in the low nanomolar range. Furthermore, we developed a kinome selective irreversible inhibitor 45a with an IC50 value of 1 nM against the EGFR L858R/T790M double mutant. Target binding kinetics and metabolic stability data are included. These potent mutant EGFR inhibitors may serve as a basis for the development of structurally novel EGFR probes, tools, or candidates.

Computational Drug Repositioning by Target Hopping: A Use Case in Chagas Disease.

Drug repositioning aims to identify novel indications for existing drugs. One approach to repositioning exploits shared binding sites between the drug targets and other proteins. Here, we review the principle and algorithms of such target hopping and illustrate them in Chagas disease, an in Latin America widely spread, but neglected disease. We demonstrate how target hopping recovers known treatments for Chagas disease and predicts novel drugs, such as the antiviral foscarnet, which we predict to target Farnesyl Pyrophosphate Synthase in Trypanosoma cruzi, the causative agent of Chagas disease.

Does providing real-time augmented feedback affect the performance of repeated lower limb loading to exhaustion?

IntroductionThis study aimed to determine whether real-time augmented feedback influenced performance of single-leg hopping to volitional exhaustion. MethodsTwenty-seven healthy, male participants performed single-leg hopping (2.2Hz) with (visual and tactile feedback for a target hop height) or without feedback on a force plate. Repeated measures ANOVA were used to determine differences in vertical stiffness (k), duration of flight (tf) and loading (tl) and vertical height displacement during flight (zf) and loading (zl). A Friedman 2-way ANOVA was performed to compare the percentage of trials between conditions that were maintained at 2.2Hz±5%. Correlations were performed to determine if the effects were similar when providing tactile or visual feedback synchronously with the audible cue. ResultsAugmented feedback resulted in maintenance of the tf, zf and zl between the start and end of the trials compared to hopping with no feedback (p<0.01). With or without feedback there was no change in tl and k from start to end. Without feedback, 21 of 27 participants maintained >70% of total hops at 2.2±5% Hz and this was significantly lower (p=0.01) with tactile (13/27) and visual (15/27) feedback. There was a strong correlation between tactile and visual feedback for duration of hopping cycle (Spearman's r=0.74, p≤0.01). ConclusionFeedback was detrimental to being able to maintain hopping cadence in some participants while other participants were able to achieve the cadence and target hop height. This indicates variability in the ability to use real-time augmented feedback effectively.

Hopscotch—reaching the target hop by hop

Concrete and abstract relation algebras have widespread applications in computer science. One of the most famous is graph theory. Classical relations, however, only reason about connectivity, not about the length of a path between nodes. Generalisations of relation algebra, such as the min-plus algebra, use numbers allowing the treatment of weighted graphs. In this way one can for example determine the length of shortest paths (e.g. Dijkstra's algorithm). In this paper we treat matrices that carry even more information, such as the “next hop” on a path towards a destination. In this way we can use algebra not only for determining the length of paths, but also the concrete path. We show how paths can be reconstructed from these matrices, hop by hop. We further sketch an application for message passing in wireless networks.

Target Hopping as a Useful Tool for the Identification of Novel EphA2 Protein–Protein Antagonists

Lithocholic acid (LCA), a physiological ligand for the nuclear receptor FXR and the G-protein-coupled receptor TGR5, has been recently described as an antagonist of the EphA2 receptor, a key member of the ephrin signalling system involved in tumour growth. Given the ability of LCA to recognize FXR, TGR5, and EphA2 receptors, we hypothesized that the structural requirements for a small molecule to bind each of these receptors might be similar. We therefore selected a set of commercially available FXR or TGR5 ligands and tested them for their ability to inhibit EphA2 by targeting the EphA2-ephrin-A1 interface. Among the selected compounds, the stilbene carboxylic acid GW4064 was identified as an effective antagonist of EphA2, being able to block EphA2 activation in prostate carcinoma cells, in the micromolar range. This finding proposes the "target hopping" approach as a new effective strategy to discover new protein-protein interaction inhibitors.

From the protein's perspective: the benefits and challenges of protein structure-based pharmacophore modeling

Protein structure-based pharmacophore (SBP) models derive the molecular features a ligand must contain to be biologically active by conversion of protein properties to reciprocal ligand space. SBPs improve molecular understanding of ligand–protein interactions and can be used as valuable tools for hit and lead optimization, compound library design, and target hopping.

A Mars hopping vehicle propelled by a radioisotope thermal rocket: thermofluid design and materials selection

Rocket-propelled vehicles capable of travelling a kilometre or more in a ballistic ‘hop’ with propellants acquired from the Martian atmosphere offer the potential for increased mobility and planetary science return compared with conventional rovers. In concept, a radioisotope heat source heats a core or ‘thermal capacitor’, which in turn heats propellant exhausted through a rocket nozzle to provide thrust. A systematic study of the thermodynamics, heat transfer and selection of core materials for a Mars hopper was undertaken. The aim was to advance the motor design and assess technical risks and feasibility. Analytical and numerical motor models were developed; the former to generate thermodynamic performance limits, an ideal hop distance and plot a materials selection chart using simple explicit relations. The numerical model assessed the effect of core configuration and geometry. A hop coefficientChopis shown to characterize the effect of core geometry independently of core material and temperature. The target hop distance of 1 km is shown to be robust. A moderate advantage to pebble-bed cores over a core consisting of straight channels was suggested. High-performance engineering ceramics such as boron carbide offer the longest hop providing the core temperature can be increased significantly above 1200 K.

Factor VIIa inhibitors: Target hopping in the serine protease family using X-ray structure determination

Selective factor VIIa–tissue factor complex (FVIIa/TF) inhibition is regarded as a promising target for developing new anticoagulant drugs. Compound 1 was discovered from focused screening of serine protease-directed compounds from our internal collection. Using parallel synthesis supported by structure-based drug design, we identified peptidemimetic FVIIa/TF inhibitors (compounds 4– 11) containing l-Gln or l-Met as the P2 moiety. However, these compounds lacked the selectivity of other serine proteases in the coagulation cascade, especially thrombin. Further optimization of these compounds was carried out with a focus on the P4 moiety. Among the optimized compounds, 12b– f showed improved selectivity.

Application of comprehensive multidimensional gas chromatography combined with time-of-flight mass spectrometry (GC x GC-TOFMS) for high resolution analysis of hop essential oil.

The selection and quality of hops is a major determinant in beer flavour. Brewers acknowledge that distinctive characteristics of different hop varieties can be traced to the composition of their essential oils. The difficulty in characterising complex mixtures such as hop oil using 1-D chromatography is that many compounds co-elute. With the introduction of comprehensive multidimensional capillary gas chromatography (GC x GC), there is a tremendous improvement in the separation power or peak capacity. Recent work using GC x GC with flame ionisation detection has suggested that there may be over 1,000 compounds in hop oil. This work describes the use of GC x GC combined with TOFMS detection (Leco Pegasus 4D instrument) to analyse Target hop oil. The TOFMS spectral acquisition rate of 60 Hz provided sufficient spectra per peak (2-D peak base width of 0.1-0.2 s) for identification (119 components were identified with 45 previously unreported compounds). When analysing results, an advantage of GC x GC coupled to TOFMS is that 2-D chromatograms can be viewed for individual masses that are characteristic of particular functional groups. This allows the analyst to view the various homologous series of compounds although in certain cases coelution may still be present as shown by the esters with mass 75.