scholarly journals Structure-Activity Relationship Analysis of Analogs of Rhosin, a RhoA Inhibitor, Reveals a New Generation of Improved Antiplatelet Agents

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 3989-3989
Author(s):  
Akhila Dandamudi ◽  
William Seibel ◽  
Huzoor Akbar ◽  
Yi Zheng

Abstract Platelet activation and aggregation play a key role in mediating hemostasis and thrombosis. The antiplatelet therapies currently available in the market are associated with a high risk of hemorrhage and are mostly irreversible in suppressing platelet activity; hence, there is a need to develop better therapeutic agents. Previous genetic and pharmacological studies have implicated the small GTPase RhoA in multiple platelet signaling pathways. We devised a lead RhoA activity-specific inhibitor, Rhosin/G04, based on the structure-function relationship of RhoA interaction with its activator, guanine nucleotide exchange factor (GEF) (Figure 1A). Rhosin/G04 binds to RhoA directly with micromolar affinity at a surface groove that is essential for GEF recognition and blocks GEF-mediated GTP loading to RhoA. Rhosin/G04 inhibits platelet spreading on fibrinogen and thrombin-induced platelet aggregation, mimicking effects of RhoA gene targeting. In the current work, we have utilized the inhibitory activity of G04 for platelet activation and its biochemical activity to define its structure-activity relationship (SAR) and to understand its mechanism of action in an effort to improve efficacy and druggability. The structure of G04 in a groove of RhoA interaction was hypothesized based on the docking studies using Molsoft ICM-Pro. Cincinnati Children's Hospital Medical Center's compound library of over 360,000 chemicals was scanned for G04 analogs by similarity and substructure searches. In the initial screen, a human platelet aggregation assay was performed at both a low concentration (1 µg/ml) and a high concentration (5 µg/ml) of collagen. The first round similarity search resulted in a set of 7 compounds (Set-1), from which, compound 177629 showed significantly enhanced potency relative to G04 (Figure 1B). The second round of similarity searches for compounds more closely related to 177629 (Set-2) identified 14 compounds. The third-round search for other related compounds (Set-3) led to 9 additional compounds that add to the understanding of the SAR. The compounds that showed enhanced antiplatelet activity were examined for their potency and selectivity in in vitro biochemical binding assays and in suppressing RhoA-GTP formation and downstream phosphorylation of myosin light chain (p-MLC) signaling in platelets. The active compounds were further examined for their anti-platelet activities under diverse stimuli including thrombin, ADP, U46619 (a stable thromboxane receptor agonist), and arachidonic acid. The most active compounds from Set-1, Set-2, and Set-3 inhibited platelet aggregation by at least 70% and showed IC 50 values below 6 µM. Of these compounds, 12 showed significantly greater potency than the initial compound, G04. The most active compounds were 177618, 177619, 177628, 177629, 177633, and 177634. These compounds specifically inhibited RhoA activity and blocked p-MLC. SAR analyses led us to believe that the quinoline is optimally attached to the hydrazine at the 4-position. The halogen (choloro- or trifluoromethyl-) substitution at the 7- or 8- position improved activity, and the 7- position may be slightly favored. The aryl group is considerably variable with similar potency between the indole, methylphenyl, and dichlorophenyl- groups. Rhosin/G04 is the R enantiomer (i.e. Rhosin is R-G04), so its S enantiomer, S-G04 was also evaluated (Figure 1C). S-G04 is significantly more potent than R-G04 in inhibiting collagen-stimulated RhoA-GTP formation and aggregation of platelets, and its effect is completely reversible by washing the platelets. Finally, R-G04 and S-G04 showed differential inhibition of arachidonic acid and U46619 stimulated primary and secondary aggregation, highlighting the potential utilities of the inhibitors in dissecting different platelet activation mechanisms. S-G04 is active in inhibiting thrombin, ADP, U46619, and arachidonic acid-mediated platelet activation at submicromolar concentration, suggesting a broad role of RhoA signaling in integrating platelet signal cross talk. In summary, evaluation of Rhosin/R-G04 analogs in a platelet activity screen identified a new generation of improved small-molecule RhoA inhibitors, including an enantiomer with significantly improved efficacy. These analog studies of novel anti-platelet agents provide a new approach to effectively and reversibly manipulate platelet activities. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

2019 ◽  
Vol 15 (1) ◽  
pp. 17-27 ◽  
Author(s):  
Elda Meta ◽  
Chiara Brullo ◽  
Michele Tonelli ◽  
Scott G. Franzblau ◽  
Yuehong Wang ◽  
...  

Background: We screened a large library of differently decorated imidazo-pyrazole and pyrazole derivatives as possible new antitubercular agents and this preliminary screening showed that many compounds are able to totally inhibit Mycobacterium growth (>90 %). Among the most active compounds, we selected some new possible hits based on their similarities and, at the same time, on their novelty with respect to the pipeline drugs. </P><P> Methods: In order to increase the potency and obtain more information about structure-activity relationship (SAR), we designed and synthesized three new series of compounds (2a–e, 3a–e, and 4a–l). Conclusion: Performed tests confirmed that both new pyrazoles and imidazo-pyrazoles could represent a new starting point to obtain more potent compounds and further work is now underway to identify the protein targets of this new class of anti-TB agents.


2017 ◽  
Vol 40 (5) ◽  
pp. 1520-1528 ◽  
Author(s):  
Yi Chang ◽  
Wen-Hsien Hsu ◽  
Wen-Bin Yang ◽  
Thanasekaran Jayakumar ◽  
Tzu-Yin Lee ◽  
...  

Molecules ◽  
2020 ◽  
Vol 25 (4) ◽  
pp. 800
Author(s):  
Cristian Ortiz ◽  
Fernando Echeverri ◽  
Sara Robledo ◽  
Daniela Lanari ◽  
Massimo Curini ◽  
...  

In continuation of our efforts to identify promising antileishmanial agents based on the chroman scaffold, we synthesized several substituted 2H-thiochroman derivatives, including thiochromenes, thichromanones and hydrazones substituted in C-2 or C-3 with carbonyl or carboxyl groups. Thirty-two compounds were thus obtained, characterized, and evaluated against intracellular amastigotes of Leishmania (V) panamensis. Twelve compounds were active, with EC50 values lower than 40 µM, but only four compounds displayed the highest antileishmanial activity, with EC50 values below 10 µM; these all compounds possess a good Selectivity Index > 2.6. Although two active compounds were thiochromenes, a clear structure-activity relationship was not detected since each active compound has a different substitution pattern.


2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Gabriel Idakwo ◽  
Sundar Thangapandian ◽  
Joseph Luttrell ◽  
Yan Li ◽  
Nan Wang ◽  
...  

Abstract The specificity of toxicant-target biomolecule interactions lends to the very imbalanced nature of many toxicity datasets, causing poor performance in Structure–Activity Relationship (SAR)-based chemical classification. Undersampling and oversampling are representative techniques for handling such an imbalance challenge. However, removing inactive chemical compound instances from the majority class using an undersampling technique can result in information loss, whereas increasing active toxicant instances in the minority class by interpolation tends to introduce artificial minority instances that often cross into the majority class space, giving rise to class overlapping and a higher false prediction rate. In this study, in order to improve the prediction accuracy of imbalanced learning, we employed SMOTEENN, a combination of Synthetic Minority Over-sampling Technique (SMOTE) and Edited Nearest Neighbor (ENN) algorithms, to oversample the minority class by creating synthetic samples, followed by cleaning the mislabeled instances. We chose the highly imbalanced Tox21 dataset, which consisted of 12 in vitro bioassays for > 10,000 chemicals that were distributed unevenly between binary classes. With Random Forest (RF) as the base classifier and bagging as the ensemble strategy, we applied four hybrid learning methods, i.e., RF without imbalance handling (RF), RF with Random Undersampling (RUS), RF with SMOTE (SMO), and RF with SMOTEENN (SMN). The performance of the four learning methods was compared using nine evaluation metrics, among which F1 score, Matthews correlation coefficient and Brier score provided a more consistent assessment of the overall performance across the 12 datasets. The Friedman’s aligned ranks test and the subsequent Bergmann-Hommel post hoc test showed that SMN significantly outperformed the other three methods. We also found that a strong negative correlation existed between the prediction accuracy and the imbalance ratio (IR), which is defined as the number of inactive compounds divided by the number of active compounds. SMN became less effective when IR exceeded a certain threshold (e.g., > 28). The ability to separate the few active compounds from the vast amounts of inactive ones is of great importance in computational toxicology. This work demonstrates that the performance of SAR-based, imbalanced chemical toxicity classification can be significantly improved through the use of data rebalancing.


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