Development and Validation of a Computational Model Ensemble for the Early Detection of BCRP/ABCG2 Substrates during the Drug Design Stage

Gantner, Melisa Edith; Peroni, Roxana N.; Morales, Juan Francisco; Villalba, María Luisa; Ruiz, María Esperanza; Talevi, Alan

doi:10.1021/acs.jcim.7b00016

Cited by 17 publications

(10 citation statements)

References 89 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Hierarchical clustering allowed deciding on an initial partition of n molecules into k groups, and this preliminary clustering was then optimized through the non-hierarchical procedure, as suggested by Everitt et al (2011). We have previously used this combined approach for representative dataset partitioning, with good results (Alberca et al, 2016, 2018; Gantner et al, 2017). The clustering procedure was performed separately for the ACTIVE and INACTIVE categories.…”

Section: Methodsmentioning

confidence: 99%

In silico Guided Drug Repurposing: Discovery of New Competitive and Non-competitive Inhibitors of Falcipain-2

et al. 2019

Self Cite

View full text Add to dashboard Cite

Malaria is among the leading causes of death worldwide. The emergence of Plasmodium falciparum resistant strains with reduced sensitivity to the first line combination therapy and suboptimal responses to insecticides used for Anopheles vector management have led to renewed interest in novel therapeutic options. Here, we report the development and validation of an ensemble of ligand-based computational models capable of identifying falcipain-2 inhibitors, and their subsequent application in the virtual screening of DrugBank and Sweetlead libraries. Among four hits submitted to enzymatic assays, two (odanacatib, an abandoned investigational treatment for osteoporosis and bone metastasis, and the antibiotic methacycline) confirmed inhibitory effects on falcipain-2, with Ki of 98.2 nM and 84.4 μM. Interestingly, Methacycline proved to be a non-competitive inhibitor (α = 1.42) of falcipain-2. The effects of both hits on falcipain-2 hemoglobinase activity and on the development of P. falciparum were also studied.

show abstract

Section: Methodsmentioning

confidence: 99%

In silico Guided Drug Repurposing: Discovery of New Competitive and Non-competitive Inhibitors of Falcipain-2

et al. 2019

Self Cite

View full text Add to dashboard Cite

show abstract

“…This work is the first report to establish machine learning models using efflux activity data of MDCK-MDR1 from the NIH-supplied cell line. In addition, there are few reports about quantitative prediction of the efflux transporter BCRP by in silico modeling methods, although several qualitative classification models have been reported (33)(34)(35)(36)(37)(38)(39). The in vitro prediction results of the MDR1 and the BCRP efflux assays indicate that the predictivity of MDR1 efflux activity was higher than the predictivity of BCRP efflux activity (Table I).…”

Section: Discussionmentioning

confidence: 99%

Direct Comparison of the Prediction of the Unbound Brain-to-Plasma Partitioning Utilizing Machine Learning Approach and Mechanistic Neuropharmacokinetic Model

Kosugi

Mizuno

Santos

et al. 2021

AAPS J

View full text Add to dashboard Cite

The mechanistic neuropharmacokinetic (neuroPK) model was established to predict unbound brain-to-plasma partitioning (Kp,uu,brain) by considering in vitro efflux activities of multiple drug resistance 1 (MDR1) and breast cancer resistance protein (BCRP). Herein, we directly compare this model to a computational machine learning approach utilizing physicochemical descriptors and efflux ratios of MDR1 and BCRP-expressing cells for predicting Kp,uu,brain in rats. Two different types of machine learning techniques, Gaussian processes (GP) and random forest regression (RF), were assessed by the time and cluster-split validation methods using 640 internal compounds. The predictivity of machine learning models based on only molecular descriptors in the time-split dataset performed worse than the cluster-split dataset, whereas the models incorporating MDR1 and BCRP efflux ratios showed similar predictivity between time and cluster-split datasets. The GP incorporating MDR1 and BCRP in the time-split dataset achieved the highest correlation (R2 = 0.602). These results suggested that incorporation of MDR1 and BCRP in machine learning is beneficial for robust and accurate prediction. Kp,uu,brain prediction utilizing the neuroPK model was significantly worse compared to machine learning approaches for the same dataset. We also investigated the predictivity of Kp,uu,brain using an external independent test set of 34 marketed drugs. Compared to machine learning models, the neuroPK model showed better predictive performance with R2 of 0.577. This work demonstrates that the machine learning model for Kp,uu,brain achieves maximum predictive performance within the chemical applicability domain, whereas the neuroPK model is applicable more widely beyond the chemical space covered in the training dataset.

show abstract

“…The mutual interactions between CP and CPC are likely to induce conformational changes of BCRP and could allosterically affect its function. Although inter-inhibitor interaction is a less understood area and the high-resolution 3D structure of BCRP has been unavailable, the development of ligand-based computational methods and homology models seems to be a feasible way to investigate the complex interaction mechanism ( Matsson et al, 2007 ; Gantner et al, 2017 ).…”

Section: Discussionmentioning

confidence: 99%

Evaluation of a Clinically Relevant Drug–Drug Interaction Between Rosuvastatin and Clopidogrel and the Risk of Hepatotoxicity

Chen

et al. 2021

Front. Pharmacol.

View full text Add to dashboard Cite

Purpose: The combination therapy of rosuvastatin (RSV) and the platelet inhibitor clopidogrel (CP) is widely accepted in the management of cardiovascular diseases. The objective of the present study was to identify the mechanism of RSV–CP DDI and evaluate the risk of hepatotoxicity associated with the concomitant use of CP.Methods: We first studied the effect of CP and its major circulating metabolite, carboxylic acid metabolite (CPC), on RSV transport by overexpressing cells and membrane vesicles. Second, we investigated whether a rat model could replicate this DDI and then be used to conduct mechanistic studies and assess the risk of hepatotoxicity. Then, cytotoxicity assay in hepatocytes, biochemical examination, and histopathology were performed to measure the magnitude of liver injury in the presence and absence of DDI.Results: CP inhibited OATP1B1-mediated transport of RSV with an IC50 value of 27.39 μM. CP and CPC inhibited BCRP-mediated RSV transport with IC50 values of <0.001 and 5.96 μM, respectively. The CP cocktail (0.001 μM CP plus 2 μM CPC) significantly inhibited BCRP-mediated transport of RSV by 26.28%. Multiple p.o. doses of CP significantly increased intravenous RSV plasma AUC0-infinity by 76.29% and decreased intravenous RSV CL by 42.62%. Similarly, multiple p.o. doses of CP significantly increased p.o. RSV plasma AUC0-infinity by 87.48% and decreased p.o. RSV CL by 43.27%. CP had no effect on cell viability, while RSV exhibited dose-dependent cytotoxicity after 96 h incubation. Co-incubation of 100 μM CP and RSV for 96 h significantly increased intracellular concentrations and cell-to-medium concentration ratios of RSV and reduced hepatocyte viability. Histological evaluation of liver specimens showed patterns of drug-induced liver injury. Cholestasis was found in rats in the presence of DDI.Conclusion: CP is not a clinically relevant inhibitor for OATP1B1 and OATP1B3. The primary mechanism of RSV–CP DDI can be attributed to the inhibition of intestinal BCRP by CP combined with the inhibition of hepatic BCRP by CPC. The latter is likely to be more clinically relevant and be a contributing factor for increased hepatotoxicity in the presence of DDI.

show abstract

Development and Validation of a Computational Model Ensemble for the Early Detection of BCRP/ABCG2 Substrates during the Drug Design Stage

Cited by 17 publications

References 89 publications

In silico Guided Drug Repurposing: Discovery of New Competitive and Non-competitive Inhibitors of Falcipain-2

In silico Guided Drug Repurposing: Discovery of New Competitive and Non-competitive Inhibitors of Falcipain-2

Direct Comparison of the Prediction of the Unbound Brain-to-Plasma Partitioning Utilizing Machine Learning Approach and Mechanistic Neuropharmacokinetic Model

Evaluation of a Clinically Relevant Drug–Drug Interaction Between Rosuvastatin and Clopidogrel and the Risk of Hepatotoxicity

Contact Info

Product

Resources

About