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Updated: Jul 1, 2026

An All-Human Hepatic Culture System for Drug Development Applications
Published on: October 20, 2023
Structural requirements for drug inhibition of the liver specific human organic cation transport protein 1
Gustav Ahlin1, Johan Karlsson, Jenny M Pedersen
1Department of Pharmacy, Uppsala University, Uppsala, Sweden.
Abstract:
The liver-specific organic cation transport protein (OCT1; SLC22A1) transports several cationic drugs including the antidiabetic drug metformin and the anticancer agents oxaliplatin and imatinib. In this study, we explored the chemical space of registered oral drugs with the aim of studying the inhibition pattern of OCT1 and of developing predictive computational models of OCT1 inhibition. In total, 191 structurally diverse compounds were examined in HEK293-OCT1 cells. The assay identified 47 novel inhibitors and confirmed 15 previously known inhibitors. The enrichment of OCT1 inhibitors was seen in several drug classes including antidepressants. High lipophilicity and a positive net charge were found to be the key physicochemical properties for OCT1 inhibition, whereas a high molecular dipole moment and many hydrogen bonds were negatively correlated to OCT1 inhibition. The data were used to generate OPLS-DA models for OCT1 inhibitors; the final model correctly predicted 82% of the inhibitors and 88% of the noninhibitors of the test set.
Insights
Researchers identified key properties for organic cation transport protein 1 (OCT1) inhibition, finding high lipophilicity and positive charge are crucial. Predictive models were developed to identify OCT1 inhibitors among registered oral drugs.
Area of Science:
- Pharmacology
- Drug Discovery
- Computational Chemistry
Background:
- The liver-specific organic cation transport protein 1 (OCT1; SLC22A1) is crucial for transporting various cationic drugs, including metformin, oxaliplatin, and imatinib.
- Understanding OCT1 inhibition is vital for optimizing drug efficacy and minimizing adverse effects.
Purpose of the Study:
- To investigate the inhibition patterns of OCT1 using a diverse set of registered oral drugs.
- To develop predictive computational models for identifying OCT1 inhibitors.
Main Methods:
- A total of 191 structurally diverse compounds were screened for OCT1 inhibition in HEK293-OCT1 cells.
- Physicochemical properties of inhibitors and non-inhibitors were analyzed.
- Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) models were generated.
Main Results:
- The study identified 47 novel OCT1 inhibitors and confirmed 15 known inhibitors.
- Drug classes such as antidepressants showed enrichment of OCT1 inhibitors.
- High lipophilicity and positive net charge were identified as key physicochemical drivers of OCT1 inhibition.
- High molecular dipole moment and numerous hydrogen bonds were negatively correlated with OCT1 inhibition.
- The final OPLS-DA model achieved 82% accuracy in predicting inhibitors and 88% in predicting non-inhibitors.
Conclusions:
- Physicochemical properties like lipophilicity and charge are critical determinants of OCT1 inhibition.
- Predictive computational models can effectively identify potential OCT1 inhibitors among existing drug compounds.
- These findings aid in the rational design and selection of drugs targeting OCT1-mediated transport.
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