ReviewComputational and structural biotechnology journal2019
Current Advances in Studying Clinically Relevant Transporters of the Solute Carrier (SLC) Family by Connecting Computational Modeling and Data Science.
Review in Computational and structural biotechnology journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed, 28 citations in OpenAlex.
- Age-adjusted machine learning identifies facial skin microbes associated with skin quality among Korean women.mSystems · 2026Article
- New Machine Learning Models for Predicting the Organic Cation Transporters OCT1, OCT2, and OCT3 Uptake.ACS omega · 2025Article
- MONSTROUS: a web-based chemical-transporter interaction profiler.Frontiers in pharmacology · 2025Article
- ATP-Binding Cassette and Solute Carrier Transporters: Understanding Their Mechanisms and Drug Modulation Through Structural and Modeling Approaches.Pharmaceuticals (Basel, Switzerland) · 2024Review
- The Neglected Sibling: NLRP2 Inflammasome in the Nervous System.Aging and disease · 2024Review
- Ligand- and Structure-based Approaches for Transmembrane Transporter Modeling.Current drug research reviews · 2024Review
- The influence of methotrexate-related transporter and metabolizing enzyme gene polymorphisms on peri-engraftment syndrome and graft-versus-host disease after haplo-hematopoietic stem cell transplantation in pediatric patients with malignant hematological diseases.Frontiers in immunology · 2023Article
- Pharmacoproteomics of Brain Barrier Transporters and Substrate Design for the Brain Targeted Drug Delivery.Pharmaceutical research · 2022Review
- Molecular Properties of Drugs Handled by Kidney OATs and Liver OATPs Revealed by Chemoinformatics and Machine Learning: Implications for Kidney and Liver Disease.Pharmaceutics · 2021Article
- Data-Driven Ensemble Docking to Map Molecular Interactions of Steroid Analogs with Hepatic Organic Anion Transporting Polypeptides.Journal of chemical information and modeling · 2021Article
- Wuzhi capsule increased systemic exposure to methotrexate by inhibiting the expression of OAT1/3 and P-gp.Annals of translational medicine · 2021Article
- An Overview of Cell-Based Assay Platforms for the Solute Carrier Family of Transporters.Frontiers in pharmacology · 2021Review
- Antidepressant efficacy of a selective organic cation transporter blocker in a mouse model of depression.Molecular psychiatry · 2020Article
- The solute carrier transporters and the brain: Physiological and pharmacological implications.Asian journal of pharmaceutical sciences · 2020Review
- Computational Assessment of the Pharmacological Profiles of Degradation Products of Chitosan.Frontiers in bioengineering and biotechnology · 2019Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Organic anion and cation transporting proteins (OATs, OATPs, and OCTs), as well as the Multidrug and Toxin Extrusion (MATE) transporters of the Solute Carrier (SLC) family are playing a pivotal role in the discovery and development of new drugs due to their involvement in drug disposition, drug-drug interactions, adverse drug effects and related toxicity. Computational methods to understand and predict clinically relevant transporter interactions can provide useful guidance at early stages in drug discovery and design, especially if they include contemporary data science approaches. In this review, we summarize the current state-of-the-art of computational approaches for exploring ligand interactions and selectivity for these drug (uptake) transporters. The computational methods discussed here by highlighting interesting examples from the current literature are ranging from semiautomatic data mining and integration, to ligand-based methods (such as quantitative structure-activity relationships, and combinatorial pharmacophore modeling), and finally structure-based methods (such as comparative modeling, molecular docking, and molecular dynamics simulations). We are focusing on promising computational techniques such as fold-recognition methods, proteochemometric modeling or techniques for enhanced sampling of protein conformations used in the context of these ADMET-relevant SLC transporters with a special focus on methods useful for studying ligand selectivity.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.