ArticleMolecules (Basel, Switzerland)2015
A Combined Molecular Docking/Dynamics Approach to Probe the Binding Mode of Cancer Drugs with Cytochrome P450 3A4.
Article in Molecules (Basel, Switzerland), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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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
8 citing papers in PubMed, 27 citations in OpenAlex.
- Interactions of Linalool and Linalyl Acetate with Selected Dog Cytochrome P450 (CYP) Proteins Identified by In Silico Drug Discovery Followed by Molecular Docking Analysis.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Integrated Network Pharmacology, Molecular Modeling, LC-MS Profiling, and Semisynthetic Approach for the Roots ofACS omega · 2025Article
- Article
- Anthracycline derivatives inhibit cardiac CYP2J2.Journal of inorganic biochemistry · 2022Article
- Article
- The Multifarious Link between Cytochrome P450s and Cancer.Oxidative medicine and cellular longevity · 2020Review
- Molecular Dynamics Simulation Framework to Probe the Binding Hypothesis of CYP3A4 Inhibitors.International journal of molecular sciences · 2019Article
- Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cytarabine, daunorubicin, doxorubicin and vincristine are clinically used for combinatorial therapies of cancers in different combinations. However, the knowledge about the interaction of these drugs with the metabolizing enzyme cytochrome P450 is limited. Therefore, we utilized computational methods to predict and assess the drug-binding modes. In this study, we performed docking, MD simulations and free energy landscape analysis to understand the drug-enzyme interactions, protein domain motions and the most populated free energy minimum conformations of the docked protein-drug complexes, respectively. The outcome of docking and MD simulations predicted the productive, as well as the non-productive binding modes of the selected drugs. Based on these interaction studies, we observed that S119, R212 and R372 are the major drug-binding residues in CYP3A4. The molecular mechanics Poisson-Boltzmann surface area analysis revealed the dominance of hydrophobic forces in the CYP3A4-drug association. Further analyses predicted the residues that may contain favorable drug-specific interactions. The probable binding modes of the cancer drugs from this study may extend the knowledge of the protein-drug interaction and pave the way to design analogs with reduced toxicity. In addition, they also provide valuable insights into the metabolism of the cancer drugs.
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