scholarly journals Comparison of Steroid Hormone Hydroxylations by and Docking to Human Cytochromes P450 3A4 and 3A5

2019 ◽  
Vol 22 ◽  
pp. 332-339 ◽  
Author(s):  
Toshiro Niwa ◽  
Kanae Narita ◽  
Ayaka Okamoto ◽  
Norie Murayama ◽  
Hiroshi Yamazaki
Keyword(s):  
Molecular Docking ◽  
Steroid Hormones ◽  
Catalytic Properties ◽  
Cytochromes P450 ◽  
Data Bank ◽  
Substrate Affinity ◽  
Protein Data Bank Code ◽  
Docking Simulations ◽  
Michaelis Constants ◽  
Docking Energy

Purpose: Hydroxylation activity at the 6β-position of steroid hormones (testosterone, progesterone, and cortisol) by human cytochromes P450 (P450 or CYP) 3A4 and CYP3A5 and their molecular docking energy values were compared to understand the catalytic properties of the major forms of human CYP3A, namely, CYP3A4 and CYP3A5. Methods: Testosterone, progesterone, and cortisol 6β-hydroxylation activities of recombinant CYP3A4 and CYP3A5 were determined by liquid chromatography. Docking simulations of these substrates to the heme moiety of reported crystal structures of CYP3A4 (Protein Data Bank code ITQN) and CYP3A5 (6MJM) were conducted. Results: Michaelis constants (Km) for CYP3A5-mediated 6β-hydroxylation of testosterone and progesterone were approximately twice those for CYP3A4, whereas the value for cortisol 6β-hydroxylation mediated by CYP3A5 was similar to the value for that by CYP3A4. Maximal velocities (Vmax) of the three steroid hormones 6β-hydroxylation catalyzed by CYP3A5 were 30%-63% of those by CYP3A4. Thus, Vmax/ Km values of these hormones for CYP3A5 resulted in 22%-31% of those for CYP3A4. The differences in the docking energies between CYP3A4 and CYP3A5 for steroid hormones were slightly correlated to the logarithm of CYP3A5/CYP3A4 ratios for Km values (substrate affinity). Conclusions: The Vmax, rather than Km values, for CYP3A5-mediated 6β-hydroxylation of three steroid hormones were different from those for CYP3A4. Molecular docking simulations could partially explain the differences in the accessibility of substrates to the heme moiety of human CYP3A molecules, resulting in the enzymatic affinity of CYP3A4 and CYP3A5.

In Silico Approach to Inhibition of Tyrosinase by Ascorbic Acid Using Molecular Docking Simulations

2014 ◽  
Vol 14 (12) ◽  
pp. 1469-1472 ◽  
Author(s):  
F. Senol ◽  
M. Khan ◽  
Gurdal Orhan ◽  
Erdem Gurkas ◽  
Ilkay Orhan ◽  
...  
Keyword(s):  
Ascorbic Acid ◽  
Molecular Docking ◽  
In Silico ◽  
Docking Simulations

Virtual Screening, Molecular docking and in-silico ADME-Tox analysis for identification of potential main protease (Mpro) enzyme inhibitors

2020 ◽  
Vol 18 ◽  
Author(s):  
Debadash Panigrahi ◽  
Ganesh Prasad Mishra
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
In Silico ◽  
Data Bank ◽  
Future Research ◽  
Reference Compound ◽  
Unexpected Death ◽  
Main Protease ◽  
In Silico Admet

Objective:: Recent pandemic caused by SARS-CoV-2 described in Wuhan China in December-2019 spread widely almost all the countries of the world. Corona virus (COVID-19) is causing the unexpected death of many peoples and severe economic loss in several countries. Virtual screening based on molecular docking, drug-likeness prediction, and in silico ADMET study has become an effective tool for the identification of small molecules as novel antiviral drugs to treat diseases. Methods:: In the current study, virtual screening was performed through molecular docking for identifying potent inhibitors against Mpro enzyme from the ZINC library for the possible treatment of COVID-19 pandemic. Interestingly, some compounds are identified as possible anti-covid-19 agents for future research. 350 compounds were screened based on their similarity score with reference compound X77 from ZINC data bank and were subjected to docking with crystal structure available of Mpro enzyme. These compounds were then filtered by their in silico ADME-Tox and drug-likeness prediction values. Result:: Out of these 350 screened compounds, 10 compounds were selected based on their docking score and best docked pose in comparison to the reference compound X77. In silico ADME-Tox and drug likeliness predictions of the top compounds were performed and found to be excellent results. All the 10 screened compounds showed significant binding pose with the target enzyme main protease (Mpro) enzyme and satisfactory pharmacokinetic and toxicological properties. Conclusion:: Based on results we can suggest that the identified compounds may be considered for therapeutic development against the COVID-19 virus and can be further evaluated for in vitro activity, preclinical, clinical studies and formulated in a suitable dosage form to maximize their bioavailability.

scholarly journals Discovery of novel potential KIT inhibitors for the treatment of gastrointestinal stromal tumor

2021 ◽  
Vol 16 (1) ◽  
pp. 303-310
Author(s):  
Lili Jiang ◽  
Zhongmin Zhang ◽  
Zhen Wang ◽  
Yong Liu
Keyword(s):  
Molecular Docking ◽  
Gastrointestinal Stromal Tumor ◽  
Pharmacophore Modeling ◽  
Stromal Tumor ◽  
Strong Hydrogen Bond ◽  
Ligand Complex ◽  
Hydrogen Bond Interaction ◽  
Mutant Proteins ◽  
Docking Simulations ◽  
Pharmacophore Models

Abstract Numerous inhibitors of tyrosine-protein kinase KIT, a receptor tyrosine kinase, have been explored as a viable therapy for the treatment of gastrointestinal stromal tumor (GIST). However, drug resistance due to acquired mutations in KIT makes these drugs almost useless. The present study was designed to screen the novel inhibitors against the activity of the KIT mutants through pharmacophore modeling and molecular docking. The best two pharmacophore models were established using the KIT mutants’ crystal complexes and were used to screen the new compounds with possible KIT inhibitory activity against both activation loop and ATP-binding mutants. As a result, two compounds were identified as potential candidates from the virtual screening, which satisfied the potential binding capabilities, molecular modeling characteristics, and predicted absorption, distribution, metabolism, excretion, toxicity (ADMET) properties. Further molecular docking simulations showed that two compounds made strong hydrogen bond interaction with different KIT mutant proteins. Our results indicated that pharmacophore models based on the receptor–ligand complex had excellent ability to screen KIT inhibitors, and two compounds may have the potential to develop further as the future KIT inhibitors for GIST treatment.

scholarly journals An Androsterone‐H 2 @C 60 hybrid: Synthesis, Properties and Molecular Docking Simulations with SARS‐Cov‐2

ChemPlusChem ◽  
2021 ◽  
Author(s):  
Margarita Suárez ◽  
Kamil Makowski ◽  
Reinier Lemos ◽  
Luis Almagro ◽  
Hortensia Rodríguez ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Docking Simulations ◽  
Synthesis Properties

Web Services for Molecular Docking Simulations

2019 ◽  
pp. 221-229 ◽  
Author(s):  
Nelson J. F. da Silveira ◽  
Felipe Siconha S. Pereira ◽  
Thiago C. Elias ◽  
Tiago Henrique
Keyword(s):  
Molecular Docking ◽  
Web Services ◽  
Docking Simulations

scholarly journals In silicoidentification of putativeTrypanosoma cruzienolase inhibitors

2019 ◽  
Author(s):  
Edward A. Valera-Vera ◽  
Melisa Sayé ◽  
Chantal Reigada ◽  
Mariana R. Miranda ◽  
Claudio A. Pereira
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Virtual Screening ◽  
Active Site ◽  
Screening Strategy ◽  
Glycolytic Enzyme ◽  
Docking Simulations ◽  
Enzyme Active Site ◽  
Key Enzyme

AbstractEnolase is a glycolytic enzyme that catalyzes the interconversion between 2-phosphoglycerate and phosphoenolpyruvate. In trypanosomatids enolase was proposed as a key enzyme afterin silicoandin vivoanalysis and it was validated as a protein essential for the survival of the parasite. Therefore, enolase constitutes an interesting enzyme target for the identification of drugs against Chagas disease. In this work, a combined virtual screening strategy was implemented, employing similarity virtual screening, molecular docking and molecular dynamics. First, two known enolase inhibitors and the enzyme substrates were used as queries for the similarity screening on the Sweetlead database using five different algorithms. Compounds retrieved in the top 10 of at least three search algorithms were selected for further analysis, resulting in six compounds of medical use (etidronate, pamidronate, fosfomycin, acetohydroximate, triclofos, and aminohydroxybutyrate). Molecular docking simulations predicted acetohydroxamate and triclofos would not bind to the active site of the enzyme, and a re-scoring of the obtained poses signaled fosfomycin and aminohydroxybutyrate as bad enzyme binders. Docking poses obtained for etidronate, pamidronate, and PEP, were used for molecular dynamics calculations to describe their mode of binding. From the obtained results, we propose etidronate as a possibleTcENO inhibitor, and describe desirable and undesirable molecular motifs to be taken into account in the repurposing or design of drugs aiming this enzyme active site.

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