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In Silico Study Probes Potential Inhibitors of Human Dihydrofolate Reductase for Cancer Therapeutics
- Source :
- Journal of Clinical Medicine, Vol 8, Iss 2, p 233 (2019), Journal of Clinical Medicine, Journal of Clinical Medicine; Volume 8; Issue 2; Pages: 233
- Publication Year :
- 2019
- Publisher :
- MDPI AG, 2019.
-
Abstract
- Dihydrofolate reductase (DHFR) is an essential cellular enzyme and thereby catalyzes the reduction of dihydrofolate to tetrahydrofolate (THF). In cancer medication, inhibition of human DHFR (hDHFR) remains a promising strategy, as it depletes THF and slows DNA synthesis and cell proliferation. In the current study, ligand-based pharmacophore modeling identified and evaluated the critical chemical features of hDHFR inhibitors. A pharmacophore model (Hypo1) was generated from known inhibitors of DHFR with a correlation coefficient (0.94), root mean square (RMS) deviation (0.99), and total cost value (125.28). Hypo1 was comprised of four chemical features, including two hydrogen bond donors (HDB), one hydrogen bond acceptor (HBA), and one hydrophobic (HYP). Hypo1 was validated using Fischer’s randomization, test set, and decoy set validations, employed as a 3D query in a virtual screening at Maybridge, Chembridge, Asinex, National Cancer Institute (NCI), and Zinc databases. Hypo1-retrieved compounds were filtered by an absorption, distribution, metabolism, excretion, and toxicity (ADMET) assessment test and Lipinski’s rule of five, where the drug-like hit compounds were identified. The hit compounds were docked in the active site of hDHFR and compounds with Goldfitness score was greater than 44.67 (docking score for the reference compound), clustering analysis, and hydrogen bond interactions were identified. Furthermore, molecular dynamics (MD) simulation identified three compounds as the best inhibitors of hDHFR with the lowest root mean square deviation (1.2 Å to 1.8 Å), hydrogen bond interactions with hDHFR, and low binding free energy (−127 kJ/mol to −178 kJ/mol). Finally, the toxicity prediction by computer (TOPKAT) affirmed the safety of the novel inhibitors of hDHFR in human body. Overall, we recommend novel hit compounds of hDHFR for cancer and rheumatoid arthritis chemotherapeutics.
- Subjects :
- Stereochemistry
In silico
lcsh:Medicine
01 natural sciences
Article
03 medical and health sciences
Dihydrofolate reductase
Medicine
dihydrofolate reductase inhibition
pharmacophore modeling
molecular docking
molecular dynamics simulation
binding free energy
030304 developmental biology
chemistry.chemical_classification
0303 health sciences
Virtual screening
biology
business.industry
lcsh:R
Active site
General Medicine
0104 chemical sciences
010404 medicinal & biomolecular chemistry
Enzyme
chemistry
Docking (molecular)
biology.protein
Lipinski's rule of five
Pharmacophore
business
Subjects
Details
- Language :
- English
- ISSN :
- 20770383
- Volume :
- 8
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- Journal of Clinical Medicine
- Accession number :
- edsair.doi.dedup.....69fed678769c4f7693ab9e6a7e55d516