Molecular Neurobiology

, Volume 55, Issue 11, pp 8328–8345 | Cite as

Folic Acid Exerts Post-Ischemic Neuroprotection In Vitro Through HIF-1α Stabilization

  • Charles K. Davis
  • Sreekala S. Nampoothiri
  • G. K. RajanikantEmail author


The constant failure of single-target drug therapies for ischemic stroke necessitates the development of novel pleiotropic pharmacological treatment approaches, to effectively combat the aftermath of this devastating disorder. The major objective of our study involves a multi-target drug repurposing strategy to stabilize hypoxia-inducible factor-1 α (HIF-1α) via a structure-based screening approach to simultaneously inhibit its regulatory proteins, PHD2, FIH, and pVHL. Out of 1424 Food and Drug Administration (FDA)-approved drugs that were screened, folic acid (FA) emerged as the top hit and its binding potential to PHD2, FIH, and pVHL was further verified by re-docking, molecular dynamics (MD) simulation and by Drug Affinity Responsive Target Stability (DARTS) assay. HIF-1α stabilization by FA was demonstrated by the nuclear translocation and increased green fluorescence emission of HIF-1α using HIF1α-GFPSpark tag vector. Further, FA treatment enhanced the cell survival following oxygen glucose deprivation and its neuroprotective mechanism was elucidated by measuring the expression of BAX, NFE2L2, VEGF, and EPO genes in a time-dependent manner (5 and 11 h following FA treatment). VEGF and EPO expressions were significantly increased by 5.41- and 1.35-folds, respectively, whereas BAX expression reduced by 4-fold at 11 h post-FA treatment. NFE2L2 expression was elevated (1.65-fold) at 5 h with no major difference at 11 h post-FA treatment. The chicken chorioallantoic membrane (CAM) assay demonstrated the pro-angiogenic potential of FA as evidenced by an increased blood vessel density and branching. The present study elucidates for the first time that the post-ischemic neuroprotection exerted by FA may be attributed to its HIF-1α stabilization and pro-angiogenic properties.


Molecular docking Molecular dynamics simulation Folic acid Drug repurposing Neuroprotection Hypoxia-inducible factor 1 



Analysis of variance


Anti-oxidant response element


Adenosine triphosphate


BCL2 associated x, apoptosis regulator


Chick chorioallantoic membrane


Drug affinity responsive target stability


Dulbecco’s modified Eagle’s medium






Folic acid


Fetal bovine serum


Food and drug administration


Factor inhibiting HIF


Glyceraldehyde 3-phosphate dehydrogenase


Green fluorescent protein


Hypoxia-inducible factor-1 alpha


Matrix assisted laser desorption/ionization - time of flight mass spectrometry


Molecular dynamics


Molecular mechanics/generalized-Born surface area


Methylene tetrahydrofolate reductase


3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide


Nuclear factor, erythroid 2 like 2


Nuclear factor erythroid 2–related factor 2


Oxygen glucose deprivation


Optimized potentials for liquid simulations-all atom


Phosphate-buffered saline


Protein data bank


HIF prolyl hydroxylase 2


Phenylmethyl sulfonyl fluoride


Von Hippel−Lindau protein


Quantitative PCR


Radius of gyration


Root-mean-square deviation


Root-mean-square fluctuation


Reactive oxygen species


Roswell Park memorial institute


Real-time-polymerase chain reaction


Sodium dodecyl sulphate


Sodium dodecyl sulphate-polyacrylamide gel electrophoresis


Standard error of the mean


Vascular endothelial growth factor



The authors would like to thank Dr. Fayaz S. M. (Manipal Institute of Technology, India) for the technical support on molecular docking and MD simulation studies.

Author Contributions

CDK and RGK planned the experiments; CDK performed the experiments and analyzed the data; SN and CDK wrote the paper; and RGK revised the manuscript critically and approved the final version to be submitted.


This research was supported by the Department of Biotechnology, Government of India, New Delhi, India (Grant numbers BT/BI/25/001/2006 and BT/PR13909/MED/30/305/2010). The computational portion of the study was carried out in the “Bioinformatics Infrastructure Facility for Biology Teaching through Bioinformatics (BIF-BTBI)” (Grant number BT/BI/25/001/2006 dated 25/03/2011), which was financially supported by the Department of Biotechnology, Government of India.

Supplementary material

12035_2018_982_Fig10_ESM.gif (577 kb)

Animation showing FA bound to PHD2?at the active site during the course of MD simulation. (GIF 646 kb)

12035_2018_982_Fig11_ESM.gif (19 kb)

The diagram shows the minor (white), moderate (light grey) or serious (dark grey) interference of FA with other drugs. The data were obtained using Drug interaction checker and graphically presented using cytoscape 3.5.0.. (GIF 18.8 kb)

12035_2018_982_MOESM1_ESM.mp4 (4 mb)
ESM 3 Animation showing FA bound to FIH at the active site during the course of MD simulation. (MP4 4089 kb)
12035_2018_982_MOESM2_ESM.mp4 (7.3 mb)
ESM 4 Animation showing FA bound to pVHL at the active site during the course of MD simulation. (MP4 7459 kb)
12035_2018_982_MOESM3_ESM.mp4 (3 mb)
ESM 5 The graph shows the fold changes in HIF1-a expression between control, OGD and FA treated OGD groups. Error bars indicate SEM (OGD vs treatment group, * p??<??0.05). (MP4 3048 kb)
12035_2018_982_MOESM4_ESM.tif (679 kb)
High resolution image (TIFF 679 kb)
12035_2018_982_MOESM5_ESM.tif (666 kb)
High resolution image (TIFF 665 kb)


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Charles K. Davis
    • 1
    • 2
  • Sreekala S. Nampoothiri
    • 1
    • 2
  • G. K. Rajanikant
    • 1
    • 2
    Email author
  1. 1.School of BiotechnologyNational Institute of Technology CalicutCalicutIndia
  2. 2.Bioinformatics Infrastructure FacilityNational Institute of Technology CalicutCalicutIndia

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