MOLECULAR DOCKING STUDIES FOR THE COMPARATIVE ANALYSIS OF DIFFERENT BIOMOLECULES TO TARGET HYPOXIA INDUCIBLE FACTOR-1α


Niraj Kumar Jha, Pravir Kumar

Abstract


Objective: Hypoxia plays a significant role in governing many vital signalling molecules in the central nervous system (CNS). Hypoxic exposure has also been depicted as a stimulus for oxidative stress, increase in lipid peroxidation, DNA damage, blood-brain dysfunction, impaired calcium (Ca2+) homoeostasis and agglomeration of oxidized biomolecules in neurons, which act as a novel signature in diverse neurodegenerative and oncogenic processes. On the contrary, the presence of abnormally impaired expression of HIF-1α under hypoxic insult could serve as an indication of the existence of tumors and neuronal dysfunction as well. For instance, under hypoxic stress, amyloid-β protein precursor (AβPP) cleavage is triggered due to the higher expression of HIF-1α and thus leads to synaptic loss. The objective of this research is to perform comparative studies of biomolecules in regulating HIF-1α activity based on in silico approaches that could establish a potential therapeutic window for the treatment of different abnormalities associated with impaired HIF-1α.

Methods: We employed various in silico methods such as drug-likeness parameters namely Lipinski filter analysis, Muscle tool, SWISS-MODEL, active site prediction, Auto Dock 4.2.1 and LigPlot1.4.5for molecular docking studies.

Results: 3D structure of HIF-1α was generated and Ramachandran plot obtained for quality assessment. RAMPAGE displayed 99.5% of residues in the most favoured regions. 0% residues in additionally allowed and 0.5% disallowed regions of the HIF-1α protein. Further, initial screenings of the molecules were done based on Lipinski’s rule of five. Cast P server used to predict the ligand binding site suggests that this protein can be utilised as a potential drug target. Finally, we have found Naringenin to be most effective amongst three biomolecules in modulating HIF-1α based on minimum inhibition constant, Ki and highest negative free energy of binding with the maximum interacting surface area during docking studies.

Conclusion: The present study outlines the novel potential of Biomolecules in regulating HIF-1α activity for the treatment of different abnormalities associated with impaired HIF-1α.


Keywords


Hypoxia-inducible factor-1α (HIF-1α), Biomolecules, Active site prediction, Molecular docking

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References


Li L, Welser JV, Dore-Duffy P. In the hypoxic central nervous system, endothelial cell proliferation is followed by astrocyte activation, proliferation, and increased expression of the alpha 6 beta 4 integrin and dystroglycan. Glia 2010;58:1157-67.

Keith B, Johnson RS, Simon MC. HIF1α and HIF2α: sibling rivalry in hypoxic tumour growth and progression. Nat Rev Cancer 2011;12:9-22.

Correia SC, Carvalho C, Cardoso S. Defective HIF signaling pathway and brain response to hypoxia in neurodegenerative diseases: not an "iffy" question. Curr Pharm Des 2013;19:6809-22.

Ziello JE, Jovin IS, Huang Y. Hypoxia-inducible factor (HIF)-1 regulatory pathway and its potential for therapeutic intervention in malignancy and ischemia. Yale J Biol Med 2007;80:51-60.

Mukandala G, Tynan R, Lanigan S. The effects of hypoxia and inflammation on synaptic signaling in the CNS. Brain Sci 2016;6:E6.

Oh YS. Bioactive compounds and their neuroprotective effects in diabetic complications. Nutrients 2016;8:E472.

Mahendra Kumar C, Singh SA. Bioactive lignans from sesame (Sesamumindicum L.): evaluation of their antioxidant and antibacterial effects for food applications. J Food SciTechnol 2015;52:2934-41.

Zhang L, Lokeshwar BL. Medicinal properties of the Jamaican pepper plant Pimentadioica and Allspice. Curr Drug Targets 2012;13:1900-6.

Sonia Angeline M, Sarkar A, Anand K. Sesamol and naringenin reverse the effect of rotenone-induced PD rat model. Neuroscience 2013;254:379-94.

Sarkar A, Angeline MS, Anand K. Naringenin and quercetin reverse the effect of hypobaric hypoxia and elicit a neuroprotective response in the murine model. Brain Res 2012;1481:59-70.

Altschul SF, Gish W, Miller W. Basic local alignment search tool. J Mol Biol 1990;215:403-10.

Edgar RC. MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics 2004;5:113.

Arnold K, Bordoli L, Kopp J. The SWISS-MODEL workspace: a web-based environment for protein structure homology modeling. Bioinformatics 2006;22:195-201.

Yang Z, Lasker K, Schneidman-Duhovny D. UCSF Chimera, MODELLER, and IMP: an integrated modeling system. J Struct Biol 2012;179:269-78.

Dundas J, Ouyang Z, Tseng J. CASTp: computed atlas of surface topography of proteins with structural and topographical mapping of functionally annotated residues. Nucleic Acids Res 2006;34:W116-118.

Lipinski CA. Lead-and drug-like compounds: the rule-of-five revolution. Drug Discovery Today Technol 2004;1:337-41.

Pradeepkiran JA, Kumar KK, Kumar YN. Modeling, molecular dynamics and docking assessment of transcription factor rho: a potential drug target in Brucellamelitensis 16M. Drug Des Dev Ther 2015;9:1897-912.

Park H, Lee J, Lee S. Critical assessment of the automated AutoDock as a new docking tool for virtual screening. Proteins 2006;65:549-54.

Pranjaligupta, Nishant Rai, Pankaj Gautam. Anticancer drugs as potential inhibitors of acrab-tolc of multidrug-resistant Escherichia coli: an in silico molecular modeling and docking study. Asian J Pharm Clin Res. 2015;8:351-8.

Sri dharani R, Ranjitha R, Sripathi R, Ali muhammad KS, Ravi S. Docking studies in target proteins involved in antibacterial action mechanisms: alkaloids isolated from Scutellariagenus. Asian J Pharm Clin Res 2016;9:121-5.

Manjula J, Maheswari R. Biological and docking studies of novel aroylhydrazones. Int J Pharm Pharm Sci 2017;9:81-5.

Sarath S, Anjali T. In silico design and molecular docking studies of some 1,2-benzisoxazole derivatives for their analgesic and anti-inflammatory activity. Int J Curr Pharm Res 2017;9:38-41.




About this article

Title

MOLECULAR DOCKING STUDIES FOR THE COMPARATIVE ANALYSIS OF DIFFERENT BIOMOLECULES TO TARGET HYPOXIA INDUCIBLE FACTOR-1α

Keywords

Hypoxia-inducible factor-1α (HIF-1α), Biomolecules, Active site prediction, Molecular docking

DOI

10.22159/ijap.2017v9i4.19505

Date

13-07-2017

Additional Links

Manuscript Submission

Journal

International Journal of Applied Pharmaceutics
Vol 9, Issue 4, 2017 Page: 83-89

Online ISSN

0975-7058

Statistics

11 Views | 28 Downloads

Authors & Affiliations

Niraj Kumar Jha
Molecular Neuroscience and Functional Genomics Laboratory, Delhi Technological University (Formerly DCE), Delhi 110042
India

Pravir Kumar
Molecular Neuroscience and Functional Genomics Laboratory, Delhi Technological University (Formerly DCE), Delhi 110042
India


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