1st International and 10th National Iranian Conference on Bioinformatics
Home Accepted Papers
Identification of a novel human dihydrofolate reductase inhibitor by virtual screening, docking, ADMET prediction and molecular dynamics simulations
Paper ID : 1177-ICB10
Authors:
Asma Soofi1, Nahid Safari-Alighiarloo *2
1Department of Physical Chemistry, School of chemistry, College of Sciences, University of Tehran, Tehran, Iran
2Endocrine Research Center, Institute of Endocrinology and Metabolism, Iran University of Medical Sciences, Tehran, Iran
Abstract:
Abstract
Dihydrofolate reductase (DHFR) is a critical enzyme that catalyzes the reduction of dihydrofolate to tetrahydrofolate (THF), responsible of the synthesis of raw material for cell growth and proliferation. Inhibition of DHFR resulted in a deficiency of THF and cell death. This feature makes human DHFR (hDHFR) as an attractive target for cancer therapy. Accordingly, we aimed to identify a novel effective hDHFR inhibitor using series of in silico approaches. In this study, we performed structure-based virtual screening of the PubChem database to identify potent hDHFR inhibitors. First, we retrieved all compounds from the PubChem database having at least 90% structural similarity with the known natural hDHFR inhibitors. Afterwards, the compounds were screened through molecular docking methods against hDHFR to investigate protein–ligand interaction and estimate their binding affinities. The sixteen compounds with higher binding affinity compared to methotrexate (MTX), as a reference compound, were selected. These compounds displayed essential molecular orientation and interactions with key residues of the hDHFR active site. They further investigated by Lipinski and ADMET prediction. At this stage, nondrug-like compounds were excluded based on computational approaches. Then, potential inhibitor (PubChem CID: 46886812) were identified and docked into the actives sites of hDHFR to investigate the binding modes. Finally, molecular dynamics (MD) simulation carried out to evaluate the stability of ligand-target complexes. We found that binding of CID: 46886812 stabilized the structure of hDHFR with the lowest fluctuations. In conclusion, this compound (CID: 46886812) can be suggested as a potential anti-cancer drug due to its non-toxicity, high binding affinity, and specificity towards the inhibition of hDHFR.
Keywords:
Dihydrofolate reductase (DHFR), Virtual screening, Molecular docking, Molecular dynamics simulation, ADMET
Status : Paper Accepted (Poster Presentation)