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Letters in Drug Design & Discovery

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ISSN (Print): 1570-1808
ISSN (Online): 1875-628X

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Research Article

In Silico Prediction and Validation of Oxygen-Regulated Protein N-myc Downstream Regulated Gene 3 and Virtual Screening of Competitive Inhibitors of L-Lactate as Therapeutics

Author(s): Hongyu Cao, Yanhua Wu, Xingzhi Zhou, Xuefang Zheng and Ge Jiang *

Volume 16, Issue 6, 2019

Page: [637 - 644] Pages: 8

DOI: 10.2174/1570180815666180816130621

Price: $65

Abstract

Background: N-myc downstream regulated gene 3 (NDRG3) is a newly discovered oxygen-regulated protein which will bind with L-Lactate in hypoxia and further activate Raf (rapidly accelerated fibrosarcoma)-ERK (extracellular regulated protein kinases) pathway, promoting cell growth and angiogenesis.

Methods: Competitive inhibition on the binding of NDRG3 and L-Lactate may be potentially a useful strategy for the repression of hypoxic response mediated by NDRG3. The threedimensional (3D) structure of NDRG3 was built by using homology modeling for its crystal structure was not available. Then, L-Lactate was docked into NDRG3, from which we knew it bound with amino acid residues Gln69, His183, Asn189, Ala72 and Pro66 of NDRG3 in the most possible active sites. Approximately 3000 compounds have been virtually screened and the 6 topranked compounds were selected as reference molecules to analyze their interaction relationships, which illustrated that some of them might form electrostatic interaction with Glu70 and Asp187, π-π stack with Phe75 and Tyr180, hydrogen bonds with Gly71 and Asn189, hydrophobic effect with Ala72 and Ile184.

Results: Novel molecules were designed through structural optimization of the 6 top-ranked compounds and subsequently their ADMET properties were predicted.

Conclusion: These molecules may be potential drug candidates for the suppression of hypoxic response mediated by NDRG3 and targeted therapy for hypoxia-induced diseases.

Keywords: NDRG3, L-Lactate, competitive inhibitors, homology modeling, molecular docking, virtual screening, drug design, ADMET prediction.

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