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Identification of novel NAD(P)H dehydrogenase [quinone] 1 antagonist using computational approaches.
J Biomol Struct Dyn. 2020 02; 38(3):682-696.JB

Abstract

NAD(P)H: quinone oxidoreductase 1 (NQO1) inhibitors are proved as promising therapeutic agents against cancer. This study is to determine potent NAD(P)H-dependent NQO1 inhibitors with new scaffold. Pharmacophore-based three-dimensional (3D) QSAR model has been built based on 45 NQO1 inhibitors reported in the literature. The structure-function correlation coefficient graph represents the relationship between phase activity and phase predicted activity for training and test sets. A QSAR model statistics shows the excellent correlation of the generated model. Pharmacophore hypothesis (AARR) yielded a statistically significant 3D QSASR model with a correlation coefficient of r2 = 0.99 as well as an excellent predictive power. From the analysis of pharmacophore-based virtual screening using by SPEC database, 4093 hits were obtained and were further filtered using virtual screening filters (HTVS, SP, XP) through structure based molecular docking. Based on glide energy and docking score, seven lead compounds show better binding affinity compared to the co-crystal inhibitor. The results of induced fit docking and prime/MM-GBSA suggest that leads AN-153/J117103 and AT-138/KB09997 binding with the catalytic site. Further, to understanding the stability of identified lead compounds MD simulations were done. The lead AN-153/J117103 showed the strong binding stable of the protein-ligand complex. Also the computed drug likeness reveals potential of this compound to treat cancer. AbbreviationsNQO1NAD(P)H-quinine oxidoreductase 1CPHcommon pharmacophore hypothesisPLSpartial least squireHBDhydrogen bond donorSDstandard deviationXPextra precisionIFDinduced fit dockingMM-GBSAmolecular mechanics generalized born surface areaMDSmolecular dynamics simulationRMSDroot mean square deviationRMSFroot mean square fluctuationRMSEroot mean square errorADMEabsorption distribution metabolism excretionsCommunicated by Ramaswamy H. Sarma.

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Publisher Full Text (DOI)

Authors+Show Affiliations

Selvakumar R
CAS in Crystallography and Biophysics, University of Madras, Chennai, Tamil Nadu, India.
Anantha Krishnan D
CAS in Crystallography and Biophysics, University of Madras, Chennai, Tamil Nadu, India.
Ramakrishnan C
Department of Biotechnology, Bhupat Jyoti Mehta School of Biosciences, Indian Institute of Technology (IIT) Madras, Chennai, Tamil Nadu, India.
Velmurugan D
CAS in Crystallography and Biophysics, University of Madras, Chennai, Tamil Nadu, India.
Gunasekaran K
CAS in Crystallography and Biophysics, University of Madras, Chennai, Tamil Nadu, India. Bioinformatics Infrastructure Facility, University of Madras, Chennai, Tamil Nadu, India.

MeSH

Drug DesignDrug Evaluation, PreclinicalEnzyme InhibitorsHydrogen BondingHydrophobic and Hydrophilic InteractionsModels, MolecularMolecular Docking SimulationNADPH DehydrogenaseQuantitative Structure-Activity RelationshipReproducibility of ResultsThermodynamics

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

30806580

Citation

Selvakumar, Rajendran, et al. "Identification of Novel NAD(P)H Dehydrogenase [quinone] 1 Antagonist Using Computational Approaches." Journal of Biomolecular Structure & Dynamics, vol. 38, no. 3, 2020, pp. 682-696.
Selvakumar R, Anantha Krishnan D, Ramakrishnan C, et al. Identification of novel NAD(P)H dehydrogenase [quinone] 1 antagonist using computational approaches. J Biomol Struct Dyn. 2020;38(3):682-696.
Selvakumar, R., Anantha Krishnan, D., Ramakrishnan, C., Velmurugan, D., & Gunasekaran, K. (2020). Identification of novel NAD(P)H dehydrogenase [quinone] 1 antagonist using computational approaches. Journal of Biomolecular Structure & Dynamics, 38(3), 682-696. https://doi.org/10.1080/07391102.2019.1585291
Selvakumar R, et al. Identification of Novel NAD(P)H Dehydrogenase [quinone] 1 Antagonist Using Computational Approaches. J Biomol Struct Dyn. 2020;38(3):682-696. PubMed PMID: 30806580.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Identification of novel NAD(P)H dehydrogenase [quinone] 1 antagonist using computational approaches. AU - Selvakumar,Rajendran, AU - Anantha Krishnan,Dhanabalan, AU - Ramakrishnan,Chandrasekaran, AU - Velmurugan,Devadasan, AU - Gunasekaran,Krishnasamy, Y1 - 2019/03/22/ PY - 2019/2/27/pubmed PY - 2020/12/29/medline PY - 2019/2/27/entrez KW - 3D-QSAR KW - MDS KW - NQO1 KW - cancer and MM/GBSA KW - induced fit docking (IFD) KW - pharmacophore modeling KW - virtual screening SP - 682 EP - 696 JF - Journal of biomolecular structure & dynamics JO - J Biomol Struct Dyn VL - 38 IS - 3 N2 - NAD(P)H: quinone oxidoreductase 1 (NQO1) inhibitors are proved as promising therapeutic agents against cancer. This study is to determine potent NAD(P)H-dependent NQO1 inhibitors with new scaffold. Pharmacophore-based three-dimensional (3D) QSAR model has been built based on 45 NQO1 inhibitors reported in the literature. The structure-function correlation coefficient graph represents the relationship between phase activity and phase predicted activity for training and test sets. A QSAR model statistics shows the excellent correlation of the generated model. Pharmacophore hypothesis (AARR) yielded a statistically significant 3D QSASR model with a correlation coefficient of r2 = 0.99 as well as an excellent predictive power. From the analysis of pharmacophore-based virtual screening using by SPEC database, 4093 hits were obtained and were further filtered using virtual screening filters (HTVS, SP, XP) through structure based molecular docking. Based on glide energy and docking score, seven lead compounds show better binding affinity compared to the co-crystal inhibitor. The results of induced fit docking and prime/MM-GBSA suggest that leads AN-153/J117103 and AT-138/KB09997 binding with the catalytic site. Further, to understanding the stability of identified lead compounds MD simulations were done. The lead AN-153/J117103 showed the strong binding stable of the protein-ligand complex. Also the computed drug likeness reveals potential of this compound to treat cancer. AbbreviationsNQO1NAD(P)H-quinine oxidoreductase 1CPHcommon pharmacophore hypothesisPLSpartial least squireHBDhydrogen bond donorSDstandard deviationXPextra precisionIFDinduced fit dockingMM-GBSAmolecular mechanics generalized born surface areaMDSmolecular dynamics simulationRMSDroot mean square deviationRMSFroot mean square fluctuationRMSEroot mean square errorADMEabsorption distribution metabolism excretionsCommunicated by Ramaswamy H. Sarma. SN - 1538-0254 UR - https://www.unboundmedicine.com/medline/citation/30806580/Identification_of_novel_NAD_P_H_dehydrogenase_[quinone]_1_antagonist_using_computational_approaches_ DB - PRIME DP - Unbound Medicine ER -

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