Literature DB >> 35436996

Identification of potent inhibitors of NEK7 protein using a comprehensive computational approach.

Mubashir Aziz1, Syeda Abida Ejaz2, Nissren Tamam3, Farhan Siddique4,5, Naheed Riaz6, Faizan Abul Qais7, Samir Chtita8, Jamshed Iqbal9.   

Abstract

NIMA related Kinases (NEK7) plays an important role in spindle assembly and mitotic division of the cell. Over expression of NEK7 leads to the progression of different cancers and associated malignancies. It is becoming the next wave of targets for the development of selective and potent anti-cancerous agents. The current study is the first comprehensive computational approach to identify potent inhibitors of NEK7 protein. For this purpose, previously identified anti-inflammatory compound i.e., Phenylcarbamoylpiperidine-1,2,4-triazole amide derivatives by our own group were selected for their anti-cancer potential via detailed Computational studies. Initially, the density functional theory (DFT) calculations were carried out using Gaussian 09 software which provided information about the compounds' stability and reactivity. Furthermore, Autodock suite and Molecular Operating Environment (MOE) software's were used to dock the ligand database into the active pocket of the NEK7 protein. Both software performances were compared in terms of sampling power and scoring power. During the analysis, Autodock results were found to be more reproducible, implying that this software outperforms the MOE. The majority of the compounds, including M7, and M12 showed excellent binding energies and formed stable protein-ligand complexes with docking scores of - 29.66 kJ/mol and - 31.38 kJ/mol, respectively. The results were validated by molecular dynamics simulation studies where the stability and conformational transformation of the best protein-ligand complex were justified on the basis of RMSD and RMSF trajectory analysis. The drug likeness properties and toxicity profile of all compounds were determined by ADMETlab 2.0. Furthermore, the anticancer potential of the potent compounds were confirmed by cell viability (MTT) assay. This study suggested that selected compounds can be further investigated at molecular level and evaluated for cancer treatment and associated malignancies.
© 2022. The Author(s).

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Year:  2022        PMID: 35436996      PMCID: PMC9016071          DOI: 10.1038/s41598-022-10253-5

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.996


  59 in total

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Review 2.  Targeting cancer with kinase inhibitors.

Authors:  Stefan Gross; Rami Rahal; Nicolas Stransky; Christoph Lengauer; Klaus P Hoeflich
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3.  Extensive consensus docking evaluation for ligand pose prediction and virtual screening studies.

Authors:  Tiziano Tuccinardi; Giulio Poli; Veronica Romboli; Antonio Giordano; Adriano Martinelli
Journal:  J Chem Inf Model       Date:  2014-09-18       Impact factor: 4.956

4.  Isolation and characterization of two evolutionarily conserved murine kinases (Nek6 and nek7) related to the fungal mitotic regulator, NIMA.

Authors:  M Kandli; E Feige; A Chen; G Kilfin; B Motro
Journal:  Genomics       Date:  2000-09-01       Impact factor: 5.736

Review 5.  Never say never. The NIMA-related protein kinases in mitotic control.

Authors:  Matthew J O'Connell; Michael J E Krien; Tony Hunter
Journal:  Trends Cell Biol       Date:  2003-05       Impact factor: 20.808

6.  Open Babel: An open chemical toolbox.

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Journal:  J Cheminform       Date:  2011-10-07       Impact factor: 5.514

7.  Nek family of kinases in cell cycle, checkpoint control and cancer.

Authors:  Larissa Moniz; Previn Dutt; Nasir Haider; Vuk Stambolic
Journal:  Cell Div       Date:  2011-10-31       Impact factor: 5.130

8.  Timing of centrosome separation is important for accurate chromosome segregation.

Authors:  William T Silkworth; Isaac K Nardi; Raja Paul; Alex Mogilner; Daniela Cimini
Journal:  Mol Biol Cell       Date:  2011-11-30       Impact factor: 4.138

9.  A mutation in Aspergillus nidulans that blocks the transition from interphase to prophase.

Authors:  B R Oakley; N R Morris
Journal:  J Cell Biol       Date:  1983-04       Impact factor: 10.539

10.  Dabrafenib inhibits the growth of BRAF-WT cancers through CDK16 and NEK9 inhibition.

Authors:  Manali Phadke; Lily L Remsing Rix; Inna Smalley; Annamarie T Bryant; Yunting Luo; Harshani R Lawrence; Braydon J Schaible; Yian A Chen; Uwe Rix; Keiran S M Smalley
Journal:  Mol Oncol       Date:  2017-11-23       Impact factor: 6.603

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  3 in total

1.  Deep Learning and Structure-Based Virtual Screening for Drug Discovery against NEK7: A Novel Target for the Treatment of Cancer.

Authors:  Mubashir Aziz; Syeda Abida Ejaz; Seema Zargar; Naveed Akhtar; Abdullahi Tunde Aborode; Tanveer A Wani; Gaber El-Saber Batiha; Farhan Siddique; Mohammed Alqarni; Ashraf Akintayo Akintola
Journal:  Molecules       Date:  2022-06-25       Impact factor: 4.927

2.  In-silico modelling studies of 5-benzyl-4-thiazolinone derivatives as influenza neuraminidase inhibitors via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions.

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Journal:  Heliyon       Date:  2022-08-08

3.  Computational modelling studies of some 1,3-thiazine derivatives as anti-influenza inhibitors targeting H1N1 neuraminidase via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions.

Authors:  Mustapha Abdullahi; Adamu Uzairu; Gideon Adamu Shallangwa; Paul Andrew Mamza; Muhammad Tukur Ibrahim
Journal:  Beni Suef Univ J Basic Appl Sci       Date:  2022-08-19
  3 in total

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