Potential Inhibitors of Methionine Aminopeptidase Type Ii Identified Via Structure-Based Pharmacophore Modeling

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Date

2021

Authors

Albayati, Safana
Uba, Abdullahi İbrahim
Yelekçi, Kemal

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Volume Title

Publisher

Springer Science and Business Media Deutschland GmbH

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Green Open Access

Yes

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Top 10%
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Average
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Top 10%

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Abstract

Methionine aminopeptidase (MetAP2) is a metal-containing enzyme that removes initiator methionine from the N-terminus of a newly synthesized protein. Inhibition of the enzyme is crucial in diminishing cancer growth and metastasis. Fumagillin—a natural irreversible inhibitor of MetAP2—and its derivatives are used as potent MetAP2 inhibitors. However, because of their adverse effects, none of them has progressed to clinical studies. In search for potential reversible inhibitors, we built structure-based pharmacophore models using the crystal structure of MetAP2 complexed with fumagillin (PDB ID: 1BOA). The pharmacophore models were validated using Gunner–Henry scoring method. The best pharmacophore consisting of 1 H-bond donor, 1 H-bond acceptor, and 3 hydrophobic features was used to conduct pharmacophore-based virtual screening of ZINC15 database against MetAP2. The top 10 compounds with pharmacophore fit values > 3.00 were selected for further analysis. These compounds were subjected to absorption, distribution, metabolism, elimination, and toxicity (ADMET) prediction and found to have druglike properties. Furthermore, molecular docking calculations was performed on these hits using AutoDock4 to predict their binding mode and binding energy. Three diverse compounds: ZINC000014903160, ZINC000040174591, and ZINC000409110720 with respective binding energy/docking scores of − 9.22, − 9.21, and −817 kcal/mol, were submitted to 100 ns (MD) simulations using Nanoscale MD (NAMD) software. The compounds showed stable binding mode over time. Therefore, they may serve as a scaffold for further computational and experimental optimization toward the design of more potent and safer MetAP2 inhibitors.

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Keywords

ADMET prediction, Docking, MD simulation, MetAP2, MetAP2 inhibitors, Structure-based pharmacophore modeling, Structure-based pharmacophore modeling, MD simulation, MetAP2 inhibitors, Molecular Dynamics Simulation, Aminopeptidases, Docking, Molecular Docking Simulation, MetAP2, Methionine, Neoplasms, Humans, ADMET prediction

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Fields of Science

0301 basic medicine, 0303 health sciences, 03 medical and health sciences

Citation

WoS Q

Q2

Scopus Q

Q2
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OpenCitations Citation Count
6

Source

Molecular Diversity

Volume

26

Issue

Start Page

1005

End Page

1016
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Scopus : 5

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Mendeley Readers : 13

SCOPUS™ Citations

5

checked on Feb 04, 2026

Web of Science™ Citations

4

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Page Views

7

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Downloads

189

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