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Ligand-based 3D pharmacophore modeling, virtual screening, and molecular dynamic simulation of potential smoothened inhibitors

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Abstract

Context

The Hedgehog (Hh) signaling pathway is a crucial regulator of various cellular processes. Dysregulated activation of the Smoothened (SMO) oncoprotein, a key component of the Hh pathway, has been implicated in several types of cancer. Although SMO inhibitors are important anti-cancer therapeutics, drug-resistant SMO mutants have emerged, limiting their efficacy. This study aimed to discover stable SMO inhibitors for both wild-type and mutant SMOs, using a 12-feature pharmacophore model validated for virtual screening. One lead compound, LCT10312, was identified with high affinity to SMO and showed a significant conformational change in the SMO structure upon binding. Molecular dynamic simulation revealed stable interaction of LCT10312 with SMO and large atom motions, indicating SMO structural fluctuation. The lead compound showed high predicted binding scores to several clinically relevant SMO mutants.

Methods

A ligand-based pharmacophore model was developed from 25 structurally clustered SMO inhibitors using LigandScout v3.12 software and virtually screened for hit identification from a library of 511,878 chemicals. Molecular docking was employed to identify potential leads based on SMO affinities. Molecular dynamic simulation (MDS) with GROMACS v5.1.4 was performed to analyze the structural changes of SMO oncoprotein upon binding lead compound(s) and cyclopamine as the control for 100 ns. The binding affinity of lead compound(s) was predicted on clinical and laboratory SMO mutants.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

The authors wish to thank the Stem Cell Research Center and Department of Microbiology for their spiritual supports.

Funding

Financial support for this study was provided by a grant (970913172).

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Authors and Affiliations

  1. Stem Cell Research Center, School of Medicine, Golestan University of Medical Sciences, Gorgan, Iran

    Alireza Mohebbi

  2. Department of Virology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran

    Alireza Mohebbi

  3. Vista Aria Rena Gene Inc., Gorgan, Iran

    Alireza Mohebbi

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  1. Alireza Mohebbi
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Contributions

The study conception and design, as well as data gathering, analysis, visualization, writing, and editing the drafts of the manuscript are all performed by Alireza Mohebbi.

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Correspondence to Alireza Mohebbi.

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An ethical approval code (IR.GOUMS.REC.1397.066) received from the Golestan University of Medical Sciences, Gorgan, Iran.

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Mohebbi, A. Ligand-based 3D pharmacophore modeling, virtual screening, and molecular dynamic simulation of potential smoothened inhibitors. J Mol Model 29, 143 (2023). https://doi.org/10.1007/s00894-023-05532-5

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