Virtual screening and pharmacophore design for a novel theoretical inhibitor of macrophage stimulating factor as a metastatic agent
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Published on: January 24, 2025
Ibrahim Torktaz1, Faezeh Mohamadhashem, Abolghasem Esmaeili
1Young Researchers and Elite Club, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
Introduction:
Metastasis is a crucial aspect of cancer. Macrophage stimulating protein (MSP) is a single chain protein and can be cleaved by serum proteases. MSP has several roles in metastasis. In this in silico study, MSP as a metastatic agent was considered as a drug target.
Methods:
Crystallographic structure of MSP was retrieved from protein data bank. To find a chemical inhibitor of MSP, a library of KEGG compounds was screened and 1000 shape complemented ligands were retrieved with FindSite algorithm. Molegro Virtual Docker (MVD) software was used for docking simulation of shape complemented ligands against MSP. Moldock score was used as scoring function for virtual screening and potential inhibitors with more negative binding energy were obtained. PLANS scoring function was used for revaluation of virtual screening data.
Results:
The top found chemical had binding affinity of -183.55 based on MolDock score and equal to -66.733 PLANTs score to MSP structure.
Conclusion:
Based on pharmacophore model of potential inhibitor, this study suggests that the chemical which was found in this research and its derivate can be used for subsequent laboratory studies.
Insights
This study identified a potential drug target, macrophage stimulating protein (MSP), involved in cancer metastasis. Computational screening revealed a chemical inhibitor with significant binding affinity, suggesting its use in future laboratory cancer research.
Area of Science:
- Biochemistry
- Computational Biology
- Drug Discovery
Background:
- Metastasis is a critical factor in cancer progression.
- Macrophage stimulating protein (MSP) plays a significant role in metastasis.
- MSP was investigated as a potential drug target due to its metastatic functions.
Purpose of the Study:
- To identify potential chemical inhibitors of Macrophage stimulating protein (MSP) using in silico methods.
- To evaluate the binding affinity of identified compounds to MSP.
- To provide a basis for further laboratory validation of potential anti-metastatic agents.
Main Methods:
- Retrieved the crystallographic structure of MSP from the Protein Data Bank.
- Screened the KEGG compound library using the FindSite algorithm to identify shape-complementary ligands.
- Performed molecular docking simulations using Molegro Virtual Docker (MVD) and evaluated ligands using MolDock and PLANTs scoring functions.
Main Results:
- Identified a top-ranking chemical compound with a MolDock score of -183.55 and a PLANTs score of -66.733.
- The identified compound exhibited significant binding affinity to the MSP structure.
- Computational analysis provided a pharmacophore model for potential MSP inhibitors.
Conclusions:
- The study successfully identified a promising chemical inhibitor for Macrophage stimulating protein (MSP).
- The identified compound and its derivatives warrant further investigation in laboratory settings.
- This research contributes to the development of novel therapeutic strategies targeting cancer metastasis.
