MMP9 in Pan-Cancer and Computational Study to Screen MMP9 Inhibitors
Abstract Purpose Stromal metalloproteinase 9 (MMP9) is a stromal cell protein associated with extracellular matrix (ECM) degradation and remodeling, which promotes tumor invasion and metastasis and regulates the activity of cell adhesion molecules and cytokines. This study aims to evaluate the MMP9 in pan-cancer and to screen out new major compounds and drug candidates that can inhibit MMP9. Methods The pan-cancer dataset was downloaded from UCSC database. The MMP9 expression in pan-cancer was evaluated and the correlation of MMP9 with tumor microenvironment (TME), RNA Modification Genes and tumor mutation burden (TMB) in pan-cancer. Then, MMP9 crystal structures was download and a ligand-based pharmacophore model was constructed. machine learning model was also constructed for further screen. The identify compounds were pooled into Discovery Studio 4.5 for ADME (absorption, distribution, metabolism, excretion) and toxicity prediction. Molecular docking was performed using the Glide module of the Schrödinger kit to demonstrate the binding affinity and mechanism between compounds and MMP9. To assess whether the ligand-receptor complex is stable, Molecular Dynamics Simulation of Discovery Studio 4.5 was used. Results The results of our pan-cancer analysis showed difference expression of MMP9 in tumor tissues. Prognostic analysis showed that higher MMP9 expression means both worse survival rate and tumor progression in GMBLGG, KIPAN, UVM, LGG, ACC, and LIHC. MMP9 expression in GMBLGG, KIPAN, UVM, LGG, ACC, and LIHC was significantly positively correlated with TME. After screened by ligand-based pharmacophore model and machine learning model, 49 small molecules were identified. ADME and toxicity prediction results indicated that CEMBL82047 and CEMBL381163 were identified as potential MMP9 inhibitor. CEMBL82047 and CEMBL381163 showed robust binding affinity with MMP9, and the complex can exist stably in the natural environment. Conclusion CHEMBL82047 and CHEMBL381163 are ideal potential leading compounds for inhibiting MMP9. The findings of this study and these selected drug candidates have greatly contributed to the design and improvement of novel MMP9-targeted drugs..
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Preprint| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
ResearchSquare.com - (2024) vom: 27. Jan. Zur Gesamtaufnahme - year:2024 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Wu, Bo [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| doi: |
10.21203/rs.3.rs-2589286/v1 |
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| PPN (Katalog-ID): |
XRA038820684 |
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| 520 | |a Abstract Purpose Stromal metalloproteinase 9 (MMP9) is a stromal cell protein associated with extracellular matrix (ECM) degradation and remodeling, which promotes tumor invasion and metastasis and regulates the activity of cell adhesion molecules and cytokines. This study aims to evaluate the MMP9 in pan-cancer and to screen out new major compounds and drug candidates that can inhibit MMP9. Methods The pan-cancer dataset was downloaded from UCSC database. The MMP9 expression in pan-cancer was evaluated and the correlation of MMP9 with tumor microenvironment (TME), RNA Modification Genes and tumor mutation burden (TMB) in pan-cancer. Then, MMP9 crystal structures was download and a ligand-based pharmacophore model was constructed. machine learning model was also constructed for further screen. The identify compounds were pooled into Discovery Studio 4.5 for ADME (absorption, distribution, metabolism, excretion) and toxicity prediction. Molecular docking was performed using the Glide module of the Schrödinger kit to demonstrate the binding affinity and mechanism between compounds and MMP9. To assess whether the ligand-receptor complex is stable, Molecular Dynamics Simulation of Discovery Studio 4.5 was used. Results The results of our pan-cancer analysis showed difference expression of MMP9 in tumor tissues. Prognostic analysis showed that higher MMP9 expression means both worse survival rate and tumor progression in GMBLGG, KIPAN, UVM, LGG, ACC, and LIHC. MMP9 expression in GMBLGG, KIPAN, UVM, LGG, ACC, and LIHC was significantly positively correlated with TME. After screened by ligand-based pharmacophore model and machine learning model, 49 small molecules were identified. ADME and toxicity prediction results indicated that CEMBL82047 and CEMBL381163 were identified as potential MMP9 inhibitor. CEMBL82047 and CEMBL381163 showed robust binding affinity with MMP9, and the complex can exist stably in the natural environment. Conclusion CHEMBL82047 and CHEMBL381163 are ideal potential leading compounds for inhibiting MMP9. The findings of this study and these selected drug candidates have greatly contributed to the design and improvement of novel MMP9-targeted drugs. | ||
| 650 | 4 | |a Biology |7 (dpeaa)DE-84 | |
| 650 | 4 | |a 570 |7 (dpeaa)DE-84 | |
| 700 | 1 | |a Wang, Xinyu |4 aut | |
| 700 | 1 | |a Chen, Chunzheng |4 aut | |
| 700 | 1 | |a Yang, Qifan |4 aut | |
| 700 | 1 | |a Zhou, Pengcheng |4 aut | |
| 700 | 1 | |a Lu, Shiyuan |4 aut | |
| 700 | 1 | |a Lin, Liangxin |4 aut | |
| 700 | 1 | |a Liu, Yanwei |4 aut | |
| 700 | 1 | |a Li, Ming |4 aut | |
| 700 | 1 | |a Zhu, Dong |4 aut | |
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