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MMP9 in pan-cancer and computational study to screen for MMP9 inhibitors.

Xianjie Ai,Xinyu Wang,Taotao Ren,Zhong Li,Bo Wu,Ming Li

Published 2024 in American journal of translational research

ABSTRACT

PURPOSE The stromal cell protein metalloproteinase 9 (MMP9), associated with extracellular matrix degradation and remodeling, promotes tumor invasion and metastasis and regulates cell adhesion molecule and cytokine activity. This study evaluated MMP9 in pan-cancer and screened for compounds and drug candidates that can inhibit it. METHODS MMP9 expression in pan-cancer tissues was evaluated in a pan-cancer dataset from the University of California Santa Cruz database, along with the correlation between MMP9 and the tumor microenvironment (TME), RNA modification genes, and tumor mutation burden. MMP9 crystal structures were downloaded, and a ligand-based pharmacophore model was constructed. A machine learning model was constructed for further screening. The identified compounds were pooled into Discovery Studio 4.5 for absorption, distribution, metabolism, and excretion (ADME) and toxicity prediction. Molecular docking was used to demonstrate the binding affinity and mechanism between the compounds and MMP9, and the stability of the ligand-receptor complex was assessed. RESULTS The expression levels of MMP9 differed between tumor tissues. Prognostic analysis showed that high MMP9 expression indicates poor survival and tumor progression in glioma (GMBLGG), pan-kidney (KIPAN; KICH+KIRC+KIRP), uveal melanoma (UVM), low-grade glioma (LGG), adrenocortical carcinoma (ACC), and liver hepatocellular carcinoma (LIHC). MMP9 expression in GMBLGG, KIPAN, UVM, LGG, ACC, and LIHC was positively correlated with the TME. The ligand-based pharmacophore model and the machine learning model identified 49 small molecules. ADME and toxicity prediction identified CEMBL82047 and CEMBL381163 as potential MMP9 inhibitors, showing robust binding affinity with MMP9. The resulting complexes are stable in the natural environment. CONCLUSION CHEMBL82047 and CHEMBL381163 are ideal compounds for inhibiting MMP9. The findings of this study will contribute to the design and improvement of MMP9-targeting drugs.

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