What question did this study set out to answer?

The aim is to computationally design selective inhibitors for matrix metalloproteinase-9 (MMP-9) as cancer therapeutics.

February 21, 2026

BPS2026 – Computational design of matrix metalloproteinase-9 (MMP-9) inhibitors as potential cancer therapeutics

Puntos clave

The aim is to computationally design selective inhibitors for matrix metalloproteinase-9 (MMP-9) as cancer therapeutics.
Identified 174 candidate ligands through de novo generation and PubChem database.
Docked ligands into MMP-9's catalytic domain using DOCK6, including the catalytic Zn 2+ ion.
Performed molecular dynamics simulations on ligands using AMBER for 250 ns and extended to 1000 ns for stability evaluation.
MMP-9 inhibitors improved binding affinities compared to the control compound BB-94.
Simulation results demonstrate the potential of redesigned ligands for therapeutics in cancer treatment.
Initial screenings suggest some candidates could selectively inhibit MMP-9 over MMP-2.

Resumen

Matrix metalloproteinase-9 (MMP-9) is a zinc-dependent endopeptidase involved in tissue remodeling, wound healing, and neuroplasticity. Its overexpression is associated with pathological conditions, such as cancer metastasis, neuroinflammation, and chronic inflammation. In cancer, MMP-9 promotes tumor invasion and angiogenesis by degrading extracellular matrix (ECM) barriers. Selective inhibition of MMP-9 holds therapeutic promise but is challenged by its high homology with other MMPs, especially MMP-2. Broad-spectrum MMP inhibitors like batimastat (BB-94) showed early promise but failed clinically due to off-target effects and poor selectivity. A total of 174 candidate ligands were identified using two approaches: 97 were generated through a generic de novo ligand generation method, and 77 were obtained from the PubChem database through a structural similarity search based on the control compound (BB-94), which had a binding free energy of −75.6 ± 4.7 kcal/mol. All ligands were docked into the catalytic domain of MMP-9 (PDB: 4H1Q) using DOCK6, with the catalytic Zn 2+ ion explicitly included. Molecular dynamics (MD) simulations were performed on all ligands in explicit solvent using AMBER for 250 ns. Then, the top ligands were simulated bound to MMP-2 for selectivity. The most promising candidates from this initial screening were extended to 1000 ns simulations to further evaluate their stability and binding behavior. Average binding free energies were then calculated to compare binding affinities. Future work will include de novo fragmentation based on the BB-94 scaffolds to identify alternative inhibitors with stronger binding potential. In addition, the top-performing ligands will be tested on other MMPs to check selectivity. Results of this study could potentially lead to advances in treatment for cancer and inflammation.

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