Computational optimization of MALT1 inhibitors against DLBCL: a QSAR-guided molecular docking and dynamics study

Mucosa-associated lymphoid tissue lymphoma translocation protein 1 (MALT1) is a critical effector in constitutive NF-κB signalling, driving oncogenesis in activated B-cell-like diffuse large B-cell lymphoma. Here, we employed an integrated computational strategy to design and optimize small-molecule MALT1 inhibitors. A statistically validated Quantitative structure-activity relationship model (R² = 0.86, Q² = 0.82, CCC = 0.90) identified descriptors linked to potency, and docking simulations revealed binding affinities between - 8.6 and - 9.6 kcal/mol. Among the MI-2, a selective small-molecule inhibitor of MALT1 analogues, compound 14 combined favourable docking affinity (- 8.9 kcal/mol) with strong pharmacokinetics, which guided rational optimization. The derivative 14f emerged as the most promising scaffold, achieving improved intestinal absorption (96.9%), favourable clearance (0.43 log ml/min/kg), non-mutagenicity, and the strongest binding affinity (- 9.6 kcal/mol). Molecular dynamics simulations confirmed the stability of the 14f-MALT1 complex, with protein backbone RMSD maintained within 3 Å and ligand fluctuations below 1 Å over 100 ns. Collectively, these results highlight compound 14f as a viable lead scaffold for MALT1 inhibition in DLBCL. As this study is purely computational, experimental validation is required to confirm these findings.

The online version contains supplementary material available at 10.1007/s40203-025-00466-7.