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

[UNLABELLED] 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 (R = 0.86, Q = 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.

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