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<p>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<sup>2</sup> = 0.86, Q<sup>2</sup> = 0.82, CCC = 0.90) identified descriptors linked to potency, and docking simulations revealed binding affinities between − 8.6 and − 9.6&#xa0;kcal/mol. Among the MI-2, a selective small-molecule inhibitor of MALT1 analogues, compound 14 combined favourable docking affinity (− 8.9&#xa0;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&#xa0;kcal/mol). Molecular dynamics simulations confirmed the stability of the 14f–MALT1 complex, with protein backbone RMSD maintained within 3&#xa0;Å and ligand fluctuations below 1&#xa0;Å over 100&#xa0;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.</p>

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

  • 期刊论文

  • 发表日期：

    2025年11月26日

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  • Josiah Joseph Isah,
  • Adamu Uzairu,
  • Sani Uba,
  • Muhammad Tukur Ibrahim

摘要

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.