抑制 TIM3-半乳糖凝集素 9 结合途径的肽-TIM3 结合位点的预测,Journal of Chemical Theory and Computation

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抑制 TIM3-半乳糖凝集素 9 结合途径的肽-TIM3 结合位点的预测
Journal of Chemical Theory and Computation ( IF 5.7 ) Pub Date : 2023-08-30 , DOI: 10.1021/acs.jctc.3c00487
Ryan E Odstrcil ₁ , Prashanta Dutta ₁ , Jin Liu ₁

Affiliation

T 细胞免疫球蛋白和粘蛋白结构域蛋白 3 (TIM3) 是调节免疫系统的重要受体蛋白。TIM3 与半乳糖凝集素 9 (GAL9) 的结合会触发免疫系统抑制，但 TIM3-GAL9 结合可以通过肽 P26 与 TIM3 的结合来抑制。快速准确地预测 P26-TIM3 结合位点至关重要，也是研究 P26-TIM3 相互作用和 TIM3-GAL9 结合途径的先决条件。在这里，我们提出了一种机器学习方法，该方法考虑蛋白质构象变化，以快速识别 TIM3 上的配体结合位点。我们的结果表明 P26 结合位点位于 TIM3 的 C”-D 环附近。进一步的模拟表明，结合姿势通过各种静电和疏水相互作用得以稳定。P26 的结合可以改变 TIM3 上附近聚糖侧链的构象，从而提供 P26 如何抑制 TIM3-GAL9 结合途径的可能机制。这项工作的见解将有助于识别也可能抑制 TIM3-GAL9 通路的其他肽或抗体，并最终导致改进 TIM3-GAL9 免疫抑制通路调节的尝试。当结合过程中的构象变化很重要时，这些策略和机器学习方法可以推广到研究配体-受体结合。

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Prediction of the Peptide–TIM3 Binding Site in Inhibiting TIM3–Galectin 9 Binding Pathways

T-cell immunoglobulin and mucin domain-containing protein-3 (TIM3) is an important receptor protein that modulates the immune system. The binding of TIM3 with Galectin 9 (GAL9) triggers immune system suppression, but the TIM3–GAL9 binding can be inhibited by binding of the peptide P26 to TIM3. A fast and accurate prediction of the P26-TIM3 binding site is crucial and a prerequisite for the investigation of P26–TIM3 interactions and TIM3–GAL9 binding pathways. Here, we present a machine learning approach, which considers protein conformational changes, to quickly identify the ligand-binding site on TIM3. Our results show that the P26 binding site is located near the C″–D loop of TIM3. Further simulations show that the binding pose is stabilized by a variety of electrostatic and hydrophobic interactions. Binding of P26 can alter the conformations of nearby glycan side chains on TIM3, providing possible mechanisms of how P26 inhibits TIM3–GAL9 binding pathways. The insights from this work will facilitate the identification of other peptides or antibodies that may also inhibit the TIM3–GAL9 pathways and eventually lead to improved attempts in the modulation of the TIM3–GAL9 immunosuppression pathways. The strategies and machine learning method can be generalized to study ligand–receptor binding when the conformational changes during the binding are important.

更新日期：2023-08-30

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