Department of Earth and Environmental Sciences, University of Milano-Bicocca, Piazza della Scienza 1, Milan 20126, Italy.
Department of Biosciences, University of Milan, via Celoria 26, Milan 20133, Italy.
J Chem Phys. 2024 Oct 7;161(13). doi: 10.1063/5.0225183.
The interpretation of ligand-target interactions at atomistic resolution is central to most efforts in computational drug discovery and optimization. However, the highly dynamic nature of protein targets, as well as possible induced fit effects, makes difficult to sample many interactions effectively with docking studies or even with large-scale molecular dynamics (MD) simulations. We propose a novel application of Self-Organizing Maps (SOMs) to address the sampling and dynamic mapping tasks, particularly in cases involving ligand flexibility and induced fit. The SOM approach offers a data-driven strategy to create a map of the interaction process and pathways based on unbiased MD. Furthermore, we show how the preliminary SOM mapping is complementary to kinetic analysis, with the employment of both network-based approaches and Markov state models. We demonstrate the method by comprehensively mapping a large dataset of 640 μs of unbiased trajectories sampling the recognition process between the phosphorylated YEEI peptide and its high-specificity target lck-SH2. The integration of SOM into unbiased simulation protocols significantly advances our understanding of the ligand binding mechanism. This approach serves as a potent tool for mapping intricate ligand-target interactions with unprecedented detail, thereby enhancing the characterization of kinetic properties crucial to drug design.
在原子分辨率下解释配体-靶标相互作用是计算药物发现和优化中大多数工作的核心。然而，由于蛋白质靶标的高度动态性质以及可能的诱导契合效应，使得通过对接研究甚至大规模分子动力学（MD）模拟有效地采样许多相互作用变得困难。我们提出了一种自组织映射（SOM）的新应用，以解决采样和动态映射任务，特别是在涉及配体灵活性和诱导契合的情况下。SOM 方法提供了一种基于无偏 MD 的数据驱动策略来创建相互作用过程和途径的图谱。此外，我们展示了初步的 SOM 映射如何与动力学分析互补，同时使用基于网络的方法和马尔可夫状态模型。我们通过全面映射磷酸化 YEEI 肽与其高特异性靶标 lck-SH2 之间识别过程的 640 μs 无偏轨迹的大型数据集来演示该方法。将 SOM 集成到无偏模拟协议中，显著提高了我们对配体结合机制的理解。这种方法是一种强大的工具，可以以前所未有的细节映射复杂的配体-靶标相互作用，从而增强对药物设计至关重要的动力学性质的表征。
