ITMB, Department of Informatics & Telecommunications, National and Kapodistrian University of Athens, Athens 15772, Greece.
Biomedical Research Foundation, Academy of Athens, 4 Soranou Ephessiou, Athens 11527, Greece.
J Chem Theory Comput. 2022 Sep 13;18(9):5636-5648. doi: 10.1021/acs.jctc.1c00881. Epub 2022 Aug 9.
Molecular dynamics simulation is a powerful technique for studying the structure and dynamics of biomolecules in atomic-level detail by sampling their various conformations in real time. Because of the long timescales that need to be sampled to study biomolecular processes and the big and complex nature of the corresponding data, relevant analyses of important biophysical phenomena are challenging. Clustering and Markov state models (MSMs) are efficient computational techniques that can be used to extract dominant conformational states and to connect those with kinetic information. In this work, we perform Molecular Dynamics simulations to investigate the free energy landscape of Angiotensin II (AngII) in order to unravel its bioactive conformations using different clustering techniques and Markov state modeling. AngII is an octapeptide hormone, which binds to the AT1 transmembrane receptor, and plays a vital role in the regulation of blood pressure, conservation of total blood volume, and salt homeostasis. To mimic the water-membrane interface as AngII approaches the AT1 receptor and to compare our findings with available experimental results, the simulations were performed in water as well as in water-ethanol mixtures. Our results show that in the water-ethanol environment, AngII adopts more compact U-shaped (folded) conformations than in water, which resembles its structure when bound to the AT1 receptor. For clustering of the conformations, we validate the efficiency of an inverted-quantized -means algorithm, as a fast approximate clustering technique for web-scale data (millions of points into thousands or millions of clusters) compared to -means, on data from trajectories of molecular dynamics simulations with reasonable trade-offs between time and accuracy. Finally, we extract MSMs using various clustering techniques for the generation of microstates and macrostates and for the selection of the macrostate representatives.
分子动力学模拟是一种强大的技术，可通过实时采样生物分子的各种构象，在原子水平上研究生物分子的结构和动态。由于需要采样很长的时间来研究生物分子过程，并且相应数据的规模庞大且复杂，因此对重要生物物理现象的相关分析具有挑战性。聚类和马尔可夫状态模型（MSM）是有效的计算技术，可用于提取主要构象状态，并将其与动力学信息联系起来。在这项工作中，我们进行分子动力学模拟，以研究血管紧张素 II（AngII）的自由能景观，以便使用不同的聚类技术和马尔可夫状态建模来揭示其生物活性构象。AngII 是一种八肽激素，与 AT1 跨膜受体结合，在调节血压、维持总血容量和盐平衡方面起着至关重要的作用。为了模拟 AngII 接近 AT1 受体时的水-膜界面，并将我们的发现与可用的实验结果进行比较，模拟在水以及水-乙醇混合物中进行。我们的结果表明，在水-乙醇环境中，AngII 采用比水更紧凑的 U 形（折叠）构象，这类似于其与 AT1 受体结合时的结构。对于构象的聚类，我们验证了倒置量化均值算法的效率，该算法是一种快速近似聚类技术，可用于处理网络规模的数据（将数百万个点聚类成数千个或数百万个簇），与均值相比，在具有合理时间和准确性折衷的分子动力学模拟轨迹数据上具有优势。最后，我们使用各种聚类技术提取 MSM，以生成微态和宏态，并选择宏态代表。
