Data-driven modeling of the vibrational spectroscopy of ion channels

离子通道振动光谱的数据驱动建模

• 批准号: 10715048
• 负责人: Alexei Kananenka
• 金额: $ 27.58万
• 依托单位: UNIVERSITY OF DELAWARE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-15 至 2028-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10715048
• 关键词: Arrhythmia; Cardiovascular Diseases; Cell membrane; Computing Methodologies; Data; Dimensions; Disease; Environment; Epilepsy; Frequencies; Functional disorder; Future; Goals; Integral Membrane Protein; Ion Channel; Ion Transport; Ions; Light; Link; Maps; Measures; Methodology; Methods; Modeling; Molecular; Molecular Conformation; Myopathy; NMR Spectroscopy; Nuclear; Peptides; Physiologic pulse; Potassium Channel; Protein Dynamics; Proteins; Research; Solvents; Spectrum Analysis; Structural Models; Structure; System; Techniques; Vertebral column; X-Ray Crystallography; chemical bond; complex biological systems; data-driven model; design; electric field; experimental study; frontier; graph neural network; improved; machine learning framework; magnetic field; nervous system disorder; novel; programs; simulation; temporal measurement; therapeutic target; two-dimensional; vibration; voltage

Data-driven modeling of the vibrational spectroscopy of ion channels Abstract The long-term goals of this research program are (1) to develop new computational methods for accurate sim- ulations of linear and two-dimensional infrared (2D IR) spectra of proteins and use the developed methods to simulate recent and design new 2D IR experiments to (2) investigate the mechanisms of ion transport and molec- ular origins of selectivity in the KcsA ion channel and (3) elucidate the conformational and hydrational changes of the voltage-sensing domain of the KvAP channel during voltage activation. Despite decades of research, we still don’t have the direct information on ion channel dynamics and the effects of an applied voltage on ion channel structures. 2D IR spectroscopy is an emerging analytical technique that probes protein dynamics with chemi- cal bond-specific spatial and high temporal resolution. 2D IR spectroscopy is analogous to NMR spectroscopy, except that it uses pulses of infrared light to measure vibrations rather than pulsed magnetic fields for nuclear spins. New methodology improvements expand the frontiers of 2D IR spectroscopy, permitting the study of com- plex biological systems in their native environments. Particularly interesting are systems for which NMR and X-ray crystallography are difficult to apply, such as ion channels. Interpreting congested 2D IR spectra is difficult without simulations that can quantitatively connect spectral features to atomistic structural models. Currently, 2D IR spectra of proteins are modeled using model-driven, mostly empirical, spectroscopic maps that correlate solvent-induced electric field and backbone dihedral angles to vibrational frequencies and couplings. This ap- proach, however, lacks systematic improvability, has limited transferability, provides qualitative accuracy at best, and is inaccurate for peptides in heterogeneous environments. Shifting away from the model-driven paradigm, we will use ab initio-based data-driven approaches based on Graph Neural Networks to accurately model the vibrational spectra of proteins in realistic environments. The proposed methods will provide computational sup- port for the ongoing and future 2D IR experiments on ion channels. The results of the proposed studies will significantly enhance our understanding of the molecular-level mechanisms of function of ion channels. A large spectrum of neurological, cardiovascular, and muscle disorders result from defective ion channel functioning. A better understanding of the origins of these diseases will pave the way for improved therapeutics that target ion channels.

离子通道振动光谱的数据驱动建模 摘要 这一研究计划的长期目标是：(1)开发新的计算方法，用于精确的模拟计算。 计算蛋白质的线性和二维红外(2D IR)光谱，并使用开发的方法 模拟和设计新的二维红外实验，以(2)研究离子输运和分子机制。 KCSA离子通道选择性的一般来源和(3)阐明了构象和水化的变化 电压激活期间KvAP通道的电压感应域。尽管进行了几十年的研究，我们仍然 没有关于离子通道动力学和施加电压对离子通道的影响的直接信息 结构。二维红外光谱是一种新兴的分析技术，它用化学-化学方法探测蛋白质动力学。 CAL键特定的空间和高时间分辨率。2D红外光谱类似于核磁共振光谱， 除了它使用红外光脉冲来测量振动，而不是用来测量原子核的脉冲磁场 旋转。新的方法学改进扩展了2D IR光谱的前沿，使COM-IR的研究成为可能。 Plex生物系统在它们的自然环境中。特别有趣的是核磁共振和核磁共振的系统 X射线结晶学很难应用，比如离子通道。解释拥挤的二维红外光谱是困难的 没有能够定量地将光谱特征与原子结构模型联系起来的模拟。目前， 蛋白质的2D IR光谱是使用模型驱动的、主要是经验的、相互关联的光谱图来建模的 溶剂诱导电场和主链二面角对振动频率和耦合的影响。这个AP- 然而，方法缺乏系统性的改进，可转移性有限，充其量只能提供定性的准确性， 而且对于多相环境中的多肽来说是不准确的。从模型驱动的范式转向， 我们将使用基于图神经网络的从头开始的数据驱动方法来准确地建模 现实环境中蛋白质的振动光谱。所提出的方法将提供计算支持。 为正在进行的和未来的离子通道2D IR实验提供端口。建议的研究结果将会 极大地提高了我们对离子通道功能的分子水平机制的理解。大号 神经、心血管和肌肉疾病的谱系由离子通道功能缺陷引起。一个 更好地了解这些疾病的起源将为改进针对离子的疗法铺平道路 频道。