Theory and Modeling of Noncovalent Binding

描述(申请人提供)：特定的、非共价结合是许多生物功能的中心，如信号和免疫；大多数药物是结合特定蛋白质并调节其功能的小分子。该项目旨在加深对非共价结合的更深入和更定量的了解，并结合日益具有预测性和洞察力的建模技术，以加快新药的发现。一个目标是开发最佳实践，不仅计算结合自由能，而且使用分子动力学模拟和水的显式处理来计算精确的结合热。然后，我们将把这些做法应用于 寻求对经常令人困惑的实验量热数据的机械解释，例如，观察到配体的预组织可能不是以熵的方式加强结合，而是以焓的方式加强结合；以及常见的、但仍然知之甚少的熵-热补偿现象。我们还将致力于一种新的方法来测试分子模拟中使用的力场。今天，力场主要是通过计算小分子水合自由能和纯液体的物理性质来测试的，并将这些结果与实验进行比较。因此，尽管模拟被广泛用于模拟结合，但实验结合数据在模拟力场的测试和优化中作用很小。在这里，我们的目标是建立主-客体结合数据作为测试力场的新基准，方法是组装一组实验表征的、计算上容易处理的主-客体系统，以及自动计算它们的结合自由能和热焓的计算脚本，并将这些结果与实验进行比较。这个“验证引擎” 将用于测试广泛使用的力场，也将免费与其他小组共享。最后，我们将把自由能模拟方法集成到两个协同工作中 药物？？发现项目。 一个项目的中心是一种名为可溶性环氧化物水解酶的人类酶，它的三维结构已知，在治疗上与心血管疾病和炎症性疾病有关。在我们的初步研究中，传统的对接方法提供的有用指导很少或根本没有；我们现在的目标是将更复杂的能量模拟方法应用于这一具有挑战性的案例。第二个项目处于早期阶段，涉及一种名为Cif的细菌毒力因子。这也是一种环化水解酶，它的抑制有望对肺炎假单胞菌患者有所帮助。我们计划使用对接和自由能方法来帮助发现有效的Cif抑制剂，用作化学探针，并有可能作为Ne药物的第一步。

DESCRIPTION (provided by applicant): Specific, noncovalent binding is central to many biological functions, such as signaling and immunity; and most drugs are small molecules that bind a specific protein and modulate its function. This project aims fr a deeper and more quantitative understanding of noncovalent binding, coupled with increasingly predictive and insightful modeling technologies that will speed the discover of new medications. One goal is to develop best practices for computing not only bindin free energies, but also numerically precise binding enthalpies, using molecular dynamics simulations with an explicit treatment of water. We will then apply these practices to seek mechanistic explanations of often puzzling experimental calorimetric data, such as observations that ligand preorganization may strengthen binding not entropically, as expected, but enthalpically; and the common, but still poorly understood, phenomenon of entropy-enthalpy compensation. We will also work on a new method to test the force fields used in molecular simulations. Today, force fields are tested primarily by computing small molecule hydration free energies and the physical properties of pure liquids, and comparing these results with experiment. Thus, although simulations are widely used to model binding, experimental binding data plays little role in the testig and optimization of simulation force fields. Here, we aim to establish host-guest bindng data as a new benchmark for testing force fields, by assembling a panel of experimentally characterized, computationally tractable, host-guest systems, along with computational scripts which automate the calculation of their binding free energies and enthalpies and the comparison of these results with experiment. This "validation engine" will be used to test widely used force fields, and will also be shared freely with ther groups. Finally, we will integrate free energy simulation methods into two collaborative drug??discovery projects. One project centers on a human enzyme called soluble epoxide hydrolase, whose three-dimensional structure is known and which is therapeutically relevant to cardiovascular and inflammatory disease. In our preliminary studies, conventional docking approaches have provided little or no useful guidance; we now aim to apply more sophisticated fre energy simulation methods to this challenging case. The second project, which is at a earlier stage, concerns a bacterial virulence factor called Cif. This, too, is an epoide hydrolase, and its inhibition is expected to be helpful to patients with Pseudomonas pneumonia. We plan to use docking and free energy methods to help discover potent Cif inhibitors for use as chemical probes and, potentially, as first steps toward a ne medication.