Calculation of Protein-ligand Binding Affinity

蛋白质-配体结合亲和力的计算

• 批准号: 0235440
• 负责人: Kim Sharp
• 金额: --
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-01-15 至 2006-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0235440&HistoricalAwards=false
• 关键词: Calculation; Protein; ligand; Binding; Affinity

The goal of this research is to understand the basis of molecular recognition in biology. The overall objective is to calculate the binding constant from the structure and chemical properties of the molecules taking part in a reaction to understand the biochemical basis for high affinity binding. The research will use recent theoretical advances in the statistical mechanical treatment of binding, developments in methods for computer simulation of biomolecules, and recent experimental data on protein-ligand complexes. The basic method is to evaluate, using computer simulations, the appropriately weighted interaction free energy between protein and ligand by integrating over all the relevant degrees of freedom of the system: translational, rotational, internal and solvent, leading directly to evaluation of the binding constant. Molecular mechanics methods will be used for the first three components. Implicit solvent methods will be used to render the latter, most expensive integration, tractable. Recent algorithms for implicit solvation are, for the first time, accurate and fast enough to be used within the molecular mechanics integration step, so that the entire calculation can be done in a self-consistent way in a practical amount of computer time. Biological recognition is a fundamental property of proteins and other macromolecules. All living things contain proteins and many life processes rely on the right protein 'recognizing' the right molecule at the right time. A protein may be said to recognize another molecule when it attracts that molecule more strongly, and binds to it more tightly, than the many other molecules present. Strong attraction or binding depends on the protein being complementary in its shape and chemical properties to its binding partner. However, even if the detailed structures of the protein and its target are known, it is not enough to determine how tightly they will bind. To determine this, one would need to know all the different forces that act to attract or repel the two molecules, and sum them up accurately. Since thousands of atoms are involved, this is a formidable task. The approach is to construct a simulation of the protein and its binding partner in their environment on the computer, encoding the laws of physics and chemistry to describe how all the atoms interact, then 'run' computer simulation to determine how tightly the two bind, test the results against experiment, improve the description and repeat, iteratively making the simulation more realistic. This software for simulating protein recognition will be made available to the wider research and teaching community. Software to realistically simulate protein recognition would help researchers understand at a molecular level basic processes in living organisms, such as how cells communicate, and help train students in the principles of molecular recognition & simulation of molecules with computers. Specifically, this software will be used in the yearly course for graduates and undergraduates at the University of Pennsylvania, developed and taught by the PI entitled "Molecular modeling."

这项研究的目的是了解生物学中分子识别的基础。总体目标是从参与反应的分子的结构和化学性质计算结合常数，以了解高亲和力结合的生物化学基础。该研究将利用结合的统计力学处理的最新理论进展，生物分子计算机模拟方法的发展，以及蛋白质-配体复合物的最新实验数据。 基本方法是使用计算机模拟，通过整合系统的所有相关自由度（平移、旋转、内部和溶剂）来评估蛋白质和配体之间适当加权的相互作用自由能，从而直接评估结合常数。 分子力学方法将用于前三个组成部分。 隐式溶剂的方法将被用来使后者，最昂贵的集成，易于处理。隐式溶剂化的最新算法第一次足够精确和快速地用于分子力学积分步骤中，因此整个计算可以在实际的计算机时间内以自洽的方式完成。 生物识别是蛋白质和其他大分子的基本性质。所有生物都含有蛋白质，许多生命过程都依赖于正确的蛋白质在正确的时间“识别”正确的分子。 当一个蛋白质比其他许多分子更强烈地吸引另一个分子，并与之更紧密地结合时，可以说它识别另一个分子。 强吸引力或结合取决于蛋白质在其形状和化学性质上与其结合伴侣互补。 然而，即使蛋白质及其靶标的详细结构已知，也不足以确定它们将结合得有多紧密。为了确定这一点，人们需要知道吸引或排斥两个分子的所有不同的力，并准确地将它们相加。 由于涉及数千个原子，这是一项艰巨的任务。 该方法是在计算机上构建蛋白质及其结合伴侣在其环境中的模拟，编码物理和化学定律以描述所有原子如何相互作用，然后“运行”计算机模拟以确定两者结合的紧密程度，根据实验测试结果，改进描述并重复，迭代使模拟更加真实。 这一模拟蛋白质识别的软件将提供给更广泛的研究和教学界。逼真地模拟蛋白质识别的软件将帮助研究人员在分子水平上了解生物体的基本过程，例如细胞如何交流，并帮助培养学生使用计算机模拟分子的分子识别原理。 具体来说，该软件将用于宾夕法尼亚大学研究生和本科生的年度课程，由PI开发和教授，名为“分子建模”。"