Hierarchical, Force-Based Method to Predict the Stability of a Protein

基于力的分层方法预测蛋白质的稳定性

• 批准号: BB/K001558/1
• 负责人: Richard Henchman
• 金额: $ 36.65万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2013
• 资助国家: 英国
• 起止时间: 2013 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FK001558%2F1
• 关键词: Hierarchical; Force; Based; Method; Predict

Proteins play an essential role in living organisms. They are important structurally in bones, muscle, connective tissue and skin, and are responsible for the majority of biomolecular processes such as synthesis, degradation, signalling, transport and motion. In addition to their biological role, they are invaluable technologically as catalysts, pharmaceuticals, sensors, biomaterials and in many other applications. However, proteins are large and complex molecules made up of hundreds of amino acids joined together in a long chain. We still have much learn about what makes proteins adopt particular shapes in order to carry out specific functions. The goal of the proposed research is to develop and implement a new method to predict protein stability. This new method will not only be able to predict stability but also explain in intricate detail how this stability comes about. Such detail is essential to understanding protein function and guide the design of new proteins. Computer simulation is a valuable way to predict molecular structure and stability. It generates a large number of structures which can be used to predict stability. While a number of methods have already been proposed to predict stability using computer simulation, they are largely based on methods appropriate for small molecules are not yet accurate and reliable enough to be useful for proteins. My approach will incorporate a number of new features that reflect the complexity of proteins, building on my experience to calculate the stability of liquids and solutions and to study the structure of proteins. This approach has already led to the most accurate characterisation yet of the structure and dynamics of water, still a complex and controversial question. Water is a key component surrounding proteins that will explicitly accounted for and not be ignored as many approaches do. Another key attribute of our approach is that the entropy is evaluated hierarchically over the many length scales of a protein. Furthermore, our approach is able to handle the intrinsic flexibility in a protein by using the forces on atoms to determine how mobile they are, defining structure in terms of contacts, and considering all of the astronomical number of configurations. The new tool will be made publicly available to all scientists to help them study their systems. Having developed the method, we will test it, firstly by measuring how well it predicts the solubility in water of a range of small organic molecules by comparing with results obtained using another simulation method that does work for small systems. Next we will examine how well the method works at predicting stability of small proteins by comparing with the relative stabilities measured from very long simulations. The third test will be in an experiment called CASP whereby participants have to predict protein structure based on the sequence of amino acids. As well as testing we will consider two applications: firstly, we will apply the method to determine the stability of the same set of small proteins as they are folded in order to learn about the mechanism of protein folding; secondly, we will examine how various solutes and ions stabilise or destabilise protein structure. The information gained from addressing both these questions will substantially improve our ability to understand protein function and design new proteins.

蛋白质在生物体中起着至关重要的作用。它们在骨骼、肌肉、结缔组织和皮肤中具有重要的结构作用，并负责大多数生物分子过程，如合成、降解、信号传导、运输和运动。除了它们的生物学作用外，它们在技术上作为催化剂、药物、传感器、生物材料和许多其他应用都是无价的。然而，蛋白质是由数百个氨基酸连接在一起的长链组成的大而复杂的分子。关于是什么使蛋白质采用特定的形状来执行特定的功能，我们仍然有很多了解。提出的研究目标是开发和实施一种预测蛋白质稳定性的新方法。这种新方法不仅能够预测稳定性，而且还能详细解释这种稳定性是如何产生的。这些细节对于理解蛋白质的功能和指导新蛋白质的设计至关重要。计算机模拟是预测分子结构和稳定性的一种有价值的方法。它产生了大量的结构，可以用来预测稳定性。虽然已经提出了许多方法来使用计算机模拟来预测稳定性，但它们主要是基于适用于小分子的方法，这些方法还不够精确和可靠，无法用于蛋白质。我的方法将结合一些反映蛋白质复杂性的新特征，建立在我计算液体和溶液稳定性以及研究蛋白质结构的经验之上。这种方法已经导致了迄今为止对水的结构和动力学最精确的描述，这仍然是一个复杂而有争议的问题。水是蛋白质周围的关键成分，它将被明确地解释，而不是像许多方法那样被忽视。我们方法的另一个关键属性是熵是在蛋白质的许多长度尺度上分层评估的。此外，我们的方法能够处理蛋白质的内在灵活性，通过使用原子上的力来确定它们的移动程度，根据接触来定义结构，并考虑所有天文数字的配置。这个新工具将公开提供给所有科学家，以帮助他们研究他们的系统。在开发了该方法之后，我们将对其进行测试，首先通过将其与另一种适用于小系统的模拟方法获得的结果进行比较，来测量它预测一系列小有机分子在水中的溶解度。接下来，我们将通过比较从非常长的模拟中测量的相对稳定性来检验该方法在预测小蛋白质稳定性方面的效果。第三项测试将在一个名为CASP的实验中进行，参与者必须根据氨基酸序列预测蛋白质结构。除了测试，我们还将考虑两种应用：首先，我们将应用该方法来确定同一组小蛋白质折叠时的稳定性，以了解蛋白质折叠的机制；其次，我们将研究各种溶质和离子如何稳定或破坏蛋白质结构。从解决这两个问题中获得的信息将大大提高我们理解蛋白质功能和设计新蛋白质的能力。

项目成果

Macromolecular Entropy Can Be Accurately Computed from Force

• DOI: 10.1021/ct500684w
• 发表时间: 2014-11-01
• 期刊: JOURNAL OF CHEMICAL THEORY AND COMPUTATION
• 影响因子: 5.5
• 作者: Hensen, Ulf;Graeter, Frauke;Henchman, Richard H.
• 通讯作者: Henchman, Richard H.

Protons and Hydroxide Ions in Aqueous Systems.

• DOI: 10.1021/acs.chemrev.5b00736
• 发表时间: 2016-07-13
• 期刊: Chemical reviews
• 影响因子: 62.1
• 作者: Agmon N;Bakker HJ;Campen RK;Henchman RH;Pohl P;Roke S;Thämer M;Hassanali A
• 通讯作者: Hassanali A

Entropy of Simulated Liquids Using Multiscale Cell Correlation.

• DOI: 10.3390/e21080750
• 发表时间: 2019-07-31
• 期刊: Entropy (Basel, Switzerland)
• 作者: Ali HS;Higham J;Henchman RH
• 通讯作者: Henchman RH

Parameter-Free Hydrogen-Bond Definition to Classify Protein Secondary Structure.

• DOI: 10.1021/acs.jpcb.6b02571
• 发表时间: 2016-04
• 期刊: The journal of physical chemistry. B
• 作者: Hasti Haghighi;J. Higham;Richard H. Henchman

Water Determines the Structure and Dynamics of Proteins.

• DOI: 10.1021/acs.chemrev.5b00664
• 发表时间: 2016-07-13
• 期刊: Chemical reviews
• 影响因子: 62.1
• 作者: Bellissent-Funel MC;Hassanali A;Havenith M;Henchman R;Pohl P;Sterpone F;van der Spoel D;Xu Y;Garcia AE
• 通讯作者: Garcia AE