Developing and applying large-scale simulation approach to understand the mechanisms of kinesins' motilities along microtubules

开发和应用大规模模拟方法来了解驱动蛋白沿微管运动的机制

• 批准号: 10261461
• 负责人: Lin Li
• 金额: $ 37.75万
• 依托单位: UNIVERSITY OF TEXAS EL PASO
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10261461
• 关键词: Algorithms; Alzheimer' s Disease; Antimitotic Agents; Antineoplastic Agents; Area; Binding; C-terminal; CDKN1B gene; Capsid; Chemotherapy-Oncologic Procedure; Complex; Defect; Disease; Drug Design; Drug Targeting; Drug resistance; Dynein ATPase; Electrostatics; Face; GTP-Binding Proteins; Grain; Human; Huntington Disease; Individual; Interruption; Kinesin; Length; Light; Membrane; Microtubule Stabilization; Microtubules; Mitosis; Mitotic; Modeling; Molecular Motors; Monte Carlo Method; Motion; Motor; Mutation; Outcome; Parkinson Disease; Pharmaceutical Preparations; Resolution; Role; Speed; System; Time; Viral; Work; base; cancer cell; cancer therapy; cancer type; cell motility; chemotherapy; complex biological systems; depolymerization; design; experience; large scale simulation; nervous system disorder; novel; programs; protein protein interaction; refractory cancer; scaffold; side effect; simulation; software development; success; tool

Abstract: Anti-mitotic drugs are highly desirable chemotherapy drugs for cancer treatment. Traditional anti-mitotic drugs destroy microtubule dynamics by depolymerizing or stabilizing microtubules to kill the overactive cancer cells. Even though these anti-mitotic drugs have achieved great success, they face two significant issues: 1) Serious side effects; and 2) Strong drug resistance for some types of cancers. To overcome these two issues, kinesins are recently found to be ideal alternative drug targets. While microtubules provide the scaffold for mitosis, it is the interaction of kinesins with microtubule that is responsible for mitotic separation. Moreover, different types of kinesins are responsible for different microtubule functions, allowing for the possible design of drugs specific to mitosis with fewer side effects. Recent experimental works have been performed to reveal mechanisms of kinesin motility successfully. However, many kinesins’ mechanisms at the atomic level are still missing in current experimental approaches due to the limitations of resolutions, both in time and in length. Computational works can bridge the gap between atomic details and the resolutions of current experimental approaches. However, simulations for kinesins are extremely challenging due to the large size of kinesin and microtubule system. Based on fast improvements of algorithms in recent years, the PI will develop a large-scale simulation package that is capable of simulating large kinesin-microtubule complexes accurately. This package will be applied to reveal the important mechanisms for kinesins’ binding and motility features, which will shed light on kinesin targeting anti-mitotic drug design. The PI has extensive experience of software developments in the areas of protein-protein interactions, electrostatic calculations, binding energy calculations, pKa calculations, and large-scale simulations. Besides, the PI also has gained rich experience of studying kinesins and other molecular motors. The PI’s recent computational woks have revealed that the interaction between kinesin motor domains and the microtubule is an important factor for kinesin’s motility features. And disease mutations on kinesins show strong tendency of electrostatic force changes between kinesins and microtubules. Therefore, investigating kinesins using accurate and comprehensive computational approaches is a very promising direction to understand the mechanisms of kinesins and discover new kinesin targeting anti-mitotic drugs. Besides mitotic kinesins, mutations and defects on other kinesins are also responsible for neurological disorders and serious diseases such as Alzheimer, Huntington, Parkinson disease and many others. The large-scale simulation package developed in this work will also help to discover novel treatments of those diseases. Furthermore, this package will solve the scale limitation issue of traditional simulation packages and therefore can be widely used to study complex biological systems, such as the dynein-microtubule complex, viral capsid assembly, G-proteins systems on the membrane, and many others.

抽象的： 抗隔离药物是用于癌症治疗的高度可取的化学疗法药物。传统的抗丝质酸 药物通过解聚或稳定微管来破坏微管动力学，以杀死过度活跃的癌症 细胞。即使这些抗隔离药物取得了巨大成功，但它们面临两个重要问题：1） 严重的副作用； 2）某些类型的癌症的强烈耐药性。为了克服这两个问题， 最近发现驱动蛋白是理想的替代药物靶标。虽然微管提供有丝分裂的支架，但 驱动蛋白与微管的相互作用是导致有丝分离的。而且，不同 驱动蛋白的类型负责不同的微管功能，从而允许药物的设计 特定于有丝分裂，副作用较少。最近进行了实验工作以揭示 驱动蛋白运动的机理成功。但是，许多金斯在原子水平上的机制仍然是 由于分辨率的局限性，无论是时间还是长时间，目前的实验方法缺失。 计算工作可以弥合原子细节与当前实验的分辨率之间的差距 方法。但是，由于驱动蛋白的大尺寸和 微管系统。基于近年来算法的快速改进，PI将开发大型 能够准确模拟大型驱动蛋白 - 微管复合物的仿真软件包。这个包 将应用于揭示Kines的结合和运动特征的重要机制，这将脱落 靶向抗隔离药物设计的驱动蛋白的光。 PI具有丰富的软件开发经验 蛋白质蛋白质相互作用，静电计算，结合能计算，PKA计算的区域， 和大规模模拟。此外，PI还获得了研究驱动素和其他研究的丰富经验 分子电动机。 PI最近的计算锅已经表明，驱动蛋白电机之间的相互作用 域和微管是动力蛋白运动特征的重要因素。和疾病突变 驱动蛋白表现出强烈的静电趋势在驱动力和微管之间变化。所以， 使用准确而全面的计算方法研究动力素是一个非常有前途的方向 了解驱动蛋白的机制并发现靶向抗溶毒药物的新动力蛋白。除了有丝分裂 动力素，其他驱动蛋白的突变和缺陷也导致神经系统疾病和严重 阿尔茨海默氏症，亨廷顿，帕金森氏病等疾病。大规模模拟 这项工作中开发的软件包还将有助于发现这些疾病的新颖疗法。此外，这个 软件包将解决传统仿真软件包的规模限制问题，因此可以广泛使用 研究复杂的生物系统，例如Dynein-Microtube复合物，病毒式衣壳组件，G蛋白 膜上的系统以及许多其他系统。