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： 抗有丝分裂药物是传统抗有丝分裂药物非常理想的化疗药物。 通过药物解聚或稳定微管来破坏微管动力学，从而杀死过度活跃的癌症 尽管这些抗有丝分裂药物取得了巨大成功，但它们面临两个重大问题：1） 严重的副作用；以及2）对某些类型的癌症有很强的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点，而微管为有丝分裂提供了支架。 驱动蛋白与微管的相互作用负责有丝分裂分离。 不同类型的驱动蛋白负责不同的微管功能，从而为药物的设计提供了可能 最近进行的实验工作揭示了有丝分裂的特异性，且副作用较少。 然而，许多驱动蛋白在原子水平上的机制仍然存在。 由于时间和长度上分辨率的限制，当前的实验方法中缺失了这一点。 计算工作可以弥合原子细节与当前实验分辨率之间的差距 然而，由于驱动蛋白尺寸较大，对驱动蛋白的模拟极具挑战性。 基于近年来算法的快速改进，PI将开发大规模的微管系统。 能够准确模拟大型驱动蛋白-微管复合物的模拟包。 将用于揭示驱动蛋白结合和运动特征的重要机制，这将揭示 PI 在驱动蛋白靶向抗有丝分裂药物设计方面拥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 计算等领域 此外，PI还积累了丰富的驱动蛋白等研究经验。 PI 最近的计算工作揭示了驱动蛋白马达之间的相互作用。 结构域和微管是驱动蛋白运动特征和疾病突变的重要因素。 驱动蛋白与微管之间表现出强烈的静电力变化倾向。 使用准确且全面的计算方法研究驱动蛋白是一个非常有前途的方向 了解驱动蛋白的机制并发现除有丝分裂药物外的新驱动蛋白靶向抗有丝分裂药物。 驱动蛋白、其他驱动蛋白的突变和缺陷也会导致神经系统疾病和严重的 阿尔茨海默病、亨廷顿病、帕金森病等多种疾病的大规模模拟。 这项工作中开发的软件包也将有助于发现这些疾病的新疗法。 包将解决传统仿真包的规模限制问题，因此可以广泛使用 研究复杂的生物系统，例如动力蛋白-微管复合物、病毒衣壳组装、G 蛋白 膜上的系统，等等。