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: 10459484
• 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 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10459484
• 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.

摘要： 抗有丝分裂药物是治疗癌症的非常理想的化疗药物。传统抗有丝分裂药 药物通过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。 细胞。尽管这些抗有丝分裂药物取得了巨大的成功，但它们面临着两个重大问题：1) 严重的副作用；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，激动素是理想的替代药物靶点。虽然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的分离。此外，不同的 不同类型的动蛋白负责不同的微管功能，这使得药物的设计成为可能 对有丝分裂具有特异性，副作用较少。最近进行的实验工作揭示了 运动蛋白运动机制的研究成功。然而，许多动蛋白在原子水平上的机制仍然是 由于分辨率在时间和长度上的限制，目前的实验方法中缺少。 计算工作可以弥合原子细节和当前实验分辨率之间的差距 接近了。然而，由于Kinesin和Kinesin的大小，对Kinesin的模拟极具挑战性 微管系统。基于近几年快速改进的算法，PI将发展成大规模的 能够准确模拟大型动蛋白-微管复合体的模拟包。这个套餐 将被应用于揭示运动蛋白结合和运动特性的重要机制 激动素靶向抗有丝分裂药物设计。PI在软件开发方面有丰富的经验 蛋白质-蛋白质相互作用、静电计算、结合能计算、pKA计算、 以及大规模的模拟。此外，该协会还在研究动蛋白等方面积累了丰富的经验 分子马达。PI最近的计算工作揭示了运动蛋白之间的相互作用 结构域和微管是驱动蛋白运动特性的一个重要因素。以及疾病的突变 动蛋白与微管之间的静电力变化趋势很强。因此， 使用精确和全面的计算方法研究运动蛋白是一个非常有前途的方向 了解动蛋白的作用机制，发现针对抗有丝分裂药物的新的动蛋白。除了有丝分裂 动蛋白、其他动蛋白的突变和缺陷也是导致神经紊乱和严重 阿尔茨海默氏症、亨廷顿病、帕金森病和许多其他疾病。大规模的模拟 这项工作中开发的一揽子方案也将有助于发现这些疾病的新疗法。此外，这一点 该软件解决了传统仿真软件的规模限制问题，具有广泛的应用前景 研究复杂的生物系统，如动力蛋白-微管复合体、病毒衣壳组装、G蛋白 膜上的系统，以及许多其他系统。

项目成果

Computational Study on DNA Repair: The Roles of Electrostatic Interactions Between Uracil-DNA Glycosylase (UDG) and DNA.

• DOI: 10.3389/fmolb.2021.718587
• 发表时间: 2021
• 期刊: Frontiers in molecular biosciences
• 影响因子: 5
• 作者: Xie Y;Karki CB;Chen J;Liu D;Li L
• 通讯作者: Li L