CAREER: Data-driven computations to infer chemomechanical coupling from cryo-electron microscopy and support zero-cost online biophysics programs in high schools

职业：数据驱动计算，从冷冻电子显微镜推断化学机械耦合，并支持高中的零成本在线生物物理学项目

• 批准号: 1942763
• 负责人: Abhishek Singharoy
• 金额: $ 59.28万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-02-01 至 2025-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1942763&HistoricalAwards=false
• 关键词: CAREER; Data; driven; computations; infer

The growth of modern civilization is closely tied to controlled movement. This control is engineered by motors that extract energy from a fuel source and convert it to mechanical energy. Similarly, motors are an indispensable part of biology, and cells employ motor proteins to perform the energy conversions that sustain life. These molecular motors must minimize energy loss, be robust enough to withstand constant cycling, and display a high efficiency of energy conversion. Data science approaches, hand-in-hand with experimental work, bring forth the opportunity to learn how such features are achieved in a family of molecular assemblies that function as biological motors. The working principles revealed by this work will guide the design of better man-made, bioinspired devices that harness energy for the world's future needs, can potentially be utilized to enhance crop yields, or even tapped to understand the molecular origins of ageing. Advances in computer technology allow us to bring the excitement of research into how these powerful molecular machines work to high schools with limited computer resources by creating virtual laboratories that illustrate dynamic molecular machines in biological systems at no cost. Thus, leading edge concepts in biology can be taught and appreciated, and spur critical thinking, at otherwise underserved high schools. Molecular motors exist as large oligomeric protein complexes. A goal of this project to determine whether the oligomeric state or copy-number of the motor proteins is responsible for their low overall light- or nutrient-to-ATP yield, underscoring a "biological energy crisis". Three different V-ATPase motors will be investigated to decipher the coupling between ATP hydrolysis, reconfigurable oligomerization and metabolic activity. Reengineering of these motors offers tangible biosynthetic alternatives (mutants or chimeras) to improve biological energy turnover. The primary method for studying the motor proteins include molecular dynamics and multi-physics simulations. These computations will be guided by ATPase models derived from experimental data by machine learning of two-dimensional cryo-electron microscopy images. The computational results will be restrained by X-ray crystallographic and single-molecule imaging experiments. As a technological product, new schemes for deriving large-scale molecular dynamics from cryo-EM and crystallographic data will be developed. Addressing a major societal need, a cloud-based remote visualization platform will be created to offer free enquiry-based online education to underserved high schools.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

现代文明的发展与有控制的运动密切相关。这种控制是由电机设计的，电机从燃料源中提取能量并将其转换为机械能。同样，马达是生物学不可或缺的一部分，细胞利用马达蛋白进行维持生命的能量转换。这些分子发动机必须最大限度地减少能量损失，足够坚固以承受恒定的循环，并显示出高效率的能量转换。数据科学方法与实验工作携手并进，带来了学习这些功能如何在作为生物马达的分子组装家族中实现的机会。这项工作揭示的工作原理将指导更好的人造生物启发设备的设计，这些设备可以利用能源满足世界未来的需求，可以用于提高作物产量，甚至可以用于了解衰老的分子起源。计算机技术的进步使我们能够通过创建虚拟实验室，免费展示生物系统中的动态分子机器，将研究这些强大的分子机器如何工作的兴奋带到计算机资源有限的高中。因此，生物学的前沿概念可以在其他服务不足的高中教授和欣赏，并激发批判性思维。分子马达以大的寡聚蛋白质复合物的形式存在。该项目的一个目标是确定马达蛋白的寡聚状态或拷贝数是否是导致其整体光或营养与ATP产量低的原因，强调了“生物能源危机”。三种不同的V-ATP酶马达将被研究，以破译ATP水解，可重构寡聚和代谢活性之间的耦合。这些马达的再工程提供了有形的生物合成替代品（突变体或嵌合体），以改善生物能量周转。研究马达蛋白的主要方法包括分子动力学和多物理场模拟。这些计算将由通过对二维冷冻电子显微镜图像进行机器学习而从实验数据中推导出的ATP酶模型来指导。计算结果将受到X射线晶体学和单分子成像实验的制约。作为一种技术产品，将开发从cryo-EM和晶体学数据导出大规模分子动力学的新方案。 为了满足一个主要的社会需求，将创建一个基于云的远程可视化平台，为服务不足的高中提供免费的基于查询的在线教育。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

ChAdOx1 interacts with CAR and PF4 with implications for thrombosis with thrombocytopenia syndrome.

• DOI: 10.1126/sciadv.abl8213
• 发表时间: 2021-12-03
• 期刊: Science advances
• 影响因子: 13.6
• 作者: Baker AT;Boyd RJ;Sarkar D;Teijeira-Crespo A;Chan CK;Bates E;Waraich K;Vant J;Wilson E;Truong CD;Lipka-Lloyd M;Fromme P;Vermaas J;Williams D;Machiesky L;Heurich M;Nagalo BM;Coughlan L;Umlauf S;Chiu PL;Rizkallah PJ;Cohen TS;Parker AL;Singharoy A;Borad MJ
• 通讯作者: Borad MJ

Adaptive Ensemble Refinement of Protein Structures in High Resolution Electron Microscopy Density Maps with Radical Augmented Molecular Dynamics Flexible Fitting

• DOI: 10.1021/acs.jcim.3c00350
• 发表时间: 2023-09-04
• 期刊: JOURNAL OF CHEMICAL INFORMATION AND MODELING
• 影响因子: 5.6
• 作者: Sarkar，Daipayan;Lee，Hyungro;Singharoy，Abhishek
• 通讯作者: Singharoy，Abhishek

CryoFold: determining protein structures and data-guided ensembles from cryo-EM density maps.

• DOI: 10.1016/j.matt.2021.09.004
• 发表时间: 2021-10-06
• 期刊: MATTER
• 影响因子: 18.9
• 作者: Shekhar, Mrinal;Terashi, Genki;Gupta, Chitrak;Sarkar, Daipayan;Debussche, Gaspard;Sisco, Nicholas J.;Nguyen, Jonathan;Mondal, Arup;Vant, John;Fromme, Petra;Van Horn, Wade D.;Tajkhorshid, Emad;Kihara, Daisuke;Dill, Ken;Perez, Alberto;Singharoy, Abhishek
• 通讯作者: Singharoy, Abhishek

The ugly, bad, and good stories of large-scale biomolecular simulations

• DOI: 10.1016/j.sbi.2022.102338
• 发表时间: 2022-03-01
• 期刊: CURRENT OPINION IN STRUCTURAL BIOLOGY
• 影响因子: 6.8
• 作者: Gupta, Chitrak;Sarkar, Daipayan;Singharoy, Abhishek
• 通讯作者: Singharoy, Abhishek

Biophysics at the dawn of exascale computers

百亿亿次计算机初期的生物物理学

• DOI: 10.1016/j.bpj.2023.06.017
• 发表时间: 2023
• 期刊: Biophysical Journal
• 影响因子: 3.4
• 作者: Singharoy, Abhishek;Pérez, Alberto;Chipot, Chris
• 通讯作者: Chipot, Chris