Emergent Properties of Complex Systems: From Atoms to Macromolecules; from Humans to Societies

复杂系统的涌现性质：从原子到大分子；

基本信息

批准号：
10622276
负责人：
MICHAEL LEVITT
金额：
$ 55.93万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-06-01 至 2028-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10622276
关键词：
2019-nCoV Accidents Behavior Biology COVID-19 Cessation of life Collaborations Community Services Complex Computational Biology Computers Coronavirus DNA Structure Data Data Analyses Drug Targeting Epidemic Future Gases Growth Health Human Infection Lead Logistics Mentors Modeling Modernization Molecular Peptides Performance Persons Philosophy Population Principal Investigator Productivity Property Protein Conformation Proteins Public Health Recovery Research Ribosomes Sampling Scientist Societies Structure System Techniques Time Viral Virus Virus Diseases Work Workplace atomic interactions career computer code computer framework curve fitting deep learning drug development drug discovery experience fascinate interdisciplinary approach macromolecule molecular dynamics neural network architecture novel outreach particle protein structure respiratory virus simulation transmission process

项目摘要

Project Summary (30 lines) With its revised title “Emergent Properties of Complex Systems: From Atoms to Macromolecules; from Humans to Societies” this proposal has been broadened by adding data-analysis & simulation on a problem of grave current concern: namely how an air-borne virus like SARS-2-CoV spread in human population. Getting involved by accident, I became fascinated with how the numbers of daily cases & deaths group with time and what is the physical mechanism that make the data follow the Gompertz function. Michael Levitt, the Principal Investigator has a long career of independent scientific research that started in 1967 when he was one of the first to work in computational biology. His early work set up the conceptual, theoretical and computational framework for protein and DNA structure refinement, structure analysis and macromolecular simulations. He makes computer codes available and has been productive, scientifically rigorous and impactful for half a century. This approaches is continued here by a PI committed to mentoring young scientists as well as engaging in sustained research-community service and public outreach. 1. Protein Structure Refinement with Deep Equivariant Networks. We propose to use Deep Learning technique to refine models of proteins. We anticipate that such an approach, combined with the power of modern neural net architectures and computational performance of hardware will enable efficient sampling of the protein conformational space near the native state and will systematically provide structures with accuracy useful for drug development purposes. 2. Functional Dynamics of Ribosome. Our experience with structure curation will lead to a useful computer package for others. Our work on Ribosome dynamics will provide a model of how peptides such as SecM can stall the ribosome. Structures sampled from our MD simulations could also be used as potential targets for drug discovery. 3. Epidemic Analysis, Curve-Fitting and Simulation. Applied to SARS-Cov-2 and COVID-19, we show that viral spread follows the Gompertz growth function rather than commonly assumed Logistics or Exponential functions. This means that the population transmitting the infection is not uniform. Network simulation of viral spread shows that only when the connection network is scale-free does the simulated epidemic follow the Gompertz function. We will model a physical system with scale-free connectivity using molecular dynamics to simulate a 2D gas of particles with a wide range of masses. This novel multi- disciplinary approach may also apply to future respiratory viruses to enable better control of their spread. Studying biomedically significant systems in collaboration with experimental colleagues will reveal fascinating details of biology in action. We expect this work will help elucidate the relationship between underlying structure and function in complex systems, extending from macromolecular machines to human societies.

项目概要（30行）其修订后的标题为“复杂系统的涌现性质：从原子到大分子； “人类到社会”这一提案已通过添加对问题的数据分析和模拟而得到扩展当前最令人担忧的问题是：像 SARS-2-CoV 这样的空气传播病毒如何在人群中传播。一次偶然的机会，我开始对每天的病例数和死亡人数如何与时间以及使数据遵循 Gompertz 函数的物理机制是什么。首席研究员迈克尔·莱维特 (Michael Levitt) 拥有长期的独立科学研究生涯，始于 1967 年，他是最早从事计算生物学工作的人之一，他的早期工作确立了这一概念：蛋白质和 DNA 结构细化、结构分析和分析的理论和计算框架他提供了计算机代码，并且富有成效且科学。半个世纪以来，这种方法一直是严格而有影响力的，由一位致力于指导的 PI 延续。年轻科学家以及参与持续的研究社区服务和公共宣传。 1. 利用深度等变网络进行蛋白质结构细化我们建议使用深度学习。我们预计这种方法与蛋白质模型的力量相结合。现代神经网络架构和硬件的计算性能将实现高效采样接近天然状态的蛋白质构象空间，并将系统地提供结构准确性对于药物开发目的很有用。 2. 核糖体的功能动力学。我们在结构管理方面的经验将带来一台有用的计算机。我们在核糖体动力学方面的工作将为其他人提供一个肽如何运作的模型。可以使核糖体停滞从我们的 MD 模拟中采样的结构也可以用作潜在的。药物发现的目标。 3. 我们展示了应用于 SARS-Cov-2 和 COVID-19 的流行病分析、曲线拟合和模拟。病毒式传播遵循 Gompertz 增长函数，而不是通常假设的物流或这意味着传播感染的人群网络并不均匀。病毒传播的模拟表明，只有当连接网络是无标度时，模拟的传播才有效。我们将使用 Gompertz 函数对具有无标度连接的物理系统进行建模。分子动力学来模拟具有广泛质量的二维粒子气体。纪律方法也可能适用于未来的呼吸道病毒，以更好地控制其传播。与实验同事合作研究具有生物医学意义的系统将揭示令人着迷的我们期望这项工作将有助于阐明潜在的生物学之间的关系。复杂系统中的结构和功能，从大分子机器延伸到人类社会。

项目成果

期刊论文数量（47）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Insights on cross-species transmission of SARS-CoV-2 from structural modeling.

DOI：
10.1371/journal.pcbi.1008449
发表时间：
2020-12
期刊：
PLoS computational biology
影响因子：
4.3
作者：
Rodrigues JPGLM;Barrera-Vilarmau S;M C Teixeira J;Sorokina M;Seckel E;Kastritis PL;Levitt M
通讯作者：
Levitt M

Probing Interplays between Human XBP1u Translational Arrest Peptide and 80S Ribosome.

DOI：
10.1021/acs.jctc.1c00796
发表时间：
2022-03-08
期刊：
Journal of chemical theory and computation
影响因子：
5.5
作者：
Di Palma F;Decherchi S;Pardo-Avila F;Succi S;Levitt M;von Heijne G;Cavalli A
通讯作者：
Cavalli A

Protein-Ligand Binding Free-Energy Calculations with ARROW─A Purely First-Principles Parameterized Polarizable Force Field.

DOI：
10.1021/acs.jctc.2c00930
发表时间：
2022-12-13
期刊：
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
影响因子：
5.5
作者：
Nawrocki, Grzegorz;Leontyev, Igor;Sakipov, Serzhan;Darkhovskiy, Mikhail;Kurnikov, Igor;Pereyaslavets, Leonid;Kamath, Ganesh;Voronina, Ekaterina;Butin, Oleg;Illarionov, Alexey;Olevanov, Michael;Kostikov, Alexander;Ivahnenko, Ilya;Patel, Dhilon S.;Sankaranarayanan, Subramanian K. . R. S.;Kurnikova, Maria G.;Lock, Christopher;Crooks, Gavin E.;Levitt, Michael;Kornberg, Roger D.;Fain, Boris
通讯作者：
Fain, Boris

Aminoglycoside ribosome interactions reveal novel conformational states at ambient temperature.

氨基糖苷核糖体相互作用揭示了环境温度下的新构象状态。

DOI：
10.1093/nar/gky693
发表时间：
2018
期刊：
Nucleic acids research
影响因子：
14.9
作者：
O'Sullivan,MaryE;Poitevin,Frédéric;Sierra,RaymondG;Gati,Cornelius;Dao,EHan;Rao,Yashas;Aksit,Fulya;Ciftci,Halilibrahim;Corsepius,Nicholas;Greenhouse,Robert;Hayes,Brandon;Hunter,MarkS;Liang,Mengling;McGurk,Alex;Mbgam,Paul;O
通讯作者：
O

Intermolecular correlations are necessary to explain diffuse scattering from protein crystals.

分子间相关性对于解释蛋白质晶体的漫散射是必要的。