Design Principles of Molecular Computing Using Engineered Enzymes

使用工程酶的分子计算设计原理

• 批准号: 1716623
• 负责人: Sagar Khare
• 金额: $ 30万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1716623&HistoricalAwards=false
• 关键词: Design; Principles; Molecular; Computing; Using

Every cell can be thought of as a computing device that takes a variety of physical and chemical stimuli as inputs, and combines them using an analog circuit of biomolecular interactions to generate outputs that aid its survival and perform its physiological function. Building such circuits from the bottom up, using basic biophysical principles of molecular recognition and chemical dynamics, provides insights into the underlying physiochemical design principles of biological systems, and allows predictive construction of useful circuits with chosen inputs and outputs that go beyond the ones found in nature. This project will develop a new class of fast biological circuitry that can detect a variety of chosen inputs, such as light and small molecule chemicals, and rapidly (and controllably) respond by generating cell survival and function-determining outputs. The principles being interrogated in this project should enable the design of artificial circuits for a variety of applications including controllable biomanufacturing of pharmaceuticals and biodegradation of pollutants. The project will offer training and research opportunities for several undergraduate students especially from the underrepresented communities via involvement of the local SACNAS chapter at Rutgers University started by the PI. This project will also support teams built by undergraduates to participate in tri-state area biomolecular design competitions.Several synthetic biological circuits using transcriptional networks in living cells, to enable biological computation with living cells, have been built in the last decade. However, the slow timescales for transcription-based circuit performance (hours to days), heterogeneity and lack of precise control over the levels of biological components, limit the speed, applicability and robustness of transcriptional circuits. The speed of the circuit is especially critical for applications where rapid sensing-and-response is required. This proposal's goal is the development of protease enzyme-based circuits using computationally designed/engineered proteases that can be made responsive to chosen input stimuli such as small molecule chemicals and light, and mutually orthogonal with respect to their substrate selectivity. Well-characterized, mutually orthogonal and diverse class of chemical/light-inducers of dimerization domains (as sensors), designed split-protease enzymes (as actuators), and a redesigned cell survival-regulating enzyme (as output) are being used to construct, characterize and optimize elementary logic gates and circuit elements. This project involves optimization of the emergent properties of circuit elements using chemical dynamics modeling methods that will allow combining multiple input signals in complex ways. Overall, this research develops a combined computational and experimental design strategy to construct stimulus-responsive, protease-based logic gates in cells, and involves optimizing their performance using a mathematical treatment of their emergent behavior in a chemical reaction network modeling framework. This project is jointly supported by the Molecular Biophysics Cluster of the Molecular and Cellular Biosciences Division in the Directorate for Biological Sciences and Cellular and Biochemical Engineering Cluster in the Chemical, Bioengineering, Environmental and Transport System Division of Engineering Directorate.

每个细胞都可以被认为是一个计算设备，它将各种物理和化学刺激作为输入，并使用生物分子相互作用的模拟电路将它们组合起来，以产生有助于其生存并执行其生理功能的输出。使用分子识别和化学动力学的基本生物物理学原理，自下而上构建这样的电路，可以深入了解生物系统的潜在物理化学设计原理，并允许预测构建具有超出自然界中发现的输入和输出的有用电路。该项目将开发一类新的快速生物电路，可以检测各种选定的输入，如光和小分子化学品，并通过产生细胞存活和功能决定输出来快速（可控）响应。在这个项目中被询问的原则应使人工电路的设计，包括可控的生物制药和生物降解的污染物的各种应用。该项目将通过PI发起的罗格斯大学当地SACNAS分会的参与，为几名本科生提供培训和研究机会，特别是来自代表性不足社区的本科生。本计划亦会资助大学生组成的团队参与三态生物分子设计比赛。在过去十年中，我们已成功利用活细胞的转录网络设计出多个合成生物电路，以实现活细胞的生物计算。然而，基于转录的电路性能的缓慢时间尺度（数小时到数天）、异质性和缺乏对生物组分水平的精确控制限制了转录电路的速度、适用性和鲁棒性。电路的速度对于需要快速检测和响应的应用尤为关键。该提案的目标是使用计算设计/工程化的蛋白酶开发基于蛋白酶的电路，所述蛋白酶可以响应于所选择的输入刺激，例如小分子化学品和光，并且相对于其底物选择性相互正交。良好的特点，相互正交和不同类别的化学/光诱导剂的二聚化域（作为传感器），设计的分裂蛋白酶（作为执行器），和一个重新设计的细胞存活调节酶（作为输出）正在被用来构建，表征和优化基本逻辑门和电路元件。该项目涉及使用化学动力学建模方法优化电路元件的紧急特性，该方法将允许以复杂的方式组合多个输入信号。总的来说，这项研究开发了一种结合计算和实验的设计策略，在细胞中构建刺激响应的基于蛋白酶的逻辑门，并在化学反应网络建模框架中使用其涌现行为的数学处理来优化其性能。该项目由生物科学理事会分子和细胞生物科学部的分子生物物理学集群和工程理事会化学，生物工程，环境和运输系统部的细胞和生物化学工程集群共同支持。

项目成果

Mathematical Models of Protease-Based Enzymatic Biosensors

• DOI: 10.1021/acssynbio.9b00279
• 发表时间: 2020-02-01
• 期刊: ACS SYNTHETIC BIOLOGY
• 影响因子: 4.7
• 作者: Agrawal, Deepak K.;Dolan, Elliott M.;Sontag, Eduardo D.
• 通讯作者: Sontag, Eduardo D.

Data-driven supervised learning of a viral protease specificity landscape from deep sequencing and molecular simulations

• DOI: 10.1073/pnas.1805256116
• 发表时间: 2019-01-02
• 期刊: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• 影响因子: 11.1
• 作者: Pethe, Manasi A.;Rubenstein, Aliza B.;Khare, Sagar D.
• 通讯作者: Khare, Sagar D.