课题基金 / 基金详情

SHF:Medium:Collaborative Research:Scaling Up Programmable and Algorithmic DNA Self-Assembly

SHF:Medium:Collaborative Research:Scaling Up Programmable and Algorithmic DNA Self-Assembly
SHF:中:合作研究:扩大可编程和算法 DNA 自组装
批准号:
1162589
负责人:
Erik Winfree
金额:
$40.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-09-01 至 2015-08-31

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中文摘要
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英文摘要
The dominant manufacturing paradigm for human technology has been top-down construction of objects, in the sense that a large entity manipulates smaller entities to put them together into a functional device. In contrast, for billions of years biological organisms have constructed objects using a bottom-up technology, in the sense that the pieces self-assemble or grow without outside assistance. For example, to make a complex molecular machine, enzymes within the cell might synthesize a number of proteins that then diffuse randomly until they bump into each other and click into place; while on a larger scale, a single cell might grow into an elephant. The bottom-up manufacturing paradigm has advantages that top-down methods are unlikely ever to achieve, such as the ability to create meter-scale objects from components with atomic-scale (nanometer) resolution and chemical functionality but it requires a level of exquisite control over molecular structure and function that human science and technology has not yet attained. We believe that the primary missing ingredient is information science and technology: information must be encoded within synthetic molecules to control their behavior and to create programmable molecular systems. In this research, the aim is to push the frontiers of information-based molecular self-assembly using DNA nanotechnology. The past fifteen years have seen the development of an abstract theory of algorithmic self-assembly (initiated by Winfree) that merges the mathematical theory of geometrical tiling, the statistical mechanical and kinetic theories of crystal growth, and the algorithmic theory of Turing machine computation. This theory shows how, in principle, synthetic DNA molecules called ?tiles? can be designed to carry information that directs their assembly into complex and sophisticated shapes and patterns. Just as a small program can produce a large and intricate output, a small tile set can result in the self-assembly of a large and intricate object the tile set is a program for controlling the molecular self-assembly process. Laboratory experiments in the past fifteen years have demonstrated the foundations of this theory using DNA tile sets on the order of two dozen tile types, i.e. very small molecular programs.In the past year, a new molecular motif for DNA tiles (developed by Yin) has been used to self-assemble molecular structures using up to 1000 distinct tile types that each has a unique target position within the structure, like a self-assembled molecular-scale jigsaw puzzle. This is the simplest type of molecular program. A major goal of the proposed work is demonstrating that the new ?single strand tile? motif can be used to create significantly more complicated self-assembly programs than have been seen to date by reusing distinct tile types in many locations and in an algorithmic fashion, much like living systems that reuse the same molecules in many different ways. Sophisticated algorithmic tile reuse of two dozen to perhaps 1000 or more distinct components vastly expands the capabilities of self-assembly programs. To achieve this, proposed work will (a) improve techniques for an important subroutine for controlling molecular growth, a binary counting process that terminates after growing a pre-specified distance; (b) develop methods and molecular structures for nucleating the growth of single-strand tiles with pre-specified information that serves as ?input? to the molecular program; (c) demonstrate algorithmic growth of single-strand tiles that perform Turing machine and/or cellular automaton computations; (d) investigate proofreading techniques for reducing the rate of errors during self-assembly; and (e) create software tools that facilitate the design and analysis of these complex molecular systems.
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FET: Small: Exploring the Computational Power of Stochastic Processes in Molecular Information Technology
  • 批准号:
    2008589
  • 项目类别:
    Standard Grant
  • 资助金额:
    $45.0万
  • 财政年份:
    2020
  • 负责人:
    Erik Winfree
  • 依托单位:
NSF Student Travel Grant for DNA24: The 24th International Conference on DNA Computing and Molecular Programming
  • 批准号:
    1844818
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.5万
  • 财政年份:
    2018
  • 负责人:
    Erik Winfree
  • 依托单位:
SHF: Small: A reconfigurable architecture for digital circuit computation by fast, robust, and leakless DNA strand displacement cascades
  • 批准号:
    1718938
  • 项目类别:
    Standard Grant
  • 资助金额:
    $46.5万
  • 财政年份:
    2017
  • 负责人:
    Erik Winfree
  • 依托单位:
Speaker support for workshop on advances in molecular programming and computing
  • 批准号:
    1340383
  • 项目类别:
    Standard Grant
  • 资助金额:
    $2.76万
  • 财政年份:
    2013
  • 负责人:
    Erik Winfree
  • 依托单位:
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