Models and Algorithms for Molecular Programming

分子编程模型和算法

• 批准号: RGPIN-2022-03784
• 负责人: Condon, Anne
• 金额: $ 3.5万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=749796
• 关键词: Models; Algorithms; Molecular; Programming

Bio-molecules do amazing things in the cell. Some store information, others translate that information to produce "actor" molecules that sense their environment and respond accordingly, via sophisticated networks of reactions. Bio-molecules self-assemble into scaffolds, or form compartments through which select molecules enter and exit. Molecular interaction is also the basis for movement and transport of cargo in the cell. Researchers in the field of DNA computing and molecular programming ask: how can we use nature's versatile bio-molecules in new ways: to compute, or to build structures and molecular robots? My long-term goal is to devise new ways to program molecules, by designing and analyzing algorithms expressed as Chemical Reaction Networks (CRNs) and other molecular programming models, by developing effective schemes to compile such algorithms down to DNA implementations, and by understanding the limits of what is possible. My short-term objectives will focus on two steps in the compilation process. (1) DNA strand displacement systems (DSDs) provide a valuable intermediate description of molecular computations, between CRNs and a DNA implementation. Currently, CRN-to-DSD compilation schemes vary across research labs, with respect to vulnerability to errors or the ease with which they can be implemented or verified. I will study new ways to compile CRNs down to DSDs, both in solution and on surfaces, so as to simplify the multi-stranded complexes involved, thereby reducing errors and using strands efficiently. I also want to understand limits to efficient compilation schemes. (2) DSDs are further compiled down to DNA strands, by associating a sequence of A,C,G,T bases with each abstract DSD domain. Kinetic simulators, such as Caltech's Multistrand simulator, are used to ensure that DNA implementations faithfully replicate the intended DSD behaviours. We will improve the accuracy and usability of Multistrand, by inferring improved kinetic parameters and by developing coarse-grained approximations of Multistrand's stochastic model of DNA reactions. These objectives provide fertile opportunities for collaborative, interdisciplinary, HQP training. A newly recruited postdoc and two graduate students are already working on our objectives, bringing valuable expertise of their own. I will provide a stimulating, supportive environment for these and future advisees, positioning them for meaningful careers. Computations happen in silico, in the brain, and in the cell through chemical reactions. The last of these is perhaps the least understood, and is particularly fascinating because of the ways that tiny bio-molecules both encode the script and are the actors in their environments. Our research will advance our ability to program bio-molecules in creative ways, and hopefully pave the way for exciting new applications of computing principles in synthetic biology.

生物分子在细胞中做着令人惊奇的事情。一些储存信息，另一些翻译信息以产生“演员”分子，这些分子通过复杂的反应网络感知环境并做出相应的反应。生物分子自组装成支架，或形成选择性分子进出的隔间。分子间的相互作用也是细胞内货物移动和运输的基础。DNA计算和分子编程领域的研究人员提出了一个问题：我们如何以新的方式使用自然界的多功能生物分子：计算，或构建结构和分子机器人？ 我的长期目标是通过设计和分析化学反应网络（CRN）和其他分子编程模型表达的算法，通过开发有效的方案来编译这些算法到DNA实现，并通过了解可能的极限来设计新的分子编程方法。我的短期目标将集中在编译过程中的两个步骤。(1)DNA链置换系统（DSD）提供了一种介于CRN和DNA实现之间的有价值的分子计算中间描述。目前，CRN到DSD的编译方案因研究实验室而异，涉及到错误的脆弱性或它们可以实现或验证的容易性。我将研究将CRN编译为DSD的新方法，无论是在溶液中还是在表面上，以便简化所涉及的多链复合物，从而减少错误并有效地使用链。我还想了解高效编译方案的局限性。(2)通过将A、C、G、T碱基序列与每个抽象DSD结构域相关联，DSD被进一步编译为DNA链。动力学模拟器，如加州理工学院的多股模拟器，用于确保DNA实现忠实地复制预期的DSD行为。我们将通过推断改进的动力学参数和开发DNA反应的多链随机模型的粗粒度近似来提高多链的准确性和可用性。这些目标为合作、跨学科的HQP培训提供了丰富的机会。一名新招募的博士后和两名研究生已经在为我们的目标工作，带来了他们自己宝贵的专业知识。我将为这些和未来的学员提供一个激励，支持的环境，定位他们有意义的职业生涯。计算发生在计算机中，在大脑中，通过化学反应在细胞中。最后一个可能是最不了解的，而且特别迷人，因为微小的生物分子既编码脚本，又是环境中的演员。我们的研究将提高我们以创造性的方式编程生物分子的能力，并有望为合成生物学中计算原理的令人兴奋的新应用铺平道路。