A main goal of synthetic biology is the design of logic gates that can reprogram cells to perform various user-defined tasks. One approach is the use of ribozyme-based logic gates (ribogates) consisting of catalytic RNA strands. However, existing ribogate design approaches face limitations in terms of complexity, diversity, ease of use, and reliability. To address these challenges, we introduce a multi-objective evolutionary algorithm called Truth-Seq-Er, which generates diverse and complex ribogate designs while improving user-friendliness and accessibility. Truth-Seq-Er uses a quality diversity approach and a novel technique called viability nullification to design 1, 2, and 3-input integrated ribogates that implement both linearly separable and inseparable functions. By requiring only a target Boolean function as input, the algorithm eliminates the need for domain knowledge and streamlines the design process. The diverse designs generated by Truth-Seq-Er are robust against unexpected requirements and provide a large, unbiased dataset for characterizing candidate ribogates. Moreover, we propose a graph-based model for ribogate operation and analyze the design principles shared by different ribogate families. The results demonstrate the potential of Truth-Seq-Er in advancing ribogate design and contributing to the development of novel synthetic biology and unconventional computing applications. Truth-Seq-Er is available for download at https://github.com/nickkamel/Truth_Seq_Er_CLI.

合成生物学的一个主要目标是设计逻辑门，可以对细胞进行重新编程以执行各种用户定义的任务。一种方法是使用由催化 RNA 链组成的基于核酶的逻辑门（核糖门）。然而，现有的核糖门设计方法在复杂性、多样性、易用性和可靠性方面面临限制。为了应对这些挑战，我们引入了一种名为 Truth-Seq-Er 的多目标进化算法，它可以生成多样化且复杂的核糖门设计，同时提高用户友好性和可访问性。Truth-Seq-Er 使用质量多样性方法和一种称为生存力无效化的新技术来设计 1、2 和 3 输入集成核糖门，实现线性可分离和不可分离功能。只需要一个目标布尔函数作为输入，该算法消除了对领域知识的需求并简化了设计过程。Truth-Seq-Er 生成的多样化设计能够满足意外要求，并提供大型、无偏见的数据集来表征候选核糖核酸酶。此外，我们提出了一种基于图的核糖门操作模型，并分析了不同核糖门家族共享的设计原则。结果证明了 Truth-Seq-Er 在推进核糖门设计以及促进新型合成生物学和非常规计算应用的开发方面的潜力。Truth-Seq-Er 可从 https://github.com/nickkamel/Truth_Seq_Er_CLI 下载。用于表征候选核糖核酸门的无偏数据集。此外，我们提出了一种基于图的核糖门操作模型，并分析了不同核糖门家族共享的设计原则。结果证明了 Truth-Seq-Er 在推进核糖门设计以及促进新型合成生物学和非常规计算应用的开发方面的潜力。Truth-Seq-Er 可从 https://github.com/nickkamel/Truth_Seq_Er_CLI 下载。用于表征候选核糖核酸门的无偏数据集。此外，我们提出了一种基于图的核糖门操作模型，并分析了不同核糖门家族共享的设计原则。结果证明了 Truth-Seq-Er 在推进核糖门设计以及促进新型合成生物学和非常规计算应用的开发方面的潜力。Truth-Seq-Er 可从 https://github.com/nickkamel/Truth_Seq_Er_CLI 下载。