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Computing Properties of Thermodynamic Binding Networks: An Integer Programming Approach
arXiv - CS - Emerging Technologies Pub Date : 2020-11-20 , DOI: arxiv-2011.10677
David Haley, David Doty

The thermodynamic binding networks (TBN) model was recently developed as a tool for studying engineered molecular systems. The TBN model allows one to reason about their behavior through a simplified abstraction that ignores details about molecular composition, focusing on two key determinants of a system's energetics common to any chemical substrate: how many molecular bonds are formed, and how many separate complexes exist in the system. We formulate as an integer program the NP-hard problem of computing stable configurations of a TBN (a.k.a., minimum energy: those that maximize the number of bonds and complexes). We provide open-source software that solves these formulations, and give empirical evidence that this approach enables dramatically faster computation of TBN stable configurations than previous approaches based on SAT solvers. Our setup can also reason about TBNs in which some molecules have unbounded counts. These improvements in turn allow us to efficiently automate verification of desired properties of practical TBNs. Finally, we show that the TBN's Graver basis (a kind of certificate of optimality in integer programming) has a natural interpretation as the "fundamental components" out of which locally minimal energy configurations are composed. This characterization helps verify correctness of not only stable configurations, but entire "kinetic pathways" in a TBN.

中文翻译:

热力学绑定网络的计算属性:整数编程方法

热力学结合网络(TBN)模型是最近开发的,用于研究工程分子系统的工具。TBN模型允许通过简化的抽象来推理其行为,该抽象忽略了有关分子组成的详细信息,着重于任何化学底物共有的系统能量的两个关键决定因素:形成了多少分子键,以及在其中存在多少个独立的配合物。系统。我们将计算TBN稳定配置的NP难题(即最小能量:使键和络合物数量最大化的NP问题)公式化为整数程序。我们提供了可以解决这些问题的开源软件,并提供了经验证据,表明该方法比基于SAT求解器的先前方法能够显着更快地计算TBN稳定配置。我们的设置还可以推断出某些分子具有无限计数的TBN。这些改进又使我们能够有效地自动验证实用TBN的所需属性。最后,我们证明TBN的Graver基础(一种整数编程中的最优性证明)对“基本成分”具有自然的解释,其中组成了局部最小的能量配置。此特征不仅有助于验证TBN中稳定配置的正确性,而且还可以验证整个“运动路径”的正确性。Graver基础(一种整数编程中的最优性证明)自然地解释为组成基本最小能量配置的“基本组成部分”。此特征不仅有助于验证TBN中稳定配置的正确性,而且还可以验证整个“运动路径”的正确性。Graver基础(一种整数编程中的最优性证明)自然地解释为组成基本最小能量配置的“基本组成部分”。此特征不仅有助于验证TBN中稳定配置的正确性,而且还可以验证整个“运动路径”的正确性。
更新日期:2020-11-25
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