Design of Complex Biologically Based Nanoscale Systems Using Multi-Agent Simulations and Structure–Behavior–Function Representations

Abstract

The process of designing integrated biological systems across scales is difficult, with challenges arising from the modeling, understanding, and search of complex system design spaces. This paper explores these challenges through consideration of how stochastic nanoscale phenomenon relate to higher level systems functioning across many scales. A domain-independent methodology is introduced which uses multi-agent simulations to predict emergent system behavior and structure–behavior–function (SBF) representations to facilitate design space navigation. The methodology is validated through a nanoscale design application of synthetic myosin motor systems. In the multi-agent simulation, myosins are independent computational agents with varied structural inputs that enable differently tuned mechanochemical behaviors. Four synthetic myosins were designed and replicated as agent populations, and their simulated behavior was consistent with empirical studies of individual myosins and the macroscopic performance of myosin-powered muscle contractions. However, in order to configure high performance technologies, designers must effectively reason about simulation inputs and outputs; we find that counter-intuitive relations arise when linking system performance to individual myosin structures. For instance, one myosin population had a lower system force even though more myosins contributed to system-level force. This relationship is elucidated with SBF by considering the distribution of structural states and behaviors in agent populations. For the lower system force population, it is found that although more myosins are producing force, a greater percentage of the population produces negative force. The success of employing SBF for understanding system interactions demonstrates how the methodology may aid designers in complex systems embodiment. The methodology's domain-independence promotes its extendibility to similar complex systems, and in the myosin test case the approach enabled the reduction of a complex physical phenomenon to a design space consisting of only a few critical parameters. The methodology is particularly suited for complex systems with many parts operating stochastically across scales, and should prove invaluable for engineers facing the challenges of biological nanoscale design, where designs with unique properties require novel approaches or useful configurations in nature await discovery.

The role of mechanics in biological and bio-inspired systems

“…Both the lever and head domains may be tuned synthetically through altering amino-acid sequences or building chimeras from combinations of myosins 74,78 . There is great potential in using these myosin engineering and manufacturing techniques in formalizing design approaches 13,79 to construct biomimetic devices, such as smart contractile materials, molecular sensors and nano-actuators with optimized responses.…”

“…In muscle-based systems 60,72 , actuation is achievable through biological, synthetic or combinations of both manufacturing approaches-the route chosen plays a pivotal role in the capabilities and trade-offs engineers may vary to meet performance requirements (Box 2). Tissue engineering approaches for synthetic biological muscle could enable design and manufacturing of tissues from the bottom-up 73 , and may eventually offer many options in calibrating a muscle response through altering their myosin motor protein content with synthetic myosins tailored for a specific functionality 13,74 . There is a strong correlation between muscle contraction speed and energy consumption to its myosin isoform composition 12,75 , which makes these molecules a key consideration in designing muscle tissues.…”

“…Muscle formation begins with a process of myosin molecules forming bipolar filaments. Myosin isoforms have varied molecular structures that influence their force generation, as well as energy usage rates that inform contractile functionality 12,13 . The aggregation of these bipolar filaments into sarcomeres forms the basis of muscles, and the system loops back as environmental feedback from muscle activation influences which myosins are recruited.…”

Human and Computational Approaches for Design Problem-Solving

“…Participants used a design GUI (Fig. 11.2) to manipulate 3 design inputs for configuring a single motor protein and 1 design input to determine how many proteins are in a system (Egan et al 2013). Participants were allowed ten design evaluations and four minutes for each task.…”

“…For our design problem, a complex muscle biosystem was considered across scales, with a particular emphasis placed on the mechanical design of nanoscale motor proteins (Howard 2001;Egan et al 2013). Due to the complexity of the design problem, human-in-the-loop approaches (Simpson and Martins 2011) were identified as a potential design strategy that motivates the need for human participant experiments for empirical testing and validation (Egan et al 2015b).…”