Rule‐based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems

Abstract

Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and post-translational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation).

BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments

“…The KMC (stochastic simulation) method implemented in NFsim tends to be computationally expensive, because in such methods, system state is advanced one reaction event at a time (Chylek et al, 2014a). Use of NFsim was required because the extended model places no constraint on the size of (linear) EGFR oligomers, which form via polymerization-like reactions.…”

“…Biomolecular interactions can be represented by formalized rules (Chylek et al, 2014a;Stefan et al, 2014). Collections of rules form rule-based models, which provide concise representations of biomolecular interaction networks and can be analyzed to obtain insights into how system-level behavior emerges from biomolecular interactions (Chylek et al, 2014a;Stefan et al, 2014).…”

“…Collections of rules form rule-based models, which provide concise representations of biomolecular interaction networks and can be analyzed to obtain insights into how system-level behavior emerges from biomolecular interactions (Chylek et al, 2014a;Stefan et al, 2014). Rule-based models must be analyzed with specialized algorithms and software tools (Chylek et al, 2014a;Stefan et al, 2014), such as BioNetGen (Harris et al, 2015), which interprets models encoded in the BioNetGen language (BNGL) and provides deterministic, stochastic and hybrid forward simulation capabilities (Harris et al, 2015). To date, other critical methods of analysis, such as fitting (parameter estimation), have typically been applied ad hoc (e.g.…”

“…a list of reactions) or the corresponding ODEs for the mass-action kinetics of the network, a capability provided by BioNetGen, is expensive and sometimes impracticable. In such cases, direct simulation methods Applications Note must be used (Chylek et al, 2014a). These methods have been called network-free methods, because they do not involve processing a set of rules to obtain a list of reactions.…”

“…Because of the potentially high cost of network-free simulation (Chylek et al, 2014a), BioNetFit has been designed to be used on clusters. It can also be used on stand-alone computers.…”