Computational resources and strategies to construct single-molecule metabolic models of microbial cells

Abstract

Recent computational methodologies, such as individual-based modelling, pave the way to the search for explanatory insight into the collective behaviour of molecules. Many reviews offer an up-to-date perspective about such methodologies, but little is discussed about the practical information requirements involved. The biological information used as input should be easily and routinely determined in the laboratory, publicly available and, preferably, organized in programmatically accessible databases. This review is the first to provide a systematic and comprehensive overview of available resources for the modelling of metabolic events at the molecular scale. The glycolysis pathway of Escherichia coli, which is one of the most studied pathways in Microbiology, serves as case study. This curation addressed structural information about E. coli (i.e. defining the simulation environment), the reactions forming the glycolysis pathway including the enzymes and the metabolites (i.e. the molecules to be represented), the kinetics of each reaction (i.e. behavioural logic of the molecules) and diffusion parameters for all enzymes and metabolites (i.e. molecule movement in the environment). Furthermore, the interpretation of relevant biological features, such as molecular diffusion and enzyme kinetics, and the connection of experimental determination and simulation validation are detailed. Notably, the information from classical theories, such as enzymatic rates and diffusion coefficients, is translated to simulation parameters, such as collision efficiency and particle velocity.

Particle-Based Simulation Reveals Macromolecular Crowding Effects on the Michaelis-Menten Mechanism

“…Based on this in vitro elementary step model, we built an equivalent in vitro particle model that required additional information on the molecular parameters, including mass, diffusion, and collision radius, of all the species involved in a reaction, meaning the substrates, products, free enzymes, and enzyme complexes. To estimate the collision radius of the enzyme and the enzyme-substrate complex, we followed the suggestions of Gameiro et al and used the empirical relation between mass and size to estimate the inert molecule size from the enzyme mass (51,54). In the same way, we applied the Stokes-Einstein relation to calculate the diffusion constants from the collision radius.…”

“…We additionally assumed that the enzyme-substrate complex entirely enclosed the substrate with its binding pocket, thus rendering the collision radius of the complex and enzyme equal. To estimate the collision radius of g3p and g2p, we also followed the suggestions of Gameiro et al and used the method developed by Zhao et al to estimate their van der Waals volume and to calculate the equivalent sphere radius (54,55). The diffusion constants of g2p and g3p were obtained from the literature (56).…”

“…This allowed for a detailed comparison of the effects of the volume fraction and size distribution of the crowding agents on enzyme kinetics. For the size The remaining values were obtained from Gameiro et al (54). distributions, we used 1) the E. coli distribution derived from Kalwarczyk et al, 2) a population containing only particles of the median size of the E. coli distribution, 3) a population the size of the upper quartile of the E. coli size distribution, and 4) a population the size of the lower quartile ( Fig.…”

Particle-based simulation reveals macromolecular crowding effects on the Michaelis-Menten mechanism

“…Based on this in vitro elementary step model, we built an equivalent in vitro particle model that required additional information on the molecular parameters, including mass, diffusion, and collision radius, of all the species involved in a reaction, meaning the substrates, products, free enzymes, and enzyme complexes. To estimate the collision radius of the enzyme and the enzyme-substrate complex, we followed the suggestions of Gameiro et al and used the empirical relation between mass and size to estimate the inert molecule size from the enzyme mass (36,39). In the same way, we applied the Stokes-Einstein relation to calculate the diffusion constants from the collision radius.…”

“…To estimate the collision radius of g3p and g2p, we also followed the suggestions of Gameiro et al and used the method developed by Zhao et al to estimate their van der Waals volume and to calculate the equivalent sphere radius (39,40). The diffusion constants of g2p and g3p were obtained from the literature (41).…”