Whole-Cell Models and Simulations in Molecular Detail

Abstract

Comprehensive data about the composition and structure of cellular components have enabled the construction of quantitative whole-cell models. While kinetic network-type models have been established, it is also becoming possible to build physical, molecular-level models of cellular environments. This review outlines challenges in constructing and simulating such models and discusses near- and long-term opportunities for developing physical whole-cell models that can connect molecular structure with biological function.

Keywords: crowding; molecular dynamics simulation; network models; protein structure; systems biology.

Figure 1:

Construction of cellular systems from atomistic structures of individual molecules based on biochemical pathway reconstruction for the cytoplasm of M. genitalium (A) (Feig et al 2015). Multiscale assembly generation protocol from spherical models to fully solvated atomistic system (B) (Feig et al 2015).

Figure 2:

Flowchart of a typical simulation of a large cellular system that involves high-performance computing, data management, and analysis challenges.

Figure 3:

Effects of cellular environments on stability, dynamics, and binding. Protein stability is altered in crowded cellular environments due to volume exclusion and interactions with crowder molecules (grey) (A) (Harada et al 2013); rotational diffusion in crowded environments depends on transient cluster formation in concentrated villin solutions (B) (Nawrocki et al 2017); binding of ATP (red with crowding, blue without crowding) to acetate kinase (grey) varies in the presence of crowders (C) (Yu et al 2016).