A Multiscale Algorithm for Spatiotemporal Modeling of Multivalent Protein-Protein Interaction
This article introduces a multiscale framework for spatiotemporal modeling of protein-protein interaction. Cellular protein molecules represent multivalent species that contain modular features, such as binding domains and phosphorylation motifs. The binding and transformations of these features occur at a small time and spatial scale. On the other hand, space and time involved in protein diffusion, colocalization, and formation of complexes could be relatively large. Here, we present an agent-based framework integrated with a multiscale Brownian Dynamics (BD) simulation algorithm. The framework employs spatial graphs to describe multivalent molecules and complexes with their site-specific details. By implementing a time-adaptive feature, the BD algorithm enables efficient computation while capturing the site-specific interactions of the diffusing species at the sub-nanometer scale. We demonstrate these capabilities by modeling two multivalent molecules, one representing a ligand and the other a receptor, in a two-dimensional plane (cell membrane). Using the model, we show that the algorithm can accelerate computation by orders of magnitudes in both concentrated and dilute regimes. We also show that the algorithm enables robust model predictions against a wide range of selection of time step sizes.
M. S. Shahinuzzaman and D. Barua, "A Multiscale Algorithm for Spatiotemporal Modeling of Multivalent Protein-Protein Interaction," Journal of Computational Biology, vol. 24, no. 12, pp. 1275-1283, Mary Ann Liebert Inc., Dec 2017.
The definitive version is available at https://doi.org/10.1089/cmb.2017.0178
Chemical and Biochemical Engineering
Keywords and Phrases
Brownian Dynamics; Multiscale Modeling; Multivalent Assembly; Receptor Aggregation; Signal Transduction
International Standard Serial Number (ISSN)
Article - Journal
© 2017 Mary Ann Liebert Inc., All rights reserved.
01 Dec 2017