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.


Chemical and Biochemical Engineering


This work was supported by the National Science Foundation (1609642).

Keywords and Phrases

Brownian Dynamics; Multiscale Modeling; Multivalent Assembly; Receptor Aggregation; Signal Transduction

International Standard Serial Number (ISSN)


Document Type

Article - Journal

Document Version


File Type





© 2017 Mary Ann Liebert Inc., All rights reserved.

Publication Date

01 Dec 2017

PubMed ID