title: Monte Carlo algorithm for simulating reversible aggregation of multisite particles.
abstract: We present an efficient and exact Monte Carlo algorithm to simulate reversible aggregation of particles with dedicated binding sites. This method introduces a data structure of dynamic bond trees to record clusters and sequences of bond formations. The algorithm achieves a constant time cost for processing cluster association and a cost between O(logM) and O(M) for processing bond dissociation in clusters with M bonds. The algorithm is statistically exact and can reproduce results obtained by the standard method. We applied the method to simulate a trivalent ligand and a bivalent receptor clustering system and obtained an average scaling of O(M(0.45)) for processing bond dissociation in acyclic aggregation, compared to a linear scaling with the cluster size in standard methods. The algorithm also demands substantially less memory than the conventional method.
authors: Chinese Academy of Sciences-Max Plank Society Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Shanghai 200031, China.
authors: Qiang
authors: Q
authors: Chang
authors: Jin
authors: J
authors: Yang
mesh_terms: D000465:Algorithms; D009010:Monte Carlo Method; D013997:Time Factors