@inproceedings{mwt-saaacsumpga-12,
author = {Kasra Manavi and Bridget S. Wilson and Lydia Tapia},
title = {Simulation and Analysis of Antibody Aggregation on Cell 
         Surfaces Using Motion Planning and Graph Analysis},
booktitle = {ACM Conference on Bioinformatics, 
             Computational Biology and Biomedicine},
year = {2012},
month = {October},
abstract = {
  IgE antibodies bound to cell-surface receptors, Fc$\epsilon$RI,
crosslink through the binding of antigens on the cell surface. This
formation of aggregates is what simulates mast cells and basophils in
order to initiate an allergic response. Experimental studies have
shown that the spatial organization of aggregated IgE-Fc$\epsilon$RI
complexes affect transmembrane signaling that initiate these
responses. About 1,500 Americans die each year from anaphylatic 
shock caused by these aggregations.
  The methods we present in this paper address modeling and analyzing 
this critical molecular data. First, we developed 3D models of a 
trivalent antigen and IgE-Fc$\epsilon$RI complex binding using relaxed 
constraints. Simplified models were generated from all-atom structures 
to reduce the complexity of the geometry and are simulated on a plane 
to capture movement of antibodies on the cell surface.  This reduces 
the computational complexity of the simulation to a rigid body 
problem, often addressed in motion planning. Motions and resulting
aggregations are extracted from Monte Carlo simulations with kinetic
rates derived from experiments. In order to analyze the resulting 
structures, we introduce techniques to map 3D molecular binding to a 
graph structure. This facilitates analysis of aggregate structures 
because simple graph metrics, such as connected components and 
subgraph isomorphism, can be used to quickly quantify and analyze 
aggregate structures.}
pdf = {https://cs.unm.edu/tapialab/Publications/19.pdf},
}