A Computer Model of Cross-Linking Surface Immunoglobulin Receptors on the Surface of a B-Lymphocyte Cell

Abstract

While models exist that give information about receptor cluster size for bivalent receptor / bivalent ligand cross-linking, there is currently no detailed data about the cluster shapes. A FORTRAN computer program model which uses a modified Monte Carlo method to simulate the cross-linking of surface immunoglobulin by anti-Ig antibodies was created to provide data on the shapes of the receptor clusters that form. The program logic is summarized in the following statements. Bivalent receptor sites are randomly placed on a two- dimensional grid. A receptor site is chosen randomly for manipulation. The probabilities of the receptor site becoming unbound, bound to a ligand only, bound to a neighboring receptor, or bound to itself are calculated and calculated and normalized. Through random number selection, the state of the receptor is updated according to the weighted probabilities. The receptor site is then moved by a random angle and distance to simulate the fluid membrane on the surface of a B-cell. In fact, the variation of shape occurs in the same time frame as the oscillations of intracellular calcium which activate the B-cell. Shape, which goes a step beyond concentration, is a vital link in conforming intramembrane enzymes that control the release of intracellular calcium. (sdw)

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jul 07, 1989
Accession Number
ADA216265

Entities

People

  • Joseph F. Lepage

Organizations

  • United States Naval Academy

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • B Lymphocytes
  • Blood
  • Cells
  • Chemistry
  • Computer Programs
  • Computers
  • Differential Equations
  • Equations
  • Immune System
  • Lymphocytes
  • Monte Carlo Method
  • Polymers
  • Probability
  • Security
  • Shape
  • United States
  • United States Naval Academy

Fields of Study

  • Biology

Readers

  • Breast cancer cell signaling and growth regulation.
  • Computational Modeling and Simulation
  • Molecular and Cellular Biochemistry