Modeling of Ligand-Receptor Protein Interaction in Biodegradable Spherical Bounded Biological Micro-Environments
Author(s) -
Muneer M. Al-Zu'bi,
Ananda Sanagavarapu Mohan
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2829658
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
In this paper, we propose a generalized model for the Ligand-Receptor protein interaction in 3D spherically bounded, diffusive biological microenvironments using molecular communication paradigm. Modeling a targeted cell as a receiver nano-machine, we derive analytical expressions for the Green's function as well as for the expected number of the activated receptors. The molecular degradation in the environment due to enzymatic effects and the changes in pH levels are included via the first-order degradation reaction mechanism. A second-order reversible reaction mechanism is employed to model the reception process that involve the reaction of ligands to activate the receptor proteins lying on the receiver surface to form ligand-receptor complexes. We also present a particle-based simulator that incorporates the reversible reaction of molecules with the receptors present on the surface of a receiver that is located inside a bounded, 3-D microfluidic environment. Our simulations also include molecular degradation and boundary absorption of the ligands due to collision. The simulation results show perfect agreement with the results obtained from the analytical, bounded, and 3-D spherical model of the medium. The proposed models can be used for accurate prediction of the drug concentration profiles and number of activated receptors at any targeted cell.
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