In this study we investigate receptor–ligand binding in the context of antibody–antigen binding. We established a quantitative mapping between macroscopic binding rates of a deterministic differential equation model and their microscopic equivalents as obtained from simulating the spatiotemporal binding kinetics by a stochastic agent-based model. Furthermore, various properties of B cell-derived receptors like their dimensionality of motion, morphology, and binding valency are considered and their impact on receptor–ligand binding kinetics is investigated. The different morphologies of B cell-derived receptors include simple sperical representations as well as more realistic Y-shaped morphologies. These receptors move in different dimensionalities, i.e. either as membrane-anchored receptors or as soluble antibodies. The mapping of the macroscopic and microscopic binding rates allowed us to quantitatively compare different agent-based model variants for the different types of B cell-derived receptors. Our results indicate that the dimensionality of motion governs the binding kinetics and that this predominant impact is quantitatively compensated by the bivalency of these receptors.
Model for antigen binding by B cell-derived receptors
Publications
Rapid detection of microbial antibiotic susceptibility via deep learning supported analysis of angle-resolved scattered-light images of picoliter droplet cultivations
Sarkar A*, Graf M*, Svensson CM, Munser A-S, Schröder S, Hengoju S, Rosenbaum M, Figge MT
The progressive increase in microbial resistance to antibiotics is a global health threat that requires solutions for rapid and reliable determination of antibiotic susceptibility in order to select appropriate antibiotics and dosages prior to treatment. We have established a screening platform that enables the detection of cell growth after just a few cell divisions. Our […]
Competitive inhibition and mutualistic growth in Co infections: deciphering Staphylococcus aureus – Acinetobacter baumannii interaction dynamics
Timme S*, Wendler S*, Klassert TE, Saraiva JP, Nunes da Rocha U, Wittchen M, Schramm S, Ehricht R, Monecke S, Edel B, Rödel J, Löffler B, Soledad Ramirez M, Slevogt H, Figge MT*#, Tuchscherr L*#
Staphylococcus aureus (Sa) and Acinetobacter baumannii (Ab) are frequently co-isolated from polymicrobial infections that are severe and refractory to therapy. Here, we apply a combination of wet-lab experiments and in silico modeling to unveil the intricate nature of the Ab/Sa interaction using both, representative laboratory strains and strains co-isolated from clinical samples.This comprehensive methodology allowed […]
Impact of functional electrical stimulation on nerve-damaged muscles by quantifying fat infiltration using deep learning
Walluks, K.*, Praetorius*, JP., Arnold, D. #, Figge, M. T.# *contributed equally and #contributed equally
Quantitative imaging in life sciences has evolved into a powerful approach combining advanced microscopy acquisition and automated analysis of image data. The focus of the present study is on the imaging-based evaluation of the posterior cricoarytenoid muscle (PCA) influenced by long-term functional electrical stimulation (FES), which may assist the inspiration of patients with bilateral vocal […]