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Multi-scale models for cell adhesion and cell signaling
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Metabolomics:Open Access

ISSN: 2153-0769

Open Access

Multi-scale models for cell adhesion and cell signaling


3rd International Conference and Exhibition on Metabolomics & Systems Biology

March 24-26, 2014 Hilton San Antonio Airport, San Antonio, USA

Yinghao Wu

Accepted Abstracts: Metabolomics

Abstract :

The interactions of membrane receptors during cell adhesion play pivotal roles in tissue morphogenesis during development. Our lab focuses on developing multi-scale models to decompose the mechanical and chemical complexity in cell adhesion. Recent experimental evidences show that clustering is a generic process for cell adhesive receptors. However, the physical basis of such receptor clustering is not understood. We introduced the effect of molecular flexibility to evaluate the dynamics of receptors. By delivering new theory to quantify the changes of binding free energy in different cellular environments, we revealed that restriction of molecular flexibility upon binding of membrane receptors from apposing cell surfaces ( trans ) causes large entropy loss, which dramatically increases their lateral interactions ( cis ). This provides a new molecular mechanism to initialize receptor clustering on the cell-cell interface. By using the subcellular simulations, we further found that clustering is a cooperative process requiring both trans and cis interactions. The detailed binding constants during these processes are calculated and compared with experimental data from our collaborator?s lab.

Biography :

Yinghao Wu has completed his Ph.D. of Applied Physics from Rice University and postdoctoral research in Biochemistry and Molecular Biophysics from Columbia University School of Medicine. He is currently an Assistance Professor in the Department of Systems and Computational Biology at Albert Einstein College of Medicine. He has published more than 17 papers in reputed journals such as Nature, PNAS, etc.

Google Scholar citation report
Citations: 895

Metabolomics:Open Access received 895 citations as per Google Scholar report

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