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Updated: Sep 18, 2025

Comparing the Affinity of GTPase-binding Proteins using Competition Assays
Published on: October 8, 2015
Computational model predicts function of Rho-GTPase binding for plexin receptor GAP activity on Rap1b via dynamic
Nisha Bhattarai1, Lindsay Morrison2, Alexandre F Gomes2
1Department of Physiology and Biophysics, Case Western Reserve University, Cleveland, Ohio, USA.
Plexin-GTPase interactions were simulated, revealing distinct dynamics and network changes when bound to single versus multiple GTPases. These findings clarify plexin signaling mechanisms.
Area of Science:
- Molecular Biology
- Cell Signaling
- Structural Biology
Background:
- Plexin-semaphorin signaling is crucial for cell migration, neuronal development, angiogenesis, and immune responses.
- Plexins directly bind active Rho- and Ras-family GTPases via intracellular domains, including Rho-GTPase binding and GTPase-activating protein (GAP) segments.
- The structural dynamics of plexin-GTPase interactions, especially with multiple GTPases, remain incompletely understood.
Purpose of the Study:
- To investigate the conformational dynamics and network alterations in plexin-B1 when bound to single versus multiple GTPases.
- To compare the binding stability and interaction networks of plexin-B1 with Rap1b (Ras), Rnd1 (Rho), and Rac1 (Rho) under different binding conditions.
Main Methods:
- Molecular dynamics simulations were performed on six distinct plexin-B1-GTPase bound systems.
- Analysis included conformational changes, network centralities, and interaction stability.
- Computational models were validated against experimental hydrogen-deuterium exchange mass spectrometry data.
Main Results:
- Plexin-B1 dynamics were more altered with Rac1 compared to Rnd1, depending on Rap1b binding to the GAP domain.
- Rnd1 showed stronger, more stable interactions with plexin-B1 without Rap1b, whereas Rac1 exhibited fewer, less stable connections.
- Network dynamics differed significantly when plexin-B1 was bound to both Ras and Rho-GTPases versus a single GTPase.
Conclusions:
- Computational models provide insights into the molecular mechanisms of plexin-GTPase interactions.
- Understanding these dynamics is key to deciphering complex GTPase signaling pathways.
- The findings align with experimental data, enhancing our comprehension of plexin-mediated cellular processes.
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