Single-Molecule Dynamics Reveals Cooperative Binding-Folding in Protein Recognition
The study of associations between two biomolecules is the key to understand molecular recognition and function. Molecular function is often thought to be determined by the underlying structures. Here, combining single molecule study of protein binding with an energy landscape inspired microscopic model, we found strong evidences that bio-molecular recognition is determined by flexibilities in addition to structures. Our model is based on coarse grained molecular dynamics performed on the residue level with the energy function biased towards the native binding structure (Go model). With our model, the underlying free energy landscape of the binding can be explored. Two distinct conformational states as free energy minimum, one with partially folding of CBD and significant binding of CBD to CDC42, and another with native folding of CBD and native binding of CBD to CDC42, are clearly seen. This shows the binding process proceeds with significant interface binding of CBD with CDC42 first without complete folding of CBD. Finally binding and folding are coupled with each other cooperatively to reach the native binding state. The single molecule experimental finding of the dynamic fluctuations between the loosely bound and closely bound conformational states can be identified with theoretically calculated free energy minimum and quantitatively explained in our model as a result of binding associated with large conformational changes. Theoretical predictions have identified certain key residues for binding which are consistent with mutational experiments. The combined study provides a test ground for fundamental mechanisms as well as insights into design and further explorations on biomolecular recognition with large conformational changes.
- Research Organization:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Environmental Molecular Sciences Lab. (EMSL)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-76RL01830
- OSTI ID:
- 890107
- Report Number(s):
- PNNL-SA-48874; 6506; TRN: US200620%%217
- Journal Information:
- PLoS Computational Biology, 2(7):842-852, Journal Name: PLoS Computational Biology, 2(7):842-852
- Country of Publication:
- United States
- Language:
- English
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