AI Article Synopsis
- The critical micelle concentration (CMC) helps scientists understand how certain molecules called surfactants organize themselves.
- This study uses both computer simulations and real experiments to find out the CMC of protein surfactants.
- The results show that the computer predictions are very similar to the actual experimental results, meaning this method could be very helpful for studying how complex molecules fit together.
Article Abstract
The critical micelle concentration (CMC) is a crucial parameter in understanding the self-assembly behavior of surfactants. In this study, we combine simulation and experiment to demonstrate the predictive capability of molecularly informed field theories in estimating the CMC of biologically based protein surfactants. Our simulation approach combines the relative entropy coarse-graining of small-scale atomistic simulations with large-scale field-theoretic simulations, allowing us to efficiently compute the free energy of micelle formation necessary for the CMC calculation while preserving chemistry-specific information about the underlying surfactant building blocks. We apply this methodology to a unique intrinsically disordered protein platform capable of a wide variety of tailored sequences that enable tunable micelle self-assembly. The computational predictions of the CMC closely match experimental measurements, demonstrating the potential of molecularly informed field theories as a valuable tool to investigate self-assembly in bio-based macromolecules systematically.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10754628 | PMC |
| http://dx.doi.org/10.1063/5.0178910 | DOI Listing |
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