AI Article Synopsis
- Conformational variability of biological macromolecules is crucial for their functions and predicting their behavior in organism-wide studies.
- Various experimental and computational methods are used to understand this variability, leading to the creation of conformational ensembles with differing properties based on the reconstruction methods applied.
- The article proposes a geometrical framework to assess how well these predicted ensembles match with experimental data.
Article Abstract
The conformational variability of biological macromolecules can play an important role in their biological function. Therefore, understanding conformational variability is expected to be key for predicting the behavior of a particular molecule in the context of organism-wide studies. Several experimental methods have been developed and deployed for accessing this information, and computational methods are continuously updated for the profitable integration of different experimental sources. The outcome of this endeavor is conformational ensembles, which may vary significantly in properties and composition when different ensemble reconstruction methods are used, and this raises the issue of comparing the predicted ensembles against experimental data. In this article, we discuss a geometrical formulation to provide a framework for understanding the agreement of an ensemble prediction to the experimental observations.
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| http://dx.doi.org/10.1021/acs.jcim.4c00582 | DOI Listing |
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