Cluster separation for different AF-quality metrics.

<p>Average silhouette score of the agglomerative clustering of the SANS intensity profiles of all conformations with pLDDT (top left), ipTM (top right), or pTM (bottom) scores above different cutoffs for the initial run of the pipeline, as a function of the number of such conformations. The da...

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Bibliographic Details
Main Author:	Samuel Eriksson Lidbrink (21616146) (author)
Other Authors:	Rebecca J. Howard (14670459) (author), Nandan Haloi (14670453) (author), Erik Lindahl (10338) (author)
Published:	2025
Subjects:	Biophysics Biochemistry Computational Biology Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified Physical Sciences not elsewhere classified markov state models machine learning algorithms also accurately sample sample multiple conformations open upon activation landscape requires understanding transition pathway resolved identify apparent closed angle neutron scattering protein &# 8217 alphafold </ p target environmental conditions activating conditions respectively weighted conformational ensemble combine af sampling angle scattering curves angle scattering target conditions activating conditions conformational landscape conformational ensemble stable conformations extensive sampling particular conditions transition pathways transition occurs predicted closed closed channels open states xlink "> without using structural information several strategies rigid proteins projects onto predicted basins membrane protein magnitude faster efficient way complete characterization
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Cluster separation for different AF-quality metrics.

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