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Clustering Heterogeneous Conformational Ensembles of Intrinsically Disordered Proteins with t-Distributed Stochastic Neighbor Embedding by Rajeswari Appadurai; Jaya Krishna Koneru; Massimiliano Bonomi; Paul Robustelli; Anand Srivastava is a Physics and Astronomy article available to read on EtoBox.

What is Clustering Heterogeneous Conformational Ensembles of Intrinsically Disordered Proteins with t-Distributed Stochastic Neighbor Embedding about?

Intrinsically disordered proteins (IDPs) populate a range of conformations that are best described by a heterogeneous ensemble. Grouping an IDP ensemble into "structurally similar" clusters for visualization, interpretation, and analysis purposes is a much-desired but formidable task, as the conformational space of IDPs is inherently high-dimensional and reduction techniques often result in ambiguous classifications. Here, we employ the tdistributed stochastic neighbor embedding (t-SNE) technique to generate homogeneous clusters of IDP conformations from the full heterogeneous ensemble. We illustrate the utility of t-SNE by clustering conformations of two disordered proteins, Aβ42, and αsynuclein, in their APO states and when bound to small molecule ligands. Our results shed light on ordered substates within disordered ensembles and provide structural and mechanistic insights into binding modes that confer specificity and affinity in IDP ligand binding. t-SNE projections preserve the local neighborhood information, provide interpretable visualizations of the conformational heterogeneity within each ensemble, and enable the quantification of cluster populations and their relative sh

Who reads Clustering Heterogeneous Conformational Ensembles of Intrinsically Disordered Proteins with t-Distributed Stochastic Neighbor Embedding?

It is typically read by researchers, students, and practitioners in Physics and Astronomy.

Author
Rajeswari Appadurai; Jaya Krishna Koneru; Massimiliano Bonomi; Paul Robustelli; Anand Srivastava
Publisher
American Chemical Society (ACS)
Published
2023
Language
EN
Field
Physics and Astronomy (Physical Sciences)