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

Appadurai, R and Koneru, JK and Bonomi, M and Robustelli, P and Srivastava, A (2023) Clustering Heterogeneous Conformational Ensembles of Intrinsically Disordered Proteins with t-Distributed Stochastic Neighbor Embedding. In: Journal of Chemical Theory and Computation .

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Abstract

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 t-distributed 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 α-synuclein, 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 shifts upon ligand binding. Our approach provides a new framework for detailed investigations of the thermodynamics and kinetics of IDP ligand binding and will aid rational drug design for IDPs.

Item Type:	Journal Article
Publication:	Journal of Chemical Theory and Computation
Publisher:	American Chemical Society
Additional Information:	The copyright for this article belongs to the American Chemical Society.
Department/Centre:	Division of Biological Sciences > Molecular Biophysics Unit
Date Deposited:	25 Jul 2023 05:02
Last Modified:	25 Jul 2023 05:02
URI:	https://eprints.iisc.ac.in/id/eprint/82605

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