Krishna, J. | bioRxiv Science

bioRxiv2024

Polymeric Lysosomal-Targeting Chimeras: Extracellular Targeted Protein Degradation Without Co-opting Lysosome-Targeting Receptors

Extracellular targeted protein degradation (eTPD) is an emerging modality to regulate protein levels without genomic interruption. Current strategies co-opt lysosome-targeting receptors (LTRs) that are ubiquitously present in most cells, offering a high success rate of eTPD across cell types and tissues. Opening up the binding complementarity requirement from LTRs to any overexpressed cell surface receptor offers to endow eTPD platforms with new cellular targeting capabilities. Here, we report polymeric lysosome-targeting chimeras (PolyTACs), a polymer-antibody conjugate based platform for the targeted degradation of membrane-bound and soluble proteins without the need for involving LTRs. Mechanistic investigations suggest a non-classical uptake pathway that is attributed to the membrane tension caused by the multivalent interaction between the PolyTACs and the overexpressed functionalities on the cell surface. The utility of PolyTACs in eTPD has been demonstrated with three therapeutically relevant membrane proteins. Additionally, the same design principle has also been leveraged to bind and drag soluble extracellular proteins into the lysosome. The design and fabrication simplicity, non-reliance on LTRs, and tissue-targeting capabilities open up new avenues for eTPD in many disease-specific applications.

cancer biology↗

bioRxiv2022

Clustering conformational ensembles of intrinsically disordered proteins with t-distributed stochastic neighbor embedding

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, A{beta}42, and a C-terminal fragment of -synuclein, in their APO states and when bound to small molecule ligands. Our results shed light on ordered sub-states 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 and 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. SignificanceGrouping heterogeneous conformations of IDPs into "structurally similar" clusters facilitates a clearer understanding of the properties of IDP conformational ensembles and provides insights into "structural ensemble: function" relationships. In this work, we provide a unique approach for clustering IDP ensembles efficiently using a non-linear dimensionality reduction method, t-distributed stochastic neighbor embedding (t-SNE), to create clusters with structurally similar IDP conformations. We show how this can be used for meaningful biophysical analyses such as understanding the binding mechanisms of IDPs such as -synuclein and Amyloid {beta}42 with small drug molecules. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=136 SRC="FIGDIR/small/516231v2_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@8ef906org.highwire.dtl.DTLVardef@7f14e5org.highwire.dtl.DTLVardef@134f9eeorg.highwire.dtl.DTLVardef@104a2ef_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗