Biology subjects

Shah, V. J.

Publications and source records attributed to Shah, V. J..

2 recordsLinked to original sources

bioRxiv2026

ProxiCapture Reveals Context-Dependent CRBN Interactore Landscape of Molecular Glue Degraders

Molecular glue degraders represent a rapidly expanding class of small molecules that reprogram E3 ubiquitin ligases to ubiquitinate and degrade disease-relevant proteins. Despite their therapeutic potential, the rational design of molecular glues remains challenging, underscoring the need for unbiased discovery strategies to identify new chemical targets. To address this challenge, we developed ProxiCapture, an affinity-based proteomics workflow that models the systemic behavior of molecular glues by combining purified CRBN-{Delta}HBD protein with native cell or tissue lysates. Systematic application of ProxiCapture across eight cancer cell lines, three maturation states of immune cells, and paired primary healthy and tumor tissues, revealed a comprehensive atlas of pomalidomide interactors, including previously uncharacterized targets. These findings reveal that degrader-dependent interactors of CRBN are context-dependent, requiring broad, physiologically and systemically anchored sampling to uncover the full "glueable" proteome. Taken together, this study establishes a scalable platform that accelerates molecular glue discovery by capturing cell- and tissue-specific recruitment profiles and predicting system-wide degrader effects.

cancer biology↗

bioRxiv2020

Combinatorial CRISPR screening reveals functional buffering in autophagy

Functional genomics studies in model organisms and human cell lines provided important insights into gene functions and their context-dependent role in genetic circuits. However, our functional understanding of many of these genes and how they combinatorically regulate key biological processes, remains limited. To enable the SpCas9-dependent mapping of gene-gene interactions in human cells, we established 3Cs multiplexing for the generation of combinatorial gRNA libraries in a distribution-unbiased manner and demonstrate its robust performance. The optimal number for combinatorial hit calling was 16 gRNA pairs and the skew of a librarys distribution was identified as a critical parameter dictating experimental scale and data quality. Our approach enabled us to investigate 247,032 gRNA-pairs targeting 12,736 gene-interactions in human autophagy. We identified novel genes essential for autophagy and provide experimental evidence that gene-associated categories of phenotypic strengths exist in autophagy. Furthermore, circuits of autophagy gene interactions reveal redundant nodes driven by paralog genes. Our combinatorial 3Cs approach is broadly suitable to investigate unexpected gene-interaction phenotypes in unperturbed and diseased cell contexts.

cell biology↗