Generative AI Framework SynGlue for the Rational Design of Clinically Relevant Protein Degraders

Description

This dataset contains processed protein-level quantitative proteomics results from a TMT-multiplex LC-MS/MS study of human 22Rv1 cells under vehicle and compound-treatment conditions at 6 h and 24 h. Files include filtered protein abundance and annotations, normalized protein abundance, and differential-expression statistics. Twenty-four Thermo RAW fractions were acquired using an Orbitrap Exploris 240 platform. The vendor RAW files and original Proteome Discoverer search output are not included in this version and are being prepared for deposition in PRIDE/ProteomeXchange. A PRIDE accession will be added in a later dataset version. These CSV tables are downstream protein-level summaries and do not contain peptide-spectrum matches or the complete database-search evidence.

Steps to reproduce

The files are processed output tables and can be opened directly in spreadsheet software or imported into R/Python. Use the filtered table for protein annotations and retained abundance values, the normalized table for sample-level normalized abundances, and the differential-expression table for comparison-level statistics. These files do not reproduce the original database search. Full search reproduction requires the 24 Thermo RAW fractions, the original Proteome Discoverer .pdResult/search workflow, and the protein FASTA database; these are planned for PRIDE/ProteomeXchange deposition.

Categories

Funders

• Department of Biotechnology

  Ministry of Science and Technology

  Delhi, New Delhi
• Indraprastha Institute of Information Technology Delhi

  Delhi, Delhi

  Grant ID: Intramural Start-up grant

Licence