Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Supercharging-Enhanced nDIA-MS Enables Global Profiling of Drug-Induced Proteome Solubility Shifts (solubility proteomics)

ABSTRACT: Mass spectrometry (MS)-based proteomics has become indispensable for high-throughput quantitation of protein expression. However, protein function is regulated by a variety of factors beyond abundance alone. Here, we optimized narrow-window, data-independent ac-quisition (nDIA) MS with 3% DMSO as a supercharging co-solvent, boosting signal intensity by up to 56% and enabling identification of ~9,600 proteins from 1 µg of HeLa digest with a 15 min gradient. Using this methodology, we quantified solubility and abundance changes in 8,694 pro-teins across three cell lines following short-term treatment with the proteasome inhibitor MG132 and the SUMO-activating enzyme inhibitor ML-792. MG132 affected the solubility of 1,723 pro-teins and the abundance of 374, and ML-792 impacted 1,294 and 288, respectively. The drugs elicited distinct and sometimes opposing solubility shifts; For instance, MG132 insolubilized HSF1, ML-792 solubilized SP100 and insolubilized PLOR3G, and SMAD2 showed opposite responses to those two treatments. These results reveal widespread, drug-induced remodeling of the pro-tein solubility landscape and establish solubility profiling by nDIA-MS as a robust and broadly ap-plicable platform for uncovering protein state transitions and cellular responses to perturbation.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Yun Xiong

LAB HEAD: Philip L. Lorenzi

PROVIDER: PXD064185 | Pride | 2026-01-12

REPOSITORIES: Pride

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	092724_OptimzDIA_15m_293A_CE_MGML_1.raw	Raw
	092724_OptimzDIA_15m_293A_CE_MGML_2.raw	Raw
	092724_OptimzDIA_15m_293A_CE_MGML_3.raw	Raw
	092724_OptimzDIA_15m_293A_CE_MG_1.raw	Raw
	092724_OptimzDIA_15m_293A_CE_MG_2.raw	Raw

Items per page:

1 - 5 of 75

Similar Datasets

Supercharging-Enhanced nDIA-MS Enables Global Profiling of Drug-Induced Proteome Solubility Shifts (co-solvent)

Project description:Mass spectrometry (MS)-based proteomics has become indispensable for high-throughput quantitation of protein expression. However, protein function is regulated by a vari-ety of factors beyond abundance alone. Here, we optimized narrow-window, data-independent acquisition (nDIA) MS with 3% DMSO as a supercharging co-solvent, boosting signal intensity by up to 56% and enabling identification of ~9,600 proteins from 1 µg of HeLa digest with a 15 min gradient. Using this methodology, we quantified solubility and abundance changes in 8,694 proteins across three cell lines following short-term treatment with the proteasome in-hibitor MG132 and the SUMO-activating enzyme inhibitor ML-792. MG132 affected the solubil-ity of 1,723 proteins and the abundance of 374, and ML-792 impacted 1,294 and 288, respec-tively. The drugs elicited distinct and sometimes opposing solubility shifts; For instance, MG132 insolubilized HSF1, ML-792 solubilized SP100 and insolubilized PLOR3G, and SMAD2 showed opposite responses to those two treatments. These results reveal wide-spread, drug-induced remodeling of the protein solubility landscape and establish solubility profiling by nDIA-MS as a robust and broadly applicable platform for uncovering protein state transitions and cellular responses to perturbation.

2026-01-11 | PXD064180 | Pride

Supercharging-Enhanced nDIA-MS Enables Global Profiling of Drug-Induced Proteome Solubility Shifts (TPP)

Project description:Mass spectrometry (MS)-based proteomics has become indispensable for high-throughput quantitation of protein expression. However, protein function is regulated by a variety of factors beyond abundance alone. Here, we optimized narrow-window, data-independent ac-quisition (nDIA) MS with 3% DMSO as a supercharging co-solvent, boosting signal intensity by up to 56% and enabling identification of ~9,600 proteins from 1 vg of HeLa digest with a 15 min gradient. Using this methodology, we quantified solubility and abundance changes in 8,694 pro-teins across three cell lines following short-term treatment with the proteasome inhibitor MG132 and the SUMO-activating enzyme inhibitor ML-792. MG132 affected the solubility of 1,723 pro-teins and the abundance of 374, and ML-792 impacted 1,294 and 288, respectively. The drugs elicited distinct and sometimes opposing solubility shifts; For instance, MG132 insolubilized HSF1, ML-792 solubilized SP100 and insolubilized PLOR3G, and SMAD2 showed opposite responses to those two treatments. These results reveal widespread, drug-induced remodeling of the pro-tein solubility landscape and establish solubility profiling by nDIA-MS as a robust and broadly ap-plicable platform for uncovering protein state transitions and cellular responses to perturbation.

2025-11-07 | MSV000099787 | MassIVE

Supercharging-Enhanced nDIA-MS Enables Global Profiling of Drug-Induced Proteome Solubility Shifts (Method evaluation)

Project description:Mass spectrometry (MS)-based proteomics has become indispensable for high-throughput quantitation of protein expression. However, protein function is regulated by a variety of factors beyond abundance alone. Here, we optimized narrow-window, data-independent ac-quisition (nDIA) MS with 3% DMSO as a supercharging co-solvent, boosting signal intensity by up to 56% and enabling identification of ~9,600 proteins from 1 vg of HeLa digest with a 15 min gradient. Using this methodology, we quantified solubility and abundance changes in 8,694 pro-teins across three cell lines following short-term treatment with the proteasome inhibitor MG132 and the SUMO-activating enzyme inhibitor ML-792. MG132 affected the solubility of 1,723 pro-teins and the abundance of 374, and ML-792 impacted 1,294 and 288, respectively. The drugs elicited distinct and sometimes opposing solubility shifts; For instance, MG132 insolubilized HSF1, ML-792 solubilized SP100 and insolubilized PLOR3G, and SMAD2 showed opposite responses to those two treatments. These results reveal widespread, drug-induced remodeling of the pro-tein solubility landscape and establish solubility profiling by nDIA-MS as a robust and broadly ap-plicable platform for uncovering protein state transitions and cellular responses to perturbation.

2025-11-07 | MSV000099791 | MassIVE

Supercharging-Enhanced nDIA-MS Enables Global Profiling of Drug-Induced Proteome Solubility Shifts (Method optimization)

Project description:Mass spectrometry (MS)-based proteomics has become indispensable for high-throughput quantitation of protein expression. However, protein function is regulated by a variety of factors beyond abundance alone. Here, we optimized narrow-window, data-independent ac-quisition (nDIA) MS with 3% DMSO as a supercharging co-solvent, boosting signal intensity by up to 56% and enabling identification of ~9,600 proteins from 1 vg of HeLa digest with a 15 min gradient. Using this methodology, we quantified solubility and abundance changes in 8,694 pro-teins across three cell lines following short-term treatment with the proteasome inhibitor MG132 and the SUMO-activating enzyme inhibitor ML-792. MG132 affected the solubility of 1,723 pro-teins and the abundance of 374, and ML-792 impacted 1,294 and 288, respectively. The drugs elicited distinct and sometimes opposing solubility shifts; For instance, MG132 insolubilized HSF1, ML-792 solubilized SP100 and insolubilized PLOR3G, and SMAD2 showed opposite responses to those two treatments. These results reveal widespread, drug-induced remodeling of the pro-tein solubility landscape and establish solubility profiling by nDIA-MS as a robust and broadly ap-plicable platform for uncovering protein state transitions and cellular responses to perturbation.

2025-11-07 | MSV000099789 | MassIVE

SLAM-seq ML-792

Project description:SLAM-seq ML-792

| PRJNA703953 | ENA

Probing the Roles of SUMOylation in Cancer Cell Biology Using a Selective SAE inhibitor

Project description:Small ubiquitin-like modifier (SUMO) family proteins regulate target protein functions by post-translational modification. However, a potent and selective inhibitor to target the SUMO pathway has been lacking. Here we describe ML-792, the first mechanism-based SUMO-activating enzyme (SAE) inhibitor with nanomolar potency in cellular assays. ML-792 selectively blocks SAE enzyme activity and total SUMOylation, which leads to reduced cancer cell proliferation. Moreover, induction of the MYC oncogene increased the ML-792 mediated viability effect in cancer cells, indicating potential application of SAE inhibitors in MYC-amplified tumors. Using ML-792, we further explored the critical roles of SUMOylation in mitotic progression and chromosome segregation. Furthermore, expression of an SAE catalytic subunit (UBA2) mutant S95N/M97T rescued SUMOylation loss and the mitotic defect induced by ML-792, confirming the selectivity of ML-792. As a potent and selective SAE inhibitor, ML-792 provides rapid loss of endogenously SUMOylated proteins allowing for novel insights into SUMO biology.

2017-09-01 | GSE100408 | GEO

Streamlined analysis of drug targets by proteome integral solubility alteration indicates organ-specific engagement

Project description:Proteins are the primary targets of almost all small molecule drugs. However, even the most selectively designed drugs can potentially target several unknown proteins. Identification of potential drug targets can facilitate design of new drugs and repurposing of existing ones. Current state-of-the-art proteomics methodologies enable screening of thousands of proteins against a limited number of drug molecules. Here we report the development of a label-free quantitative proteomics approach that enables proteome-wide screening of small organic molecules in a scalable, reproducible, and rapid manner by streamlining the proteome integral solubility alteration (PISA) assay. We used rat organs ex-vivo to determine organ specific targets of medical drugs and enzyme inhibitors to identify novel drug targets for common drugs such as Ibuprofen. Finally, global drug profiling revealed overarching trends of how small molecules affect the proteome through either direct or indirect protein interactions.

2024-10-16 | PXD050784 | Pride

Sun2019 - Predictive models of aqueous solubility of organic compounds.

Project description:Kinetic aqueous solubility (μg/mL) was experimentally determined using the same SOP in over 200 NCATS drug discovery projects. A final dataset of 11780 non-redundant molecules and their associated solubility was used to train a SVM classifier. Model Type: Predictive machine learning model. Model Relevance: Predicting the aqueous solubility of a chemical compound. Model Encoded by: Pauline (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos74bo

2024-04-22 | MODEL2404220003 | BioModels

Not1 and Not4 inversely determine mRNA solubility that sets the dynamics of co-translational events

Project description:The goal is to compare role of Not1,4,5 in co-translational decay and solubility of RNAs from soluble and total RNA pools using degron strains

2023-01-24 | GSE193912 | GEO

Rong2020 - Grover-Esol: Prediction of water solubility (log solubility in mols per litre) for common organic small molecules

Project description:This model has been trained using the GROVER embedding and the Molecule Net ESOL dataset. . Model Type: Molecular properties prediction ML model. Model Relevance: Predicts Log Solubility. Model Encoded by: Amna Ali (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos8451

2024-06-04 | MODEL2406040005 | BioModels

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data