Analytical ChemistryBiophysicsPeer-reviewed journal article
A Hit Prioritization Strategy for Compound Library Screening Using LiP-MS and Molecular Dynamics Simulations Applied to KRas G12D Inhibitors
Foroughsadat Absar, Brandon NovyiD, Edith Nagy, Evgeniy V. PetrotchenkoiD, Konstantin PopoviD, Jason B. CrossiD, Roopa ThapariD, Christoph H. BorchersiD
Abstract
An important step in screening small molecule libraries for drug discovery is hit prioritization and validation to rule out false positives, which is usually performed using biochemical and biophysical assays. The development of orthogonal assays that are highly sensitive and can accelerate the hit-to-lead process is valuable. Limited proteolysis combined with mass spectrometry (LiP-MS) is a technique used to study changes in protein structure upon ligand binding. In LiP-MS, proteins are exposed to low concentrations of proteases under native conditions. The resulting proteolytic pattern is sensitive to protein structure at the cleavage site, which can change upon ligand binding. We characterized the interaction of small molecule inhibitors of the KRas G12D mutant oncoprotein by LiP-MS combined with molecular dynamics (MD). Intact mass spectrometry and top-down analysis were used to detect and identify KRas G12D cleavage products in the presence and absence of inhibitors, thereby locating the cleavage sites in the protein. Cleavage sites protected upon compound binding correlated well with the switch II binding site. The degree of cleavage depends on binding affinity and the presence of specific functional groups in the inhibitors structure. A comparison of MD simulations for the ligand-free and ligand-bound proteins revealed the atomistic mechanisms by which the cleavage sites, located in flexible and disordered regions, are stabilized upon compound binding. We suggest that LiP-MS combined with MD (LiP-MS-MD) could be valuable in small molecule screening campaigns and add to the repertoire of available methods for high-quality hit selection in early-stage drug discovery.
- assay: proteomics
- assay: structural biology
- research focus: drug response / drug discovery
- research focus: protein folding & dynamics
- research focus: cell signaling & trafficking
- approach: experimental assay
- approach: statistical model
- Citations
- 4
- FWCI
- 1.01
- Field percentile
- top 28%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Characterization of the KRas G12D-inhibitor interactions by HDX-MS and molecular dynamics simulations
Evgeniy V. Petrotchenko, Brandon Novy, … Christoph H. Borchers·Computational and Structural Biotechnology JournalPeer-reviewed·Jan 1, 2025
- LiF-MS: Mapping unstructured peptide-protein interactions using Ligand-Footprinting Mass Spectrometry
Benjamin Parker, Edward Goncz, … Eric Weiss·bioRxiv·Jul 3, 2018
- LiP-Quant, an automated chemoproteomic approach to identify drug targets in complex proteomes
Ilaria Piazza, Nigel Beaton, … Lukas Reiter·bioRxiv·Dec 1, 2019
- In-silico predictive identification of K-RasG12V inhibitors in natural compounds
Masoud Aliyar, Hassan Aryapour, Majid Mahdavi·bioRxiv·Feb 18, 2019
- Protein Domain-Based Prediction of Compound-Target Interactions and Experimental Validation on LIM Kinases
Tunca Doğan, Ece Akhan Güzelcan, … Rengül Çetin-Atalay·PLoS Computational BiologyPeer-reviewed·Nov 29, 2021
- LiF-MS+, a revised technique for mapping peptide-protein interactions
Benjamin W. Parker, Eric L. Weiss·bioRxiv·May 28, 2024