Titlebook: Cell-Wide Identification of Metabolite-Protein Interactions; Aleksandra Skirycz,Marcin Luzarowski,Jennifer C. E Book 2023 The Editor(s) (i

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媒介

,PROMIS: Co-fractionation Mass Spectrometry for Analysis of Protein–Metabolite Interactions,—but a comprehensive overview of protein–metabolite interactions (PMIs) is missing. Recently we devised a non-targeted method for detecting PMIs using size-exclusion chromatography followed by proteomic and metabolomic analysis: PROMIS. Under test this method was able to identify known PMIs such as enzyme–cofactor complexes as well as novel ones.

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Solvent-Induced Protein Precipitation for Drug Target Discovery,nce to solvent-induced precipitation. This chapter describes the protocol for identifying drug–target protein interactions by performing unbiased SIP with total cell lysate using a mass spectrometry-based proteomic strategy.

Flatus

Databases and Tools to Investigate Protein-Metabolite Interactions, our knowledge on PMIs, with particular emphasis on platforms and databases to explore the highly heterogenous nature of characterized PMIs, which is likely to be an essential resource on the development of new computational approaches to predict and validate interactions based on large-scale PMI screenings.

大范圍流行

Book 2023erent organisms, in order to shed light on these important regulatory interactions. Experimental and computational strategies to characterize protein-metabolite interactions are discussed, and recent advances in enabling technologies are featured as well. Written for the highly successful .Methods i

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1064-3745 expertsThis thorough volume explores protocols of proteome- and metabolome-wide strategies for the identification of protein-small molecule complexes in different organisms, in order to shed light on these important regulatory interactions. Experimental and computational strategies to characterize

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https://doi.org/10.1007/978-3-319-66869-7stablishing their biological relevance. Here, we describe a protocol that allows the identification of multiple protein partners for one ligand. This protocol describes a straightforward methodology that can be adapted to a wide variety of organisms.

Flirtatious

Data Science Meets Optimizationffinity purification (AP) followed by liquid chromatography–mass spectrometry (LC–MS). Aside from its speed, simplicity, and adaptability to a variety of biological systems, its main strength lies in the parallel identification, in a near-physiological environment, of a given protein’s protein and small-molecule partners.

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