Mass spectrometry approaches to monitor protein–drug interactions

Zinn, Nico; Hopf, Carsten; Drewes, Gerard; Bantscheff, Marcus

doi:10.1016/j.ymeth.2012.05.008

Cited by 24 publications

(23 citation statements)

References 141 publications

(162 reference statements)

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“…Establishing SILAC-qGAP-Quantitative affinity purification combined with mass spectrometry can be used to study cellular dynamics of PPIs (8,9,(11)(12)(13). The principle is to compare the abundance of proteins copurifying with the bait to an internal control.…”

Section: Resultsmentioning

confidence: 99%

Quantitative GTPase Affinity Purification Identifies Rho Family Protein Interaction Partners

Paul

Zauber

Berg³

et al. 2017

Molecular & Cellular Proteomics

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Although Rho GTPases are essential molecular switches involved in many cellular processes, an unbiased experimental comparison of their interaction partners was not yet performed. Here, we develop quantitative GTPase affinity purification (qGAP) to systematically identify interaction partners of six Rho GTPases (Cdc42, Rac1, RhoA, RhoB, RhoC, and RhoD), depending on their nucleotide loading state. The method works with cell line or tissuederived protein lysates in combination with SILAC-based or label-free quantification, respectively. We demonstrate that qGAP identifies known and novel binding partners that can be validated in an independent assay. Our interaction network for six Rho GTPases contains many novel binding partners, reveals highly promiscuous interaction of several effectors, and mirrors evolutionary relationships among Rho GTPases. The Ras superfamily of small guanosine triphosphatases (Ras GTPases) consists of more than 150 members in mammals and conserved orthologs in all eukaryotes (1). As molecular switches, they cycle between an active GTP-and an inactive GDP-bound state. GTPase-activating proteins (GAPs) 1 stimulate the slow intrinsic GTPase activity, which inactivates the GTPase. Conversely, guanine nucleotide exchange factors (GEFs) promote release of GDP, which is replaced by GTP, thereby transforming the GTPase into the active state. The GTP-bound form binds to downstream effector proteins to initiate their specific cellular function. In this manner, GTPases control numerous biological processes, including cytoskeletal rearrangements, membrane dynamics, and gene expression. Rho GTPases form a subfamily of the Ras superfamily (2). Of its 22 mammalian members, RhoA, Rac1, and Cdc42 have been studied most intensively and are best known for their role in regulating the actin cytoskeleton (3).Identifying effector proteins is key to understanding Rho GTPase function. More than 70 effector proteins have already been identified for each of the three prototypical family members, RhoA, Rac1, and Cdc42 (4). However, new effector proteins are still being discovered, and little is known about effectors of less well studied family members. Systematic screens for GTPase effectors employed the yeast two-hybrid approach (5) or immobilized GTPases for affinity purification (6, 7). However, these approaches are semiquantitative at best, which makes it difficult to distinguish loading-statespecific binders from constitutive interactors and nonspecific contaminants. Due to these challenges, an unbiased interactor screen for multiple Rho GTPases has not yet been reported.We sought to systematically identify proteins that interact with Rho GTPases in a loading-state-specific manner. Quantitative affinity purification combined with mass spectrometry is a powerful technology that can be used to identify proteinprotein interactions (PPIs) in an unbiased way (8 -11). Here, we develop quantitative GTPase affinity purification (qGAP) as a novel variant of quantitative affinity purification combined with mass spectro...

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Section: Resultsmentioning

confidence: 99%

Quantitative GTPase Affinity Purification Identifies Rho Family Protein Interaction Partners

Paul

Zauber

Berg³

et al. 2017

Molecular & Cellular Proteomics

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“…values of h xy for HMBA + AA system in D-mannitol solutions are all positive due to the dominance of the partial desolvation and hydrophobic interactions over H-bonding interactions. (2) The values of h xy for HMBA + AA system follow the order h xy (glycine) < h xy (L-serine) < h xy (L-alanine) because of the structural difference of the three amino acids. (3) With the increasing D-mannitol molar fraction, the h xy values of HMBA with the three amino acids all pass through a maximum at about 0.0018 molar fraction of D-mannitol, which is caused by the compensation of the endothermic dehydration effect and the exothermic H-bonding effect.…”

Section: Resultsmentioning

confidence: 99%

Enthalpic Interactions of HMBA with Glycine, l-Alanine, and l-Serine in Aqueous d-Mannitol Solutions at 298.15 K

Wang

Dong²,

Niu

et al. 2015

J. Chem. Eng. Data

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The mixing enthalpies of N,N′-hexamethylenebisacetamide (HMBA) with glycine, L-alanine, and L-serine in D-mannitol solutions with different molar fractions have been determined by means of mixing-flow isothermal microcalorimetry at 298.15 K. The heterotactic enthalpic interaction coefficients (h xy , h xxy , and h xyy ), in the molar fraction (x) range of D-mannitol from (0 to 0.0159), have been calculated in terms of McMillan−Mayer theory. The trends of h xy with the molar fractions of D-mannitol have been discussed based on the interactions between solute molecules under the participation of solvent molecules. The enthalpic contribution of the functional groups of solute molecules to h xy has been estimated according to the Savage−Wood additivity group (SWAG) approach. The influence of structural difference between glucose and D-mannitol on the h xy values of HMBA with glycine has been elucidated by combining the present results with our previous work.

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“…To circumvent this limitation, approaches for systematically identifying drug-target interactions are increasingly being used. These include mass spectrometry-based methods (see [31]), phage display and protein microarray approaches, as well as technologies that provide more global information, such as drug-induced changes in mRNA or protein levels, or metabolite expression profiles [18].…”

Section: Investigating Drug-protein Interactions: the Yeast Threehybrmentioning

confidence: 99%

Yeast “N”-hybrid systems for protein–protein and drug–protein interaction discovery

Rezwan¹,

Auerbach²

2012

Methods

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Mass spectrometry approaches to monitor protein–drug interactions

Cited by 24 publications

References 141 publications

Quantitative GTPase Affinity Purification Identifies Rho Family Protein Interaction Partners

Quantitative GTPase Affinity Purification Identifies Rho Family Protein Interaction Partners

Enthalpic Interactions of HMBA with Glycine, l-Alanine, and l-Serine in Aqueous d-Mannitol Solutions at 298.15 K

Yeast “N”-hybrid systems for protein–protein and drug–protein interaction discovery

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