Mapping protein-protein interactions between MutL and MutH by cross-linking
ABSTRACT Strand discrimination in Escherichia coli DNA mismatch repair requires the activation of the endonuclease MutH by MutL. There is evidence that MutH binds to the N-terminal domain of MutL in an ATP-dependent manner; however, the interaction sites and the molecular mechanism of MutH activation have not yet been determined. We used a combination of site-directed mutagenesis and site-specific cross-linking to identify protein interaction sites between the proteins MutH and MutL. Unique cysteine residues were introduced in cysteine-free variants of MutH and MutL. The introduced cysteines were modified with the cross-linking reagent 4-maleimidobenzophenone. Photoactivation resulted in cross-links verified by mass spectrometry of some of the single cysteine variants to their respective Cys-free partner proteins. Moreover, we mapped the site of interaction by cross-linking different combinations of single cysteine MutH and MutL variants with thiol-specific homobifunctional cross-linkers of varying length. These results were used to model the MutH.MutL complex and to explain the ATP dependence of this interaction.
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ABSTRACT: Recently, Paul Modrich's group reported the discovery of an intrinsic endonuclease activity for human MutLalpha. This breakthrough provides a satisfactory answer to the longstanding puzzle of a missing nuclease activity in human mismatch repair and will undoubtedly lead to new investigations of DNA repair and replication. Here, the implications of this exciting new finding are discussed in the context of mismatch repair in Escherichia coli and humans.DNA Repair 02/2007; 6(1):135-9. DOI:10.1016/j.dnarep.2006.10.021 · 3.36 Impact Factor
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ABSTRACT: Closely related to studying the function of a protein is the analysis of its three-dimensional structure and the identification of interaction sites with its binding partners. An alternative approach to the high-resolution methods for three-dimensional protein structure analysis, such as X-ray crystallography and NMR spectroscopy, consists of covalently connecting two functional groups of the protein(s) under investigation. The location of the created cross-links imposes a distance constraint on the location of the respective side chains and allows one to draw conclusions on the three-dimensional structure of the protein or a protein complex. Recently, chemical cross-linking of proteins has been combined with a mass spectrometric analysis of the created cross-linked products. This review article describes the most popular cross-linking reagents for protein structure analysis and gives an overview of the different available strategies that employ chemical cross-linking and different mass spectrometric techniques. The challenges for mass spectrometry caused by the enormous complexity of the cross-linking reaction mixtures are emphasized. The various approaches described in the literature to facilitate the mass spectrometric detection of cross-linked products as well as computer software for data analyses are reviewed.Mass Spectrometry Reviews 07/2006; 25(4):663-82. DOI:10.1002/mas.20082 · 8.05 Impact Factor
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ABSTRACT: The goal of this work is the development of a suitable monitoring module, which is to be the first module of an integrated fault detection and control system for the SHARON process. To model the process properly, different PCA models are tested. As a first step, PCA is used in an iterative manner to exclude data not considered to represent normal operational conditions and process behaviour from the original data set. To improve the performance of the identified model, it is decided to account for dynamics in the SHARON process by means of auto-regressive exogenous (ARX) structuring of data before the identification. A fruitful replacement of missing values for this purpose is done by means of a static PCA model. It is shown that the different criteria used in model selection lead to the same DPCA model. In this paper all steps of the monitoring module design are explained and the performance of different models is analyzed.Computer Aided Chemical Engineering DOI:10.1016/S1570-7946(05)80058-6