Dataset Information

The Role of a Key Amino Acid Position in Species-Specific Proteinaceous dUTPase Inhibition.

ABSTRACT: Protein inhibitors of key DNA repair enzymes play an important role in deciphering physiological pathways responsible for genome integrity, and may also be exploited in biomedical research. The staphylococcal repressor StlSaPIbov1 protein was described to be an efficient inhibitor of dUTPase homologues showing a certain degree of species-specificity. In order to provide insight into the inhibition mechanism, in the present study we investigated the interaction of StlSaPIbov1 and Escherichia coli dUTPase. Although we observed a strong interaction of these proteins, unexpectedly the E. coli dUTPase was not inhibited. Seeking a structural explanation for this phenomenon, we identified a key amino acid position where specific mutations sensitized E. coli dUTPase to StlSaPIbov1 inhibition. We solved the three-dimensional (3D) crystal structure of such a mutant in complex with the substrate analogue dUPNPP and surprisingly found that the C-terminal arm of the enzyme, containing the P-loop-like motif was ordered in the structure. This segment was never localized before in any other E. coli dUTPase crystal structures. The 3D structure in agreement with solution phase experiments suggested that ordering of the flexible C-terminal segment upon substrate binding is a major factor in defining the sensitivity of E. coli dUTPase for StlSaPIbov1 inhibition.

SUBMITTER: Benedek A

PROVIDER: S-EPMC6627510 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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The Role of a Key Amino Acid Position in Species-Specific Proteinaceous dUTPase Inhibition.

Benedek András A Temesváry-Kis Fanni F Khatanbaatar Tamjidmaa T Leveles Ibolya I Surányi Éva Viola ÉV Szabó Judit Eszter JE Wunderlich Lívius L Vértessy Beáta G BG

Biomolecules 20190606 6

Protein inhibitors of key DNA repair enzymes play an important role in deciphering physiological pathways responsible for genome integrity, and may also be exploited in biomedical research. The staphylococcal repressor StlSaPIbov1 protein was described to be an efficient inhibitor of dUTPase homologues showing a certain degree of species-specificity. In order to provide insight into the inhibition mechanism, in the present study we investigated the interaction of StlSaPIbov1 and <i>Escherichia c ...[more]

PMID: 31174420

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Project description:BackgroundProtein carbonylation, an irreversible and non-enzymatic post-translational modification (PTM), is often used as a marker of oxidative stress. When reactive oxygen species (ROS) oxidized the amino acid side chains, carbonyl (CO) groups are produced especially on Lysine (K), Arginine (R), Threonine (T), and Proline (P). Nevertheless, due to the lack of information about the carbonylated substrate specificity, we were encouraged to develop a systematic method for a comprehensive investigation of protein carbonylation sites.ResultsAfter the removal of redundant data from multipe carbonylation-related articles, totally 226 carbonylated proteins in human are regarded as training dataset, which consisted of 307, 126, 128, and 129 carbonylation sites for K, R, T and P residues, respectively. To identify the useful features in predicting carbonylation sites, the linear amino acid sequence was adopted not only to build up the predictive model from training dataset, but also to compare the effectiveness of prediction with other types of features including amino acid composition (AAC), amino acid pair composition (AAPC), position-specific scoring matrix (PSSM), positional weighted matrix (PWM), solvent-accessible surface area (ASA), and physicochemical properties. The investigation of position-specific amino acid composition revealed that the positively charged amino acids (K and R) are remarkably enriched surrounding the carbonylated sites, which may play a functional role in discriminating between carbonylation and non-carbonylation sites. A variety of predictive models were built using various features and three different machine learning methods. Based on the evaluation by five-fold cross-validation, the models trained with PWM feature could provide better sensitivity in the positive training dataset, while the models trained with AAindex feature achieved higher specificity in the negative training dataset. Additionally, the model trained using hybrid features, including PWM, AAC and AAindex, obtained best MCC values of 0.432, 0.472, 0.443 and 0.467 on K, R, T and P residues, respectively.ConclusionWhen comparing to an existing prediction tool, the selected models trained with hybrid features provided a promising accuracy on an independent testing dataset. In short, this work not only characterized the carbonylated substrate preference, but also demonstrated that the proposed method could provide a feasible means for accelerating preliminary discovery of protein carbonylation.

Dataset Information

The Role of a Key Amino Acid Position in Species-Specific Proteinaceous dUTPase Inhibition.

Publications

The Role of a Key Amino Acid Position in Species-Specific Proteinaceous dUTPase Inhibition.

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