Dataset Information

Avoiding hot-spots in Microwave-assisted Pd/C catalysed reactions by using the biomass derived solvent ?-Valerolactone.

ABSTRACT: Herein, we report the use of ?-valerolactone as a new biomass-derived reaction medium for microwave assisted organic synthesis. The interaction of this solvent with microwaves and its heating profile under microwave irradiation has been fully characterized for the first time, demonstrating its stability and the applicability in microwave assisted Pd/C catalysed reactions avoiding the arcing phenomena frequently observed in these conditions. The use of ?-valerolactone demonstrated to be compatible with aliphatic and aromatic amines in the hydrogen transfer Pd/C mediated synthesis of benzimidazoles.

SUBMITTER: Petricci E

PROVIDER: S-EPMC6043498 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Avoiding hot-spots in Microwave-assisted Pd/C catalysed reactions by using the biomass derived solvent γ-Valerolactone.

Petricci Elena E Risi Caterina C Ferlin Francesco F Lanari Daniela D Vaccaro Luigi L

Scientific reports 20180712 1

Herein, we report the use of γ-valerolactone as a new biomass-derived reaction medium for microwave assisted organic synthesis. The interaction of this solvent with microwaves and its heating profile under microwave irradiation has been fully characterized for the first time, demonstrating its stability and the applicability in microwave assisted Pd/C catalysed reactions avoiding the arcing phenomena frequently observed in these conditions. The use of γ-valerolactone demonstrated to be compatibl ...[more]

PMID: 30002506

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Project description:BACKGROUND: It is well known that most of the binding free energy of protein interaction is contributed by a few key hot spot residues. These residues are crucial for understanding the function of proteins and studying their interactions. Experimental hot spots detection methods such as alanine scanning mutagenesis are not applicable on a large scale since they are time consuming and expensive. Therefore, reliable and efficient computational methods for identifying hot spots are greatly desired and urgently required. RESULTS: In this work, we introduce an efficient approach that uses support vector machine (SVM) to predict hot spot residues in protein interfaces. We systematically investigate a wide variety of 62 features from a combination of protein sequence and structure information. Then, to remove redundant and irrelevant features and improve the prediction performance, feature selection is employed using the F-score method. Based on the selected features, nine individual-feature based predictors are developed to identify hot spots using SVMs. Furthermore, a new ensemble classifier, namely APIS (A combined model based on Protrusion Index and Solvent accessibility), is developed to further improve the prediction accuracy. The results on two benchmark datasets, ASEdb and BID, show that this proposed method yields significantly better prediction accuracy than those previously published in the literature. In addition, we also demonstrate the predictive power of our proposed method by modelling two protein complexes: the calmodulin/myosin light chain kinase complex and the heat shock locus gene products U and V complex, which indicate that our method can identify more hot spots in these two complexes compared with other state-of-the-art methods. CONCLUSION: We have developed an accurate prediction model for hot spot residues, given the structure of a protein complex. A major contribution of this study is to propose several new features based on the protrusion index of amino acid residues, which has been shown to significantly improve the prediction performance of hot spots. Moreover, we identify a compact and useful feature subset that has an important implication for identifying hot spot residues. Our results indicate that these features are more effective than the conventional evolutionary conservation, pairwise residue potentials and other traditional features considered previously, and that the combination of our and traditional features may support the creation of a discriminative feature set for efficient prediction of hot spot residues. The data and source code are available on web site http://home.ustc.edu.cn/~jfxia/hotspot.html.

Dataset Information

Avoiding hot-spots in Microwave-assisted Pd/C catalysed reactions by using the biomass derived solvent ?-Valerolactone.

Publications

Avoiding hot-spots in Microwave-assisted Pd/C catalysed reactions by using the biomass derived solvent γ-Valerolactone.

Similar Datasets

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