Dataset Information

Selective and Scalable Perfluoroarylation of Nitroalkanes.

ABSTRACT: Functionalized per- and polyfluoroarenes are important building blocks, with many industrially and medicinally important molecules containing them. Nucleophilic aromatic substitution can be employed as a quick and straightforward way to synthesize these building blocks. While many methods to derivatize fluoroarenes exist that use heteroatom centered nucleophiles, there are fewer methods that use carbon centered nucleophiles, and of those many are poorly defined. This work presents the SNAr reaction of nucleophiles generated from nitroalkanes with a variety of fluorinated arenes. Given that the products are versatile, accessing polyfluorinated arene building blocks in substantial scale is important. This method is highly regioselective, and produces good to moderate yields on a large scale, sans chromatography, and thus fulfills this need. In addition, the regioselectivity of the addition was probed using both DFT calculations and experimentally via halogen exchange.

SUBMITTER: Day JI

PROVIDER: S-EPMC5568861 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Publications

Selective and Scalable Perfluoroarylation of Nitroalkanes.

Day Jon I JI Weaver Jimmie D JD

The Journal of organic chemistry 20170609 13

Functionalized per- and polyfluoroarenes are important building blocks, with many industrially and medicinally important molecules containing them. Nucleophilic aromatic substitution can be employed as a quick and straightforward way to synthesize these building blocks. While many methods to derivatize fluoroarenes exist that use heteroatom centered nucleophiles, there are fewer methods that use carbon centered nucleophiles, and of those many are poorly defined. This work presents the SNAr react ...[more]

PMID: 28598158

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Project description:BACKGROUND:Linkage disequilibrium is defined as the non-random associations of alleles at different loci, and it occurs when genotypes at the two loci depend on each other. The model of genetic hitchhiking predicts that strong positive selection affects the patterns of linkage disequilibrium around the site of a beneficial allele, resulting in specific motifs of correlation between neutral polymorphisms that surround the fixed beneficial allele. Increased levels of linkage disequilibrium are observed on the same side of a beneficial allele, and diminish between sites on different sides of a beneficial mutation. This specific pattern of linkage disequilibrium occurs more frequently when positive selection has acted on the population rather than under various neutral models. Thus, detecting such patterns could accurately reveal targets of positive selection along a recombining chromosome or a genome. Calculating linkage disequilibria in whole genomes is computationally expensive because allele correlations need to be evaluated for millions of pairs of sites. To analyze large datasets efficiently, algorithmic implementations used in modern population genetics need to exploit multiple cores of current workstations in a scalable way. However, population genomic datasets come in various types and shapes while typically showing SNP density heterogeneity, which makes the implementation of generally scalable parallel algorithms a challenging task. FINDINGS:Here we present a series of four parallelization strategies targeting shared-memory systems for the computationally intensive problem of detecting genomic regions that have contributed to the past adaptation of the species, also referred to as regions that have undergone a selective sweep, based on linkage disequilibrium patterns. We provide a thorough performance evaluation of the proposed parallel algorithms for computing linkage disequilibrium, and outline the benefits of each approach. Furthermore, we compare the accuracy of our open-source sweep-detection software OmegaPlus, which implements all four parallelization strategies presented here, with a variety of neutrality tests. CONCLUSIONS:The computational demands of selective sweep detection algorithms depend greatly on the SNP density heterogeneity and the data representation. Choosing the right parallel algorithm for the analysis can lead to significant processing time reduction and major energy savings. However, determining which parallel algorithm will execute more efficiently on a specific processor architecture and number of available cores for a particular dataset is not straightforward.

Dataset Information

Selective and Scalable Perfluoroarylation of Nitroalkanes.

Publications

Selective and Scalable Perfluoroarylation of Nitroalkanes.

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