Nickel-Catalyzed Regioselectivity-Switchable Hydroheteroarylation of Vinylarenes with Electron-Rich Heteroarenes.

We report the first example of a regioselectivity switch in the hydroheteroarylation of vinylarenes with electron-rich heteroarenes, including benzofurans, benzothiophenes, and indoles, using an expedient ligand-controlled strategy. In the presence of NaOBu, Ni(IMes)[P(OEt)]Br yields C2-alkylated heteroarenes with high branched selectivity, whereas the use of Ni(IPr)[P(OEt)]Br favors the formation of the corresponding linear products. This robust method also provides easy access to a range of C2-alkylated electron-rich heteroarenes without employing directing groups.

Ligand-Controlled Nickel-Catalyzed Tandem Isomerization/Regiodivergent Hydroheteroarylation of α-Alkenes with Heteroarenes.

We herein describe an accessible ligand-controlled nickel-catalyzed tandem isomerization/regiodivergent hydroheteroarylation of α-alkenes with a series of heteroarenes, wherein the NHC ligand of heteroleptic Ni(II) complexes of the type Ni(NHC)[P(OEt)]Br displayed significant effects on regulation. In the presence of NaOBu, Ni(IMes)[P(OEt)]Br enables C═C bond isomerization of α-alkenes over up to four sp carbon atoms to afford branched products, while Ni(IPr*)[P(OEt)]Br greatly deactivates α-alkene isomerization and favors the formation of linear products.

Engineering and screening of novel β-1,3-xylanases with desired hydrolysate type by optimized ancestor sequence reconstruction and data mining.

Engineering of hydrolases to shift their hydrolysate types has not been attempted so far, though computer-assisted enzyme design has been successful. A novel integrative strategy for engineering and screening the β-1,3-xylanase with desired hydrolysate types was proposed, with the purpose to solve problems that the separation and preparation of β-1,3--oligosaccharides was in high cost yet in low yield as monosaccharides existed in the hydrolysates. By classifying the hydrolysate types and coding them into numerical values, two robust mathematical models with five selected attributes from molecular docking were established based on LogitBoost and partial least squares regression with overall accuracy of 83.