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HIGHLIGHTS


Applied chemistry


NIGEL P FREESTONE University of Northampton, UK


Solar-to-fuel system recycles CO2 to make ethanol and ethylene


Scientists have harnessed the power of photosynthesis to convert carbon dioxide into fuels and alcohols at efficiencies far greater than plants (G. J. Bullock, D. F. Srankó, C. M. Towle, Y. Lum, M. Hettick, M. C. Scott, A. Javeyd, J. Ager; Energy Environ. Sci., 2017, 10, 2222) (Scheme 1). The achievement marks a significant milestone in the effort to move toward sustainable sources of fuel. Electrochemical reduction of CO2 into chemical products, in particular hydrocarbons and oxygenates, which are formed by multi-electron transfer reactions selectively and efficiently, can be facilitated by nanostructured Cu–Ag bimetallic cathodes. When operated in an electrolysis


cell, the cathode provides a constant energetic efficiency for hydrocarbon and oxygenate production. As a result, when coupled to Si photovoltaic cells, solar conversion efficiencies of 3–4% to the target products can be achieved for 0.35 to 1 Sun illumination. Use of a four-


terminal III–V/Si tandem solar cell configuration yields a conversion efficiency to hydrocarbons and oxygenates exceeding 5% at 1 Sun illumination.


Metal-free photocatalyst for H2 evolution Scheme 1


in visible to near-infrared region In the drive toward green and sustainable chemistry, exploring efficient and stable metal-free photocatalysts with broadband solar absorption from the UV to near-infrared region for the photoreduction of water to H2 remains a big challenge. To this end, a binary nanohybrid (BP/CN) of two- dimensional (2D) black phosphorus (BP) and graphitic carbon nitride (CN) has been designed and used as a metal-free photocatalyst for the first time (M. Zhu, S. Kim, L. Mao, M. Fujitsuka, .J Zhang, X. Wang, T. Majima; J. Amer. Chem. Soc., 2017, 139, 13234) (Scheme 2). During irradiation of BP/CN in


water with >420 and >780nm light, solid H2


Scheme 2 gas is generated, respectively.


Owing to the interfacial interaction between BP and CN, efficient charge transfer occurred, thereby enhancing the photocatalytic performance.


Biomedical


KEVIN BURGESS Texas A&M University, US


Macrocycles that bind PD-L1 Previous Highlights have discussed work by Holak et al, which established an unexpected route by which molecules patented for disruption of the immunotherapy checkpoint target PD-1•PD-L1 achieved this. Another contribution from Holek’s group has established three patented macrocyclic peptides comprising around 14 amino acids bind at the PD-1•PD-L1 interface region and disrupt the protein- protein interaction with IC50 values of 7, 9, and 153nM (Angew. Chem., Int. Ed., 2017, 56, 13732). HMQC and differential scanning


fluorimetry showed these compounds bind PD-L1 only. They used a cellular assay involving T-cell-like Jurkat cells overexpressing PD-1 and also carrying a luciferase gene controlled by a promoter that is only turned on when the T-cell is activated by another cell bearing the T-cell receptor. The complementary cells bearing


the T-cell receptor also express PD-1, and this silences the activation via the PD-1•PD-L1 interaction. Small molecules that disrupt PD-1•PD-L1 cause the T-like-cells to be activated and express luciferase. All three molecules tested positive in this assay with EC50


566nM. Finally, two of the three


macrocycles were crystallised with values of 6.30, 293 and


PD-L1 at the region that corresponds to the interface, but in different ways to PD-1.


Modeling compounds to disrupt Tight PPIs Meroueh and co-workers point out the difficulties of finding small molecule inhibitors for high affinity protein-protein interactions (PPIs) involving, then propose a virtual screening approach to test this (ChemMedChem, doi: cmdc.201700572). Throughout, their method features


the uPA•uPAR PPI for which the PI has established assays, including fluorescence polarisation and microscale thermophoresis to check if the small molecule binds uPAR, and ELISA to establish whether or not it disrupts the PPI. Their method involves: (i) using data from experimental or virtual


46 10 | 2017


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