Oligodeoxynucleotides incorporating internucleotide phosphoroselenolate linkages have been prepared under solid-phase synthesis conditions using dimer phosphoramidites. These dimers were constructed following the high yielding Michaelis-Arbuzov (M-A) reaction of nucleoside H-phosphonate derivatives with 5'-deoxythymidine-5'-selenocyanate and subsequent phosphitylation. Efficient coupling of the dimer phosphoramidites to solid-supported substrates was observed under both manual and automated conditions and required only minor modifications to the standard DNA synthesis cycle. In a further demonstration of the utility of M-A chemistry, the support-bound selenonucleoside was reacted with an H-phosphonate and then chain extended using phosphoramidite chemistry. Following initial unmasking of methyl-protected phosphoroselenolate diesters, pure oligodeoxynucleotides were isolated using standard deprotection and purification procedures and subsequently characterised by mass spectrometry and circular dichroism. The CD spectra of both modified and native duplexes derived from self-complementary sequences with A-form, B-form or mixed conformational preferences were essentially superimposable. These sequences were also used to study the effect of the modification upon duplex stability which showed context-dependent destabilisation (-0.4 to -3.1 °C per phosphoroselenolate) when introduced at the 5'-termini of A-form or mixed duplexes or at juxtaposed central loci within a B-form duplex (-1.0 °C per modification). As found with other nucleic acids incorporating selenium, expeditious crystallisation of a modified decanucleotide A-form duplex was observed and the structure solved to a resolution of 1.45 Å. The DNA structure adjacent to the modification was not significantly perturbed. The phosphoroselenolate linkage was found to impart resistance to nuclease activity. This journal is © The Royal Society of Chemistry 2019.Nickel-catalyzed 1,2-carboboration of alkenes is emerging as a useful method for chemical synthesis. Prior studies have been limited to only the incorporation of aryl groups. In this manuscript, a method for the 1,2-benzylboration of unactivated alkenes is presented. The reaction combines readily available alkenes, diboron reagents and benzylchlorides to generate synthetically versatile products with control of stereochemistry. The utility of the products as well as the mechanistic details of the process are also presented. This journal is © The Royal Society of Chemistry 2019.Efficient carbon-carbon bond formation is of great importance in modern organic synthetic chemistry. The pinacol coupling discovered over a century ago is still one of the most efficient coupling reactions to build the C-C bond in one step. However, traditional pinacol coupling often requires over-stoichiometric amounts of active metals as reductants, causing long-lasting metal waste issues and sustainability concerns. A great scientific challenge is to design a metal-free approach to the pinacol coupling reaction. Herein, we describe a light-driven pinacol coupling protocol without use of any metals, but with N2H4, used as a clean non-metallic hydrogen-atom-transfer (HAT) reductant. In this transformation, only traceless non-toxic N2 and H2 gases were produced as by-products with a relatively broad aromatic ketone scope and good functional group tolerance. A combined experimental and computational investigation of the mechanism suggests that this novel pinacol coupling reaction proceeds via a HAT process between photo-excited ketone and N2H4, instead of the common single-electron-transfer (SET) process for metal reductants. This journal is © The Royal Society of Chemistry 2019.Molecular probes activated by a single enzyme have been extensively used in bioimaging and disease diagnosis; however, imaging and identification in an accurate manner remains a challenge for such probes. Here, based on the specificity of enzyme recognition, we engineered a "double-locked" and enzyme-activated molecular probe (NML) for accurate bioimaging and hepatopathy differentiation. Triggered by the successive reactions with leucine aminopeptidase (LAP, first "key") and monoamine oxidase (MAO, second "key"), the emissive fluorophore (NF) was released. NML can be activated only in the presence of both LAP and MAO and can be silenced when either enzyme is inhibited. Benefiting from the "double-locked" strategy, NML showed higher accuracy for imaging of drug-induced liver injury (DILI) than the "single-locked" probe. With serum testing, NML showed significant differences in mouse models of both CCl4-induced liver cirrhosis and DILI. Significantly, NML can be applied to accurately distinguish serum samples from clinical patients with different hepatopathies. Our smart molecular probe may hold great potential for hepatopathy diagnosis and clinical transformation. This journal is © The Royal Society of Chemistry 2019.The modification of lysine residues with acylating agents has represented a ubiquitous approach to the construction of antibody conjugates, with the resulting amide bonds being robustly stable and clinically validated.  https://www.selleckchem.com/products/dibutyryl-camp-bucladesine.html  However, the conjugates are highly heterogeneous, due to the presence of numerous lysines on the surface of the protein, and greater control of the sites of conjugation are keenly sought. Here we present a novel approach to achieve the targeted modification of lysines distal to an antibody fragment's binding site, using a disulfide bond as a temporary 'hook' to deliver the acylating agent. This cysteine-to-lysine transfer (CLT) methodology offers greatly improved homogeneity of lysine conjugates, whilst retaining the advantages offered by the formation of amide linkages. This journal is © The Royal Society of Chemistry 2019.The capability to rank different potential drug molecules against a protein target for potency has always been a fundamental challenge in computational chemistry due to its importance in drug design. While several simulation-based methodologies exist, they are hard to use prospectively and thus predicting potency in lead optimization campaigns remains an open challenge. Here we present the first machine learning approach specifically tailored for ranking congeneric series based on deep 3D-convolutional neural networks. Furthermore we prove its effectiveness by blindly testing it on datasets provided by Janssen, Pfizer and Biogen totalling over 3246 ligands and 13 targets as well as several well-known openly available sets, representing one the largest evaluations ever performed. We also performed online learning simulations of lead optimization using the approach in a predictive manner obtaining significant advantage over experimental choice. We believe that the evaluation performed in this study is strong evidence of the usefulness of a modern deep learning model in lead optimization pipelines against more expensive simulation-based alternatives.