Strong and Superhydrophobic Wood with Aligned Cellulose Nanofibers as a Waterproof Structural Material†

Lightweight structural materials are important for the energy efficiency of applications, particularly those in the building sector. Here, inspired by nature, we developed a strong, superhydrophobic, yet lightweight material by simple in situ growth of nano‐SiO₂ and subsequent densification of the wood substrate. In situ generation of SiO₂ nanoparticles both inside the wood channels and on the wood surfaces gives the material superhydrophobicity, with static and dynamic contact angles of 159.4^o and 3^o, respectively. Densification of the wood to remove most of the spaces among the lumen and cell walls results in a laminated, dense structure, with aligned cellulose nanofibers, which in turn contributes to a high mechanical strength up to 384.2 MPa (7‐times higher than natural wood). Such treatment enables the strong and superhydrophobic wood (SH‐Wood) to be stable and have excellent water, acid, and alkaline resistance. The high mechanical strength of SH‐Wood combined with its excellent structural stability in harsh environments, as well its low density, positions the strong and superhydrophobic wood as a promising candidate for strong, lightweight, and durable structural materials that could potentially replace steel.     

Fragment‐Based De Novo Design Reveals a Small‐Molecule Inhibitor of Helicobacter Pylori HtrA

Sustained identification of innovative chemical entities is key for the success of chemical biology and drug discovery. We report the fragment‐based, computer‐assisted de novo design of a small molecule inhibiting Helicobacter pylori HtrA protease. Molecular binding of the designed compound to HtrA was confirmed through biophysical methods, supporting its functional activity in vitro. Hit expansion led to the identification of the currently best‐in‐class HtrA inhibitor. The results obtained reinforce the validity of ligand‐based de novo design and binding‐kinetics‐guided optimization for the efficient discovery of pioneering lead structures and prototyping drug‐like chemical probes with tailored bioactivity.     

Multidimensional De Novo Design Reveals 5‐HT2B Receptor‐Selective Ligands

We report a multi‐objective de novo design study driven by synthetic tractability and aimed at the prioritization of computer‐generated 5‐HT_2B receptor ligands with accurately predicted target‐binding affinities. Relying on quantitative bioactivity models we designed and synthesized structurally novel, selective, nanomolar, and ligand‐efficient 5‐HT_2B modulators with sustained cell‐based effects. Our results suggest that seamless amalgamation of computational activity prediction and molecular design with microfluidics‐assisted synthesis enables the swift generation of small molecules with the desired polypharmacology.     

Computation of mutual information from Hidden Markov Models

Understanding evolution at the sequence level is one of the major research visions of bioinformatics. To this end, several abstract models--such as Hidden Markov Models--and several quantitative measures--such as the mutual information--have been introduced, thoroughly investigated, and applied to several concrete studies in molecular biology. With this contribution we want to undertake a first step to merge these approaches (models and measures) for easy and immediate computation, e.g. for a database of a large number of externally fitted models (such as PFAM). Being able to compute such measures is of paramount importance in data mining, model development, and model comparison. Here we describe how one can efficiently compute the mutual information of a homogenous Hidden Markov Model orders of magnitude faster than with a naive, straight-forward approach. In addition, our algorithm avoids sampling issues of real-world sequences, thus allowing for direct comparison of various models. We applied the method to genomic sequences and discuss properties as well as convergence issues.     

Crystalline cellulose elastic modulus predicted by atomistic models of uniform deformation and nanoscale indentation

The elastic modulus of cellulose Iβ in the axial and transverse directions was obtained from atomistic simulations using both the standard uniform deformation approach and a complementary approach based on nanoscale indentation. This allowed comparisons between the methods and closer connectivity to experimental measurement techniques. A reactive force field was used that explicitly describes hydrogen bond, coulombic and van der Waals interactions, allowing each contribution to the inter- and intra-molecular forces to be analyzed as a function of crystallographic direction. The uniform deformation studies showed that the forces dominating elastic behavior differed in the axial and transverse directions because of the relationship between the direction of the applied strain and the hydrogen bonding planes. Simulations of nanoscale indentation were then introduced to model the interaction between a hemispherical indenter with the $(1\bar{1}0)$ surface of a cellulose Iβ rod. The role of indenter size, loading force and indentation speed on the transverse elastic modulus was studied and, for optimized parameters, the results found to be in good agreement with experimentally-measured transverse elastic modulus for individual cellulose crystals.     

Determination of neurotransmitters and their metabolites using one- and two-dimensional liquid chromatography with acidic potassium permanganate chemiluminescence detection

High-performance liquid chromatography with chemiluminescence detection based on the reaction with acidic potassium permanganate and formaldehyde was explored for the determination of neurotransmitters and their metabolites. The neurotransmitters norepinephrine and dopamine were quantified in the left and right hemispheres of rat hippocampus, nucleus accumbens and prefrontal cortex, and the metabolites vanillylmandelic acid, 3,4-dihydrophenylacetic acid, 5-hydroxyindole-3-acetic acid and homovanillic acid were identified in human urine. Under optimised chemiluminescence reagent conditions, the limits of detection for these analytes ranged from 2.5?×?10^?8 to 2.5?×?10^?7 M. For the determination of neurotransmitter metabolites in urine, a two-dimensional high-performance liquid chromatography (2D-HPLC) separation operated in heart-cutting mode was developed to overcome the peak capacity limitations of the one-dimensional separation. This approach provided the greater separation power of 2D-HPLC with analysis times comparable to conventional one-dimensional separations. Figure

2D-HPLC separation and permanganate chemiluminescence detection of neurotransmitter metabolites     

Deorphaning the Macromolecular Targets of the Natural Anticancer Compound Doliculide

The cyclodepsipeptide doliculide is a marine natural product with strong actin‐polymerizing and anticancer activities. Evidence for doliculide acting as a potent and subtype‐selective antagonist of prostanoid E receptor 3 (EP3) is presented. Computational target prediction suggested that this membrane receptor is a likely macromolecular target and enabled immediate in vitro validation. This proof‐of‐concept study demonstrates the in silico deorphanization of phenotypic screening hits as a viable concept for future natural‐product‐inspired chemical biology and drug discovery efforts.