Liquids with High Compressibility.

Compressibility is a fundamental property of all materials. For fluids, that is, gases and liquids, compressibility forms the basis of technologies such as pneumatics and hydraulics and determines basic phenomena such as the propagation of sound and shock waves. In contrast to gases, liquids are almost incompressible. If the compressibility of liquids could be increased and controlled, new applications in hydraulics and shock absorption could result. Here, it is shown that dispersing hydrophobic porous particles into water gives aqueous suspensions with much greater compressibilities than any normal liquids such as water (specifically, up to 20 times greater over certain pressure ranges). The increased compressibility results from water molecules being forced into the hydrophobic pores of the particles under applied pressure. The degree of compression can be controlled by varying the amount of porous particles added. Also, the pressure range of compression can be reduced by adding methanol or increased by adding salt. In all cases, the liquids expand back to their original volume when the applied pressure is released. The approach shown here is simple and economical and could potentially be scaled up to give large amounts of highly compressible liquids.

Quantitative prediction of excited-state decay rates for radical anion photocatalysts.

We present a computational approach for predicting key properties of organic radical anions, including excited-state lifetimes and redox potentials. The approach shows good agreement with experimental data and has potential for in silico screening to facilitate the rational design of photocatalysts.

Noria and its derivatives as hosts for chemically and thermally robust Type II porous liquids.

Porous Liquids (PLs) are a new class of material that possess both fluidity and permanent porosity. As such they can act as enhanced, selective solvents and may ultimately find applications which are not possible for porous solids, such as continuous flow separation processes. Type II PLs consist of empty molecular hosts dissolved in size-excluded solvents and to date have mainly been based on hosts that have limited chemical and thermal stability. Here we identify Noria, a rigid cyclic oligomer as a new host for the synthesis of more robust Type II PLs. Although the structure of Noria is well-documented, we find that literature has overlooked the true composition of bulk Noria samples. We find that bulk samples typically consist of Noria (ca. 40%), a Noria isomer, specifically a resorcinarene trimer, "R3" (ca. 30%) and other unidentified oligomers (ca. 30%). Noria has been characterised crystallographically as a diethyl ether solvate and its 1H NMR spectrum fully assigned for the first time. The previously postulated but unreported R3 has also been characterised crystallographically as a dimethyl sulfoxide solvate, which confirms its alternative connectivity to Noria. Noria and R3 have low solubility which precludes their use in Type II PLs, however, the partially ethylated derivative Noria-OEt dissolves in the size-excluded solvent 15-crown-5 to give a new Type II PL. This PL exhibits enhanced uptake of methane (CH4) gas supporting the presence of empty pores in the liquid. Detailed molecular dynamics simulations support the existence of pores in the liquid and show that occupation of the pores by CH4 is favoured. Overall, this work revises the general accepted composition of bulk Noria samples and shows that Noria derivatives are appropriate for the synthesis of more robust Type II PLs.

Design, synthesis and evaluation of cholinesterase hybrid inhibitors using a natural steroidal alkaloid as precursor.

To date, Alzheimer's disease is the most alarming neurodegenerative disorder worldwide. This illness is multifactorial in nature and cholinesterase inhibitors have been the ones used in clinical treatments. In this context, many of these drugs selectively inhibit the acetylcholinesterase enzyme interacting in both the active site and the peripheric anionic site. Besides, some agents have exhibited extensive benefits being able to co-inhibit butyrylcholinesterase. In this contribution, a strategy previously explored by numerous authors is reported; the synthesis of hybrid cholinesterase inhibitors. This strategy uses a molecule of recognized high inhibitory activity (tacrine) together with a steroidal alkaloid of natural origin using different connectors. The biological assays demonstrated the improvement in the inhibitory activity compared to the alkaloidal precursor, together with the reinforcement of the interactions in multiple sites of the enzymatic cavity. This strategy should be explored and exploited in this area. Docking and molecular dynamic studies were performed to explain enzyme-ligand interactions, assisting a structure-activity relationship analysis.

An activity prediction model for steroidal and triterpenoidal inhibitors of Acetylcholinesterase enzyme.

Nowadays, the importance of computational methods in the design of therapeutic agents in a more efficient way is indisputable. Particularly, these methods have been important in the design of novel acetylcholinesterase enzyme inhibitors related to Alzheimer's disease. In this sense, in this report a computational model of linear prediction of acetylcholinesterase inhibitory activity of steroids and triterpenes is presented. The model is based in a correlation between binding energies obtained from molecular dynamic simulations (after docking studies) and [Formula: see text] values of a training set. This set includes a family of natural and semi-synthetic structurally related alkaloids reported in bibliography. These types of compounds, with some structural complexity, could be used as building blocks for the synthesis of many important biologically active compounds Therefore, the present study proposes an alternative based on the use of conventional and easily accessible tools to make progress on the rational design of molecules with biological activity.

Clinanthus microstephium, an Amaryllidaceae Species with Cholinesterase Inhibitor Alkaloids: Structure-Activity Analysis of Haemanthamine Skeleton Derivatives.

Plants of the Amaryllidaceae family are well-known (not only) for their ornamental value but also for the alkaloids that they produce. In this report, the first phytochemical study of Clinanthus genus was carried out. The chemical composition of alkaloid fractions from Clinanthus microstephium was analyzed by GC/MS and NMR. Seven known compounds belonging to three structural types of Amaryllidaceae alkaloids were identified. An epimeric mixture of a haemanthamine-type compound (6-hydroxymaritidine) was tested as an inhibitor against acetyl- and butyrylcholinesterase enzymes (AChE and BChE, respectively), two enzymes relevant in the treatment of Alzheimer's disease, with good results. Structure-activity relationships through molecular docking studies with this alkaloid and other structurally related compounds were discussed.

In search of the best DFT functional for dealing with organic anionic species.

Quantum chemical computational methods are thought to have problems in dealing with unstable organic anions. This work assesses the ability of different Density Functional Theory (DFT) functionals to reproduce the electron affinity and reduction potential of organic compounds. The performance of 23 DFT functionals was evaluated by computing the negative electron affinities (from 0 eV to -3.0 eV) and reduction potentials in acetonitrile (from 0 to -2.7 V). In general, most of the hybrid GGA functionals work fine in the prediction of electron affinities, BPW91, B3PW91 and M06 being the best in each class of functionals (pure, hybrid and meta-GGA functionals, respectively). On the other hand, the ab initio post-Hartree-Fock methods, MP2 and coupled-cluster (CCSD(T)), as well as the double hybrid functionals, B2PLYP and mPW2PLYP, usually fail. For compounds with EAs lower than -1.75 eV, a method for stabilizing the anion, based on solvation with the IEFPCM model, was employed. In this case, BPW91, PBE0 and M06-HF could be the recommended option for the pure, hybrid and meta-GGA functionals, respectively. The situation improves for the evaluation and prediction of redox potentials. In this case the performance of the DFT functionals is better, in part because the solvent assists in the stabilization of the anions. Nevertheless, there is a systematic bias in the calculation of absolute redox potentials, which could be corrected by using a redox partner that helps by the cancellation of errors. In this case, the hybrid and meta-GGA functionals B3PW91, PBE0, TPSSh and M06 are also among the best for computing redox potentials with a mean absolute deviation (MAD) lower than 0.13 V.

Solanocapsine derivatives as potential inhibitors of acetylcholinesterase: Synthesis, molecular docking and biological studies.

The investigation of natural products in medicinal chemistry is essential today. In this context, acetylcholinesterase (AChE) inhibitors comprise one type of the compounds most actively studied in the search for an effective treatment of symptoms of Alzheimer's disease. This work describes the isolation of a natural compound, solanocapsine, the preparation of its chemical derivatives, the evaluation of AChE inhibitory activity, and the structure-activity analysis of relevant cases. The influence of structural variations on the inhibitory potency was carefully investigated by modifying different reactive parts of the parent molecule. A theoretical study was also carried out into the binding mode of representative compounds to the enzyme through molecular modeling. The biological properties of the series were investigated. Through this study valuable information was obtained of steroidal alkaloid-type compounds as a starting point for the synthesis of AChE inhibitors.