Beining Chen

MIP-based solid phase extraction cartridges combined with MIP-based sensors for the detection of microcystin-LR.

Microsystin-LR is one of the most widespread and dangerous toxins produced by the freshwater Cyanobacteria. The contamination of water supplies with microcystin-LR has been reported in several areas around the world and the development of an easy-to-use, rapid, robust and inexpensive sensor for this toxin is urgently required. In this work an artificial receptor for microcystin-LR was synthesised using the technique of molecular imprinting. The composition of the molecularly imprinted polymer (MIP) was optimised using computer modelling. The synthesised polymer was used both as a material for solid-phase extraction (SPE) and as a sensing element in a piezoelectric sensor. Using the combination of SPE followed by detection with a piezoelectric sensor the minimum detectable amount of toxin was 0.35 nM. The use of MIP-SPE provided up to 1000 fold pre-concentration, which was more than sufficient for achieving the required detection limit for microcystin-LR in drinking water (1 nM). This work is the first example where the same MIP receptor has been used successfully for both SPE and the corresponding sensor.

Evaluation of machine-learning methods for ligand-based virtual screening

Machine-learning methods can be used for virtual screening by analysing the structural characteristics of molecules of known (in)activity, and we here discuss the use of kernel discrimination and naive Bayesian classifier (NBC) methods for this purpose. We report a kernel method that allows the processing of molecules represented by binary, integer and real-valued descriptors, and show that it is little different in screening performance from a previously described kernel that had been developed specifically for the analysis of binary fingerprint representations of molecular structure. We then evaluate the performance of an NBC when the training-set contains only a very few active molecules. In such cases, a simpler approach based on group fusion would appear to provide superior screening performance, especially when structurally heterogeneous datasets are to be processed.

Plant perception of β-aminobutyric acid is mediated by an aspartyl-tRNA synthetase

Specific chemicals can prime the plant immune system for augmented defence. β-aminobutyric acid (BABA) is a priming agent that provides broad-spectrum disease protection. However, BABA also suppresses plant growth when applied in high doses, which has hampered its application as a crop defence activator. Here we describe a mutant of Arabidopsis thaliana that is impaired in BABA-induced disease immunity (ibi1) but hypersensitive to BABA-induced growth repression. IBI encodes an aspartyl-tRNA synthetase. Enantiomer-specific binding of R-BABA to IBI1 primed the protein for non-canonical defence signalling in the cytoplasm after pathogen attack. This priming was associated with aspartic acid accumulation and tRNA-induced phosphorylation of translation initiation factor eIF2α. However, mutation of eIF2α-phosphorylating GCN2 kinase did not affect BABA-induced immunity, but relieved BABA-induced growth repression. Hence, BABA-activated IBI1 controls plant immunity and growth via separate pathways. Our results open new opportunities to separate broad-spectrum disease resistance from the associated costs on plant growth.

Design and synthesis of novel monocyclic β-lactam inhibitors of prostate specific antigen

Abstract A novel series of monocyclic β-lactam analogues was designed using a homology derived model of prostate specific antigen (PSA) and by application of a multiple copy simultaneous search technique. Syntheses were conducted by assembly of the β-lactam core via a Staudinger reaction with elaboration at the 1, 3 and 4 positions to probe active site binding. Inhibition against PSA was evaluated.

Exploring Catalyst and Solvent Effects in the Multicomponent Synthesis of Pyridine-3,5-dicarbonitriles

The effects of an ionic base, tetrabutylammonium hydroxide (TBAH), and an amine base, piperidine, on the direct synthesis of pyridine-3,5-dicarbonitriles using a multicomponent reaction (MCR) from aldehydes, malononitrile, and thiols were systematically investigated. The amine base showed better results when the MCR was performed in ethanol, whereas employing the ionic base in acetonitrile resulted in similar yields but in a much shorter reaction time. A modified protocol to overcome the difficulty in the direct synthesis of pyridine-3,5-dicarbonitriles via the MCR from sterically hindered aldehydes using either base was realized by changing the reaction solvent from ethanol to acetonitrile. Mechanistically, the two catalysts were found to each promote different pathways in the final oxidation step of the penultimate product, 1,4-dihydropyridine 6. A reaction intermediate, Knoevenagel adduct 7, plays the major role in the amine base-catalyzed system, while in the presence of an ionic base, aerobic oxygen acts as the primary oxidant.

Ligand-based virtual screening using bayesian networks

A Bayesian inference network (BIN) provides an interesting alternative to existing tools for similarity-based virtual screening. The BIN is particularly effective when the active molecules being sought have a high degree of structural homogeneity but has been found to perform less well with structurally heterogeneous sets of actives. In this paper, we introduce an alternative network model, called a Bayesian belief network (BBN), that seeks to overcome this limitation of the BIN approach. Simulated virtual screening experiments with the MDDR, WOMBAT and MUV data sets show that the BIN and BBN methods allow effective screening searches to be carried out. However, the results obtained are not obviously superior to those obtained using a much simpler approach that is based on the use of the Tanimoto coefficient and of the square roots of fragment occurrence frequencies.

Knowledge-Based Approach to de Novo Design Using Reaction Vectors

A knowledge-based approach to the de novo design of synthetically feasible molecules is described. The method is based on reaction vectors which represent the structural changes that take place at the reaction center along with the environment in which the reaction occurs. The reaction vectors are derived automatically from a database of reactions which is not restricted by size or reaction complexity. A structure generation algorithm has been developed whereby reaction vectors can be applied to previously unseen starting materials in order to suggest novel syntheses. The approach has been implemented in KNIME and is validated by reproducing known synthetic routes. We then present applications of the method in different drug design scenarios including lead optimization and library enumeration. The method offers great potential for capturing and using the growing body of data on reactions that is becoming available through electronic laboratory notebooks.

Combination Rules for Group Fusion in Similarity-Based Virtual Screening.

This paper evaluates the screening effectiveness of 15 parameter‐free, similarity‐based and rank‐based rules for group fusion, where one combines the outputs of similarity searches from multiple reference structures using ECFC_4 fingerprints and a Bayesian inference network. Searches of the MDDR and WOMBAT databases show that group fusion is most effective when as many reference structures as possible are used, when only a small proportion of each ranked similarity list is submitted to the final fusion rule, and when a fusion rule based on reciprocal rank positions is used to combine the individual search outputs. An analysis of the reciprocal rank rule suggests that its effectiveness derives from the close relationship that exists between the reciprocal rank of a database structure and its probability of activity.

Design, Synthesis, and Structure−Activity Relationship of Indole-3-glyoxylamide Libraries Possessing Highly Potent Activity in a Cell Line Model of Prion Disease

Transmissible spongiform encephalopathies (TSEs) are a family of invariably fatal neurodegenerative disorders for which no effective curative therapy currently exists. We report here the synthesis of a library of indole-3-glyoxylamides and their evaluation as potential antiprion agents. A number of compounds demonstrated submicromolar activity in a cell line model of prion disease together with a defined structure-activity relationship, permitting the design of more potent compounds that effected clearance of scrapie in the low nanomolar range. Thus, the indole-3-glyoxylamides described herein constitute ideal candidates to progress to further development as potential therapeutics for the family of human prion disorders.

“Bite‐and‐Switch” Approach to Creatine Recognition by Use of Molecularly Imprinted Polymers

The detection of creatine is important in the analysis of athletes and body builders. Here is reported the preparation of a synthetic polymer using imprinting polymerization, which leaves the polym ...