Pharmacophore Modeling and Virtual Screening of Novel Inhibitors for c-Kit Kinase

The stem cell factor receptor (c‐Kit) has been known to play critical roles in regulating numerous aspects of cellular behavior including cell growth, differentiation, migration and metabolism. In this investigation, a three‐dimensional pharmacophore model of c‐Kit inhibitors has been established by using the HypoGen algorithms implemented in the catalyst software package. The best quantitative pharmacophore model, hypothesis 1, which has the highest correlation coefficient (0.989), consists of one hydrogen bond acceptor, two hydrogen bond donors and one hydrophobic feature. To our knowledge, this is the first report on the pharmacophore modeling study of c‐Kit inhibitors. The best hypothesis, hypothesis 1, was used to screen molecular structural databases, including Specs and China Natural Products Database for potential lead compounds. The hit compounds were subsequently subjected to filtering by Lipinski's rules and docking study to refine the retrieved hits and as a result to reduce the rate of false positive. Finally 28 compounds were purchased or synthesized for further in vitro assay against several human tumour cell lines including A549, MCF‐7, HepG2 and PC‐3, in which c‐Kit is overexpressed. Two compounds show very low micromolar inhibition potency against the PC‐3 and HepG2 cell lines respectively. And they were selected for further modification and testing.     

Investigation of modulation parameters in multiplexing gas chromatography

Combination of information technology and separation sciences opens a new avenue to achieve high sample throughputs and therefore is of great interest to bypass bottlenecks in catalyst screening of parallelized reactors or using multitier well plates in reaction optimization. Multiplexing gas chromatography utilizes pseudo-random injection sequences derived from Hadamard matrices to perform rapid sample injections which gives a convoluted chromatogram containing the information of a single sample or of several samples with similar analyte composition. The conventional chromatogram is obtained by application of the Hadamard transform using the known injection sequence or in case of several samples an averaged transformed chromatogram is obtained which can be used in a Gauss–Jordan deconvolution procedure to obtain all single chromatograms of the individual samples. The performance of such a system depends on the modulation precision and on the parameters, e.g. the sequence length and modulation interval. Here we demonstrate the effects of the sequence length and modulation interval on the deconvoluted chromatogram, peak shapes and peak integration for sequences between 9-bit (511 elements) and 13-bit (8191 elements) and modulation intervals Δt between 5 s and 500 ms using a mixture of five components. It could be demonstrated that even for high-speed modulation at time intervals of 500 ms the chromatographic information is very well preserved and that the separation efficiency can be improved by very narrow sample injections. Furthermore this study shows that the relative peak areas in multiplexed chromatograms do not deviate from conventionally recorded chromatograms.     

PPAR激动剂的定向设计、虚拟筛选及合成

过氧化物酶体增殖因子活化受体(PPAR)是核受体超家族的一员.基于受体结构的药物分子设计与组合化学策略相结合,构建了过氧化物酶体增殖因子活化受体(PPAR)激动剂的虚拟化合物库.将已知小分子配体(GW409544)与PPAR晶体复合物进行剥离,得到受体的活性构象,并利用此活性受体分子与虚拟库中小分子进行对接和虚拟筛选,得到理论上结合较强的化合物,并对这些化合物进行合成,共合成9个新化合物.活性筛选结果显示化合物对PPAR具有一定的亲和力,其中有三个化合物显示出对PPARα,PPARγ的双重激动作用,从而指导新活性化合物的设计和合成.     

Fast Multi‐residue Screening for 84 Pesticides in Tea by Gas Chromatography with Dual‐tower Auto‐sampler,Dual‐column and Dual Detectors

A fast multi‐residue screening method for determining pesticides in tea is described. Pesticides are extracted from tea with acetone and methylene chloride, then enriched and cleaned up with solid phase extraction (SPE) prior to gas chromatographic determination. The fast screening is achieved by a gas chromatograph system equipped with dual‐column, dual‐tower auto‐sampler and both electron capture detector (ECD) and flame photometric detector (FPD). Optimal conditions are investigated for the prospective pesticides including column selection, detection mode, the retention behaviors, quantitative calibration, as well as the recoveries and repeatability of pesticides from tea samples. Under the optimal conditions, with the FPD‐P detector accompanied CP‐SIL 13CB column, 48 pesticides can be separated well and detected within 38 min; and with a DB‐5 column, 35 ECD‐detectable pesticides can be separated and detected within 46 min. The recoveries of 84 pesticides in tea samples are 65–120% with 0.34–16% RSD for spiking 0.02–3.0 mg/kg standard species. Because of the thermal instability of most pesticides, direct cold extraction of pesticides from a tea sample is recommended. The proposed method provided a very fast and efficient procedure to screen 84 pesticides from a complicated tea sample matrix.     

Validation of an empirical RNA-ligand scoring function for fast flexible docking using RiboDock®

We report the design and validation of a fast empirical function for scoring RNA-ligand interactions, and describe its implementation within RiboDock, a virtual screening system for automated flexible docking. Building on well-known protein-ligand scoring function foundations, features were added to describe the interactions of common RNA-binding functional groups that were not handled adequately by conventional terms, to disfavour non-complementary polar contacts, and to control non-specific charged interactions. The results of validation experiments against known structures of RNA-ligand complexes compare favourably with previously reported methods. Binding modes were well predicted in most cases and good discrimination was achieved between native and non-native ligands for each binding site, and between native and non-native binding sites for each ligand. Further evidence of the ability of the method to identify true RNA binders is provided by compound selection ('enrichment factor') experiments based around a series of HIV-1 TAR RNA-binding ligands. Significant enrichment in true binders was achieved amongst high scoring docking hits, even when selection was from a library of structurally related, positively charged molecules. Coupled with a semi-automated cavity detection algorithm for identification of putative ligand binding sites, also described here, the method is suitable for the screening of very large databases of molecules against RNA and RNA-protein interfaces, such as those presented by the bacterial ribosome.     

Competition STD NMR for the detection of high-affinity ligands and NMR-based screening

The reported competition STD NMR method combines saturation transfer difference (STD) NMR with competition binding experiments to allow the detection of high-affinity ligands that undergo slow chemical exchange on the NMR time-scale. With this technique, the presence of a competing high-affinity ligand in the compound mixture can be detected by the disappearance or reduction of the STD signals of a low-affinity indicator ligand. This is demonstrated on a BACE1 (beta-site amyloid precursor protein cleaving enzyme 1) protein-inhibitor system. This method can also be used to derive an approximate value, or a lower limit, for the dissociation constant of the potential ligand based on the reduction of the signal intensity of the STD indicator, which is illustrated on an HSA (human serum albumin) model system. This leads to important applications of the competition STD NMR method for lead discovery: it can be used (i) for compound library screening against a broad range of drug targets to identify both high- and low-affinity ligands and (ii) to rank order analogs rapidly and derive structure-activity relationships, which are used to optimize these NMR hits into viable drug leads.     

Aminoglycoside microarrays to explore interactions of antibiotics with RNAs and proteins

RNA is an important target for drug discovery efforts. Several clinically used aminoglycoside antibiotics bind to bacterial rRNA and inhibit protein synthesis. Aminoglycosides, however, are losing efficacy due to their inherent toxicity and the increase in antibiotic resistance. Targeting of other RNAs is also becoming more attractive thanks to the discovery of new potential RNA drug targets through genome sequencing and biochemical efforts. Identification of new compounds that target RNA is therefore urgent, and we report here on the development of rapid screening methods to probe binding of low molecular weight ligands to proteins and RNAs. A series of aminoglycosides has been immobilized onto glass microscope slides, and binding to proteins and RNAs has been detected by fluorescence. Construction and analysis of the arrays is completed by standard DNA genechip technology. Binding of immobilized aminoglycosides to proteins that are models for study of aminoglycoside toxicity (DNA polymerase and phospholipase C), small RNA oligonucleotide mimics of aminoglycoside binding sites in the ribosome (rRNA A-site mimics), and a large (approximately 400 nucleotide) group I ribozyme RNA is detected. The ability to screen large RNAs alleviates many complications associated with binding experiments that use isolated truncated regions from larger RNAs. These studies lay the foundation for rapid identification of small organic ligands from combinatorial libraries that exhibit strong and selective RNA binding while displaying decreased affinity to toxicity-causing proteins.