Combinatorial Chemistry & High Throughput Screening - Volume 15, Issue 6, 2012

In the life cycle of hepatitis C virus (HCV), NS3/NS4A protease has been proved to play a vital role in the replication of the HCV virus. Narlaprevir and its derivatives, the inhibitors of NS3/NS4A, would be potentially developed as important anti-HCV drugs in the future. In this study, quantitative structure-activity relationship (QSAR) analyses for 190 narlaprevir derivatives were conducted using comparative molecular field analysis (CoMFA), comparative molecular indices analysis (CoMSIA) and hologram quantitative structure–activity relationship (HQSAR) techniques. Both of the best CoMFA and HQSAR models showed statistical significance for the training set and good predictive accuracy for the test set, which strongly manifested the robustness of the CoMFA and HQSAR models. The CoMFA contour maps and the HQSAR contribution maps were both presented. Furthermore, based on the essential factors for ligand binding derived from the QSAR models, sixteen new derivatives were designed and some of them showed higher inhibitory activities confirmed by our models and molecular docking studies. General speaking, this study provides useful suggestions for the design of potential anti-HCV drugs.

The iodocyclization of functionally-substituted alkynes provides an excellent way to prepare a wide range of iodoheterocycles, which can then be readily elaborated through palladium-catalyzed Suzuki-Miyaura, Sonogashira, Heck, Hartwig-Buchwald, and carbonylation processes into libraries of medicinally relevant heterocycles. The synthesis of libraries of indoles, benzofurans, benzothiophenes, isocoumarins and pyrones, cyclic imidates, isoxazoles, furans using this approach is reviewed. This technology is very versatile, proceeds under mild reaction conditions in high yields, and tolerates considerable functionality.

Affinity selection-mass spectrometry (AS-MS) is a sensitive technology for identifying small molecules that bind to target proteins, and assays enabled by AS-MS can be used to delineate relative binding affinities of ligands for proteins. 'Indirect' AS-MS assays employ size-exclusion techniques to separate target-ligand complexes from unbound ligands, and target-associated ligands are then specifically detected by liquid chromatography mass spectrometry. We report how indirect AS-MS binding assays with known reference control compounds were used as guideposts for development of an optimized purification method for CXCR4, a G-protein coupled chemokine receptor, for which we sought novel antagonists. The CXCR4 purification method that was developed was amenable to scale-up and enabled the screening of purified recombinant human CXCR4 against a large combinatorial library of small molecules by high throughput indirect AS-MS. The screen resulted in the discovery of new ligands that competed off binding of reference compounds to CXCR4 in AS-MS binding assays and that antagonized SDF1α-triggered responses and CXCR4-mediated HIV1 viral uptake in cell-based assays. This report provides a methodological paradigm whereby indirect AS-MS-based ligand binding assays may be used to guide optimal integral membrane protein purification methods that enable downstream affinity selection-based applications such as high throughput AS-MS screens.

Polymerase chain reaction (PCR) is one of the most popular molecular biological techniques and has been widely applied in many areas. However, PCR still faces challenges nowadays. During recent decades, the experimental procedure of PCR, including the primer design, was always the focus of attention, while little attention was paid to the analysis of the PCR template, and still nobody can accurately predict whether or not a DNA sequence can be simply amplified using conventional Taq DNA polymerase-based PCR protocol. In this study, we focus on the DNA template, the subject of PCR experiment, and introduce a support vector machine (SVM) based method to help evaluate PCR result. Through the Jackknife cross-validation test, our method achieves an accuracy of 92.06%, with 93.62% sensitivity and 90.53% specificity.

Acetylcholinesterase has long been considered as a target for Alzheimer disease therapy. In this work, several classification models were built for the purpose of distinguishing acetylcholinesterase inhibitors (AChEIs) and decoys. Each molecule was initially represented by 211 ADRIANA.Code and 334 MOE descriptors. Correlation analysis, F-score and attribute selection methods in Weka were used to find the best reduced set of descriptors, respectively. Additionally, models were built using a Support Vector Machine and evaluated by 5-, 10-fold and leave-one-out cross-validation. The best model gave a Matthews Correlation Coefficient (MCC) of 0.99 and a prediction accuracy (Q) of 99.66% for the test set. The best model also gave good result on an external test set of 86 compounds (Q=96.51%, MCC=0.93). The descriptors selected by our models suggest that H-bond and hydrophobicity interactions are important for the classification of AChEIs and decoys.

An efficient synthesis of dialkyl pyrrolo[2,1-a]isoquinoline-2,3-dicarboxylates, pyrrolo[1,2-a]quinoline-1,2- dicarboxylates and indolizines is described via one-pot reactions of isoquinoline, quinoline or pyridine and phenacyl bromids with dialkyl acetylenedicarboxylates or diaryloylacetylene under solvent-free conditions at 50°C. The mild reaction conditions and high yields of the products exhibit the good synthetic advantage of these methods.

Chiral analysis of profens in human plasma is an important area of research due to different pharmaceutical activities of their enantiomers. The solid phase extraction of ibuprofen and flurbiprofen from human plasma was carried out on C18 cartridges by using phosphate buffer (50 mM, pH 6.0) followed by elution with methanol. Chiral-HPLC was performed on AmyCoat RP (150 mm x 46 mm, 3 μm particle size) column by using different combinations of wateracetonitrile- trifluoro acetic acid at 1.5 mLmin-1 flow rate. The detection was achieved at 236 and 254 nm for ibuprofen and flurbiprofen, respectively with 27±1°C as working temperature. The chromatographic parameters i.e. retention (k), separation (α) and resolution (Rs) factors ranged from 4.54-14.42, 1.10-1.30 and 1.01-1.49, respectively. The binding differences of enantiomers of ibuprofen and flurbiprofen were 4.4 and 5.2, respectively. These values suggest that S-(+)- enantiomer of flurbiprofen is more active than ibuprofen due to low enantiomeric difference of the later drug. The developed SPE-Chiral HPLC methods were validated, which are selective, efficient and reproducible.