Improving (Q)SAR predictions by examining bias in the selection of compounds for experimental testing

ABSTRACT

Existing data on structures and biological activities are limited and distributed unevenly across distinct molecular targets and chemical compounds. The question arises if these data represent an unbiased sample of the general population of chemical-biological interactions. To answer this question, we analyzed ChEMBL data for 87,583 molecules tested against 919 protein targets using supervised and unsupervised approaches. Hierarchical clustering of the Murcko frameworks generated using Chemistry Development Toolkit showed that the available data form a big diffuse cloud without apparent structure. In contrast hereto, PASS-based classifiers allowed prediction whether the compound had been tested against the particular molecular target, despite whether it was active or not. Thus, one may conclude that the selection of chemical compounds for testing against specific targets is biased, probably due to the influence of prior knowledge. We assessed the possibility to improve (Q)SAR predictions using this fact: PASS prediction of the interaction with the particular target for compounds predicted as tested against the target has significantly higher accuracy than for those predicted as untested (average ROC AUC are about 0.87 and 0.75, respectively). Thus, considering the existing bias in the data of the training set may increase the performance of virtual screening.     

Profiling analysis of volatile compounds from fruits using comprehensive two-dimensional gas chromatography and image processing techniques

An image processing approach originating from the proteomics field has been transferred successfully to the processing of data obtained with comprehensive two-dimensional gas chromatographic separations data. The approach described here has proven to be a useful analytical tool for unbiased pattern comparison or profiling analyses, as demonstrated with the differentiation of volatile patterns (“aroma”) from fruits such as apples, pears, and quince fruit. These volatile patterns were generated by headspace solid phase microextraction coupled to comprehensive two-dimensional gas chromatography (HS-SPME-GC × GC). The data obtained from GC × GC chromatograms were used as contour plots which were then converted to gray-scale images and analyzed utilizing a workflow derived from 2D gel-based proteomics. Run-to-run variations between GC × GC chromatograms, respectively their contour plots, have been compensated by image warping. The GC × GC images were then merged into a fusion image yielding a defined and project-wide spot (peak) consensus pattern. Within detected spot boundaries of this consensus pattern, relative quantities of the volatiles from each GC × GC image have been calculated, resulting in more than 700 gap free volatile profiles over all samples. These profiles have been used for multivariate statistical analysis and allowed clustering of comparable sample origins and prediction of unknown samples. At present state of development, the advantage of using mass spectrometric detection can only be realized by data processing off-line from the identified software packages. However, such information provides a substantial basis for identification of statistically relevant compounds or for a targeted analysis.     

A rapid and simple method for the isolation of mutant variants regulating tissue-specific expression of the tni gene through drug selection

TnINEO fusion gene was constructed by fusing 3.4-kbp of quailTnI genomic DNA sequences spanning the promoter to exon 5 and aneo gene in frame. A myoblast cell line was established after transfection of pTnINEO. Since this cell line was passaged several times, a high frequency of neomycin (G418) sensitivity conversion was detected. Two drug-resistant variants were analyzed through genomic Southern blot and S1 nuclease protection assay. One variant has a mutation(s) in the regulatory element that activated the dormantTnI promoter-enhancer in myoblast, and the other has shown the genomic rearrangement. This result presented the possibility of isolating factor(s) that activate the muscle-specificTnI promoter simply by screening drug-resistant cells having appropriate mutations.     

多层螺旋CT诊断甲状腺癌中的辐射和对比剂剂量选择

本文对多层螺旋CT（MSCT）诊断甲状腺癌中的辐射和对比剂剂量选择进行了分析。选取2016年12月～2018年12月本院行MSCT检查的甲状腺癌、甲状腺良性结节患者各200例,依据随机数字表分为A组、B组、C组、D组,每组50例,A组参数为对比剂1.2 mL/kg、120 kV、180 mA,B组为对比剂1.0 mL/kg、120 kV、180 mA,C组为对比剂1.2 mL/kg、100 kV、100 mA,D组为对比剂1.0 mL/kg、100 kV、100 mA。结果显示,A组和B组CT容积剂量指数（CTDIvol）、剂量长度乘积（DLP）、有效辐射剂量（ED）明显低于C组和D组,A组和B组甲状腺CT值、背景信号、背景噪声明显高于C组和D组,差异有统计学意义（P<0.05）,A组、B组、C组、D组信噪比（SNR）、对比信噪比（CNR）、图像质量评分比较,差异无统计学意义（P>0.05）;A组、B组、C组、D组诊断甲状腺癌的敏感度、特异度、准确度比较,差异无统计学意义（P>0.05）。本文证实,对于MSCT诊断甲状腺癌中的辐射和对比剂剂量,选择1.0 mL/kg、100 kV、100 mA可在不严重影响图像质量及检查结果下有效减少患者的CT辐射,值得临床推广。     

Label‐ and modification‐free‐based in situ selection of bovine serum albumin specific aptamer

Systematic evolution of ligands by exponential enrichment is a traditional approach to select aptamer, which has a great potential in biosensing field. However, chemical modifications of DNA library or targets before selection might block the real recognition and binding sites between aptamers and their targets. In this study, a label‐ and modification‐free‐based in situ selection strategy was developed to overcome this limitation. The strategy is an attempt to screen bovine serum albumin aptamers according to the principle of electrophoretic mobility shift assay, and allowed single‐stranded DNA sequence to be fully exposed to interact with bovine serum albumin which was mixed with the agarose gel beforehand. After eight rounds of selection, specific aptamer with low dissociation constant (K_d) value of 69.44 ± 7.60 nM was selected and used for subsequent establishment of fluorescence biosensor. After optimization, the optimal aptasensor exhibited a high sensitivity toward bovine serum albumin with a limit of detection of 0.24 ng/mL (linear range from 1 to 120 ng/mL). These results indicated that the label‐ and modification‐free‐based in situ selection strategy proposed in this work could effectively select specific aptamer to develop aptasensor for sensitive detection of bovine serum albumin or other targets in actual complicated samples.     

Performance monitoring of a mammalian cell based bioprocess using Raman spectroscopy

Being able to predict the final product yield at all stages in long-running, industrial, mammalian cell culture processes is vital for both operational efficiency, process consistency, and the implementation of quality by design (QbD) practices. Here we used Raman spectroscopy to monitor (in terms of glycoprotein yield prediction) a fed-batch fermentation from start to finish. Raman data were collected from 12 different time points in a Chinese hamster ovary (CHO) based manufacturing process and across 37 separate production runs. The samples comprised of clarified bioprocess broths extracted from the CHO cell based process with varying amounts of fresh and spent cell culture media. Competitive adaptive reweighted sampling (CoAdReS) and ant colony optimization (ACO) variable selection methods were used to enhance the predictive ability of the chemometric models by removing unnecessary spectral information. Using CoAdReS accurate prediction models (relative error of predictions between 2.1% and 3.3%) were built for the final glycoprotein yield at every stage of the bioprocess from small scale up to the final 5000 L bioreactor. This result reinforces our previous studies which indicate that media quality is one of the most significant factors determining the efficiency of industrial CHO-cell processes. This Raman based approach could thus be used to manage production in terms of selecting which small scale batches are progressed to large-scale manufacture, thus improving process efficiency significantly.     

Drying dissipative structures of the aqueous suspensions of monodisperse bentonite particles

Macroscopic and microscopic dissipative structural patterns formed in the course of drying the fractionated and monodisperse bentonite particles (plate-like in their shape) in aqueous deionized suspension and in the presence of NaCl have been studied on a cover glass. The patterns coexisted with the broad ring of the hill accumulated with the particles and with the round hills are formed around the outside edges of the film and in the center, respectively, in the macroscopic scale. By the addition of NaCl the pattern shifts from the broad ring to the round hill in the center. The spoke-like cracks, which have been observed for the suspensions of the spherical particles so often hitherto, are not observed at all for the bentonite suspensions. The characteristic convection flow of the particles and the interactions among the particles and substrate are important for the macroscopic pattern formation. Wrinkled, branch-like and/or star-like fractal patterns are observed in the microscopic scale. These patterns are determined mainly by the electrostatic and polar interactions between the particles and/or between the particle and the substrate in the course of drying.