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.     

Spectrophotometric resolution of ternary mixtures of pseudoephedrine hydrochloride, dextromethorphan hydrobromide, and sodium benzoate in syrups using wavelength selection by net analyte signals calculated with hybrid linear analysis

Hybrid linear analysis (HLA), as a recent factor-based multivariate calibration technique, was applied for the spectrophotometric determination of ternary mixtures of pseudoephedrine hydrochloride (PSU), dextromethorphan hydrobromide (DXT), and sodium benzoate (BNZ). The utilized HLA was assisted by a wavelength selection procedure which was based on the calculation of the net analyte signal (NAS) regression plot in any considered wavelengths window for each test sample, in addition to a moving window strategy for searching the region with maximum linearity of NAS regression plot (minimum error indicator (EI)). HLA was applied because it was simpler to adapt to the NAS regression plot methodology, and also used less factors than partial least squares (PLS). An orthogonal array design was applied for formation of calibration and prediction sets in the concentration ranges 0-7500 μmol L⁻¹ for PSU, 0-300 μmol L⁻¹ for DXT, and 0-1400 μmol L⁻¹ for BNZ. The method had the ability to select wavelength regions that minimize the effect of non-linearity of the spectral data, in addition to that of non-modeled interferences. The application of the selected wavelength regions improved the obtained relative standard error of predictions for PSU, DXT, and BNZ, respectively, from 5.24, 8.67, and 5.48% to 2.19, 5.21, and 3.62% (using lower number of factors). To check the ability of the proposed method in selection of linear regions of spectra, a test for detecting non-linear regions of spectral data in multivariate spectroscopic assays was also described. Additives in the commercial syrup samples did not interfere with their determinations. The method was successfully applied for the determination of pseudoephedrine HCl, dextromethorphan HBr, and sodium benzoate in cough suppressant syrup samples.     

Packings and stationary phases for biopolymer separations by HPLC

Summary Packings and stationary phases applied to high resolution separations of proteins, enzymes, and nucleic acids must satisfy a series of distinct criteria that are different from those usually required by HPLC of low molecular weight non-biologically active analytes. These requirements have been met through substantial improvements in classical gel media together with novel developments in silica supports, and have led to a family of products with tailor-made and reproducible properties. Supports consisting of cross-linked organic gels, and inorganic materials (mostly silicas) are now available with graduated particle sizes, pore sizes, porosities and surface areas as well as non-porous beads. A whole range of stationary phases, such as reversed phase, hydrophobic interaction, ion exchanger and affinity packings, were designed for application as chemical sensors for biopolymer recognition in adsorptive chromatography. The phase systems are operated in the gradient mode, giving high resolution and high peak capacities. In addition, aqueous liquid-liquid partitioning systems have been developed for the fractionation of proteins and nucleic acids. Size exclusion media complete the set of HPLC variants enabling a discrimination of proteins according to their size and shape in an isocratic elution mode. Basically, protein purification and isolation is a multistage process where-by the HPLC variants are combined in a logistic sequence, utilizing the different selectivities of the phase systems and thus maximising resolution, speed and throughput.     

一种新型极性脲丙基-C30固定相的制备和性能评价

以3-脲丙基三甲氧基硅烷为偶联剂，制备了一种新型极性脲丙基-C30（TPU-C30）反相色谱固定相。采用扫描电子显微镜、元素分析、红外光谱和热分析等对该固定相进行表征。结果表明，TPU-C30固定相已成功制备，连续制备3次固定相，其元素含量的相对偏差均小于5%，说明该合成工艺重复性良好。以不同极性、位置异构、碱性化合物为溶质探针，以传统的C18色谱柱与C30色谱柱为参比，对制备的固定相的色谱性能进行了研究。研究结果表明，TPU-C30固定相具有不同于传统C18柱、C30柱的选择性和更优的择形性，明显改善了碱性物质的峰形，其具有广阔的应用空间。     

南方红豆杉扦插繁殖技术研究Ⅱ.穗条对扦插生根率的影响

本文系统研究了南方红豆杉(Taxus chinensisvar.mairei)扦插育苗中穗条来源对生根率的效应。结果显示,采条母树龄、穗条年龄和穗条采自的树冠部位均对扦插生根率影响较大。本研究3年龄实生苗优于胸径10-20 cm的母树,后者又优于胸径30-40 cm的母树,胸径50 cm以上的最差,且差异显著。在母树龄和树冠部位一样的条件下,1年龄穗条的生根率显著高于2年龄穗条,树冠中部穗条优于上部,下部穗条生根率最低。采用3年龄实生苗为采条母树,并采集树冠中部的1年龄穗条,其最高生根率可达98.7%。研究结果为扦插繁殖中穗条的选择提供科学依据。     

不可能的可能--试论冰心和丁玲笔下的女性形象

冰心和丁玲两位女作家在现代新女性面对不可能的选择时作出各自的选择。冰心高扬“爱的旗帜”,表现“家”的温馨,歌颂“圣母”之爱;前期的丁玲展示女性的欲望和活泼的生命力,致力于与男性世界争一片天空。两位女作家对女性意识的不同回答,成为关于女性解放的极有代表性的两翼。     

基于克隆选择的粗糙集属性约简方法

基于免疫克隆选择的原理，提出了一种新的粗糙集属性约简方法，将属性集合的分类近似质量作为进化目标，利用免疫反应的分布性特点通过局部并行搜索实现全局优化，并采用抗体更新和亲和力抑制手段来维持群体的多样性，保证了各抗体局部优化解的稳定性，从而获得了多个优化约简集合，通过机械故障诊断数据的实例应用，表明该方法可以获得多个符合分类质量要求的属性约简集合，因此满足了设备故障诊断的特征优化选择要求。     

混合遗传算法求解0-1背包问题尝试

遗传算法是一种基于自然选择和遗传机制的搜索算法．为解决著名的0-1背包问题，尝试混合使用一点杂交与多点杂交以及将传统的算法与遗传算法相结合的方法，对经典遗传算法进行改进，并在实验中获得了更佳近似解．