药物化学中构效关系的教学方法研究

构效关系是先导化合物修饰、新型药物设计的基础,在药物化学教学中具有至关重要的作用.由于其多样性和复杂性,学生的掌握情况不理想.本文针对这一问题对药物的构效关系进行归纳分类,总结为"三部分一核心多构型"三类,每一类都进行举例讲解,为学生更好地理解与掌握药物化学的构效关系提供一种可行的方式.     

Novel Tdp1 Inhibitors Based on Adamantane Connected with Monoterpene Moieties via Heterocyclic Fragments

Tyrosyl-DNA phosphodiesterase 1 (Tdp1) is a promising target for anticancer therapy due to its ability to counter the effects topoisomerase 1 (Top1) poison, such as topotecan, thus, decreasing their efficacy. Compounds containing adamantane and monoterpenoid residues connected via 1,2,4-triazole or 1,3,4-thiadiazole linkers were synthesized and tested against Tdp1. All the derivatives exhibited inhibition at low micromolar or nanomolar concentrations with the most potent inhibitors having IC₅₀ values in the 0.35–0.57 µM range. The cytotoxicity was determined in the HeLa, HCT-116 and SW837 cancer cell lines; moderate CC₅₀ (µM) values were seen from the mid-teens to no effect at 100 µM. Furthermore, citral derivative 20c, α-pinene-derived compounds 20f, 20g and 25c, and the citronellic acid derivative 25b were found to have a sensitizing effect in conjunction with topotecan in the HeLa cervical cancer and colon adenocarcinoma HCT-116 cell lines. The ligands are predicted to bind in the catalytic pocket of Tdp1 and have favorable physicochemical properties for further development as a potential adjunct therapy with Top1 poisons.     

Heterocyclic compounds as antiviral drugs: Synthesis,structure–activity relationship and traditional applications

A virus outbreak challenges the economic, medical, and public health infrastructure worldwide. More than one virus capable of triggering diseases have been identified per year since 1972, which requires the development of new ways of treatment and prevention, however, such processes are not rapid and easy. With the pandemic scenario experienced since early 2020, several drugs with well-known purposes have gained prominence, due to speculation of their use in the treatment against the new coronavirus. Among the main drugs studied, the vast majority contain a heterocyclic structure. In this review, we presented the traditional and efficient synthesis of 15 drugs that have been studied for the COVID-19 treatment, containing in their structure heterocycles like indole, quinoline, pyrimidone, tetrahydrofuran, pyrrolidine, triazole, pyridazine, pyrazole, pyrrolopyrimidine, azetidine, pyrrolotriazine, pyrazine, tetrahydropyran, benzofuran, spiroketal, and thiazole. Furthermore, we have shown the original applications, as well as their structure–activity relationship and what is their situation as a drug candidate against COVID-19. Thus, the objective was to consolidate the main synthetic and pharmacological aspects involving clinically developed heterocycles that at some point were presented as promising against SARS-CoV-2.     

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.     

Physicochemical and Graph Theoretical Descriptors in Developmental Toxicity SAR: A Comparative Study

Abstract

Chemical insults to the developing fetus can lead to growth retardation, malformation, death, and functional deficits. The present study seeks to determine if physicochemical and/or graph theoretical parameters can be used to determine a structure-activity relationship (SAR) for developmental toxicity, and if consistency is observed among the selected features. The biological data utilized consists of a diverse series of compounds evaluated within the Chernoff-Kavlock in vivo mouse assay. Physicochemical parameters calculated correspond to electronic, steric, and transport properties. Graph theoretical parameters calculated include the simple, valence, and kappa indices. Both sets of parameters were independently applied to derive SARs in order to compare the quality of the respective models. Multiple random sampling, without replacement, was utilized to obtain ten training/test partitions. Models were built by linear discriminant analysis, decision trees, and neural networks respectively. Comparisons on identical sets of data were carried out to determine if any of the model building procedures had a significant advantage in terms of predictive performance. Furthermore, comparison of the features selected within and across the model building processes led to the determination of model consistency. Our results indicate that consistent features related to developmental toxicity are observed and that both physicochemical and graph theoretical parameters have equal utility.     

New chemical constituents from the Piper betle Linn. (Piperaceae)

The phytochemical investigation of chloroform extract from Piper betle var. haldia, Piperaceae, leaves has resulted in the isolation of two new chemical constituents which were identified as 1-n-dodecanyloxy resorcinol (H1) and desmethylenesqualenyl deoxy-cepharadione-A (H4), on the basis of spectroscopic data 1D NMR (¹H and ¹³C) and 2D NMR (¹H-¹H COSY and HMBC) as well as ESI-MS, FT-IR and HR-ESI-MS analyses. Compounds H1 and H4 showed excellent antioxidant DPPH free radical scavenging activity with IC₅₀ values of 7.14 μg/mL and 8.08 μg/mL compared to ascorbic acid as a standard antioxidant drug with IC₅₀ value of 2.52 μg/mL, respectively. Evaluation of cytotoxic activity against human hepatoma cell line (PLC-PRF-5) showed moderate effect with the GI₅₀ values of 35.12 μg/mL for H1, 31.01 μg/mL for H4, compared to Doxorubicin^® as a standard cytotoxic drug with GI₅₀ value of 18.80 μg/mL.     

基于幅度统计多分辨率分析的SAR图像灰度压缩

基于幅度统计多分辨率分析的原理，针对SAR图像特殊的显示要求，提出了一种新的灰度压缩方法，解决了常规灰度级压缩方法不能很好保持原始图像数据直方图分布的问题，实验结果表明该方法能有效保证灰度压缩前后图像数据直方图分布形状的一致性，较好地保持原始图像的视觉特征。     

INS／GPS／SAR组合系统白噪声误差特性的在线随机加权估计

首次把随机加权估计这一新兴的统计计算方法应用于导航系统的研究,证明用它进行INS/GPS/SAR组合系统误差特性的估计是可行的,仿真实验和计算结果表明,该方法明显地优于其它传统的统计估计方法。     

Multi-sensors SAR system for real-time dosimetry assessment

A multi-sensor test-bench for determining the SAR (specific absorption rate) due to wireless devices emitting in equivalent human tissues is presented. Real-time SAR assessment is proposed considering a spatially distributed multiprobe test-bench. In comparison with a multi-axial robot SAR system, the proposed one does not require any displacement, thus reducing drastically acquisition time, once parallel data acquisition and interpolation techniques are employed for accelerating measurements.