Alcohols,ethers, carbohydrates,and related compounds. II. The anomeric effect

The anomeric effect has been studied for a variety of compounds using the MM4 force field, and also using MP2/6-311++G(2d,2p) ab initio calculations and experimental data for reference purposes. Geometries and energies, including conformational, rotational barriers, and heats of formation were examined. Overall, the agreement of MM4 with the experimental and ab initio data is good, and significantly better than the agreement obtained with the MM3 force field. The anomeric effect is represented in MM4 by various explicit terms in the force constant matrix. The bond length changes are accounted for with torsion-stretch elements. The angle changes are accounted for with torsion-bend elements. The energies are taken into account with a number of torsional terms in the usual way. A torsion-torsion interaction is also of some importance. With all of these elements included in the calculation, the MM4 results now appear to be adequately accurate. The heats of formation were examined for a total of 12 anomeric compounds, and the experimental values were fit by MM4 with an RMS error of 0.42 kcal/mol.     

交叉分段差分进化支持向量回归的气体超声 流量计测量方法

为了进一步提高全量程气体超声流量计的测量精度,基于多通道声波到时和实时温度,提出了一种交叉分段差分进化(Differential Evolution)支持向量回归(Support Vector Regression)DE-SVR模型。考虑到气体在不同流量条件下的流体状态不同,提出了交叉分段处理的方法,采用DE算法优化选取SVR参数。实验结果表明,对于16~1600m3/h全量程,交叉分段DE-SVR和传统积分方法计算气体流量的平均相对误差分别为0.00447和0.02781,前者较后者降低了83.93%;对于16~160m3/h小流量,交叉分段DE-SVR和无分段DE-SVR算法计算结果平均相对误差分别为0.00436和0.03214,前者较后者降低了86.43%。该方法有效避免了声道长度、探头角度以及管道直径等参数不确定性对流量计算的影响,为全量程气体流量的高精度测量提供了保障。     

An Algorithm Framework for Drug-Induced Liver Injury Prediction Based on Genetic Algorithm and Ensemble Learning

In the process of drug discovery, drug-induced liver injury (DILI) is still an active research field and is one of the most common and important issues in toxicity evaluation research. It directly leads to the high wear attrition of the drug. At present, there are a variety of computer algorithms based on molecular representations to predict DILI. It is found that a single molecular representation method is insufficient to complete the task of toxicity prediction, and multiple molecular fingerprint fusion methods have been used as model input. In order to solve the problem of high dimensional and unbalanced DILI prediction data, this paper integrates existing datasets and designs a new algorithm framework, Rotation-Ensemble-GA (R-E-GA). The main idea is to find a feature subset with better predictive performance after rotating the fusion vector of high-dimensional molecular representation in the feature space. Then, an Adaboost-type ensemble learning method is integrated into R-E-GA to improve the prediction accuracy. The experimental results show that the performance of R-E-GA is better than other state-of-art algorithms including ensemble learning-based and graph neural network-based methods. Through five-fold cross-validation, the R-E-GA obtains an ACC of 0.77, an F1 score of 0.769, and an AUC of 0.842.     

Virtual Screening and Hit Selection of Natural Compounds as Acetylcholinesterase Inhibitors

Acetylcholinesterase (AChE) is one of the classical targets in the treatment of Alzheimer’s disease (AD). Inhibition of AChE slows down the hydrolysis of acetycholine and increases choline levels, improving the cognitive function. The achieved success of plant-based natural drugs acting as AChE inhibitors, such as galantamine (GAL) from Galanthus genus and huperzine A from Huperzia serrate (approved drug in China), in the treatment of AD, and the fact that natural compounds (NCs) are considered as safer and less toxic compared to synthetic drugs, led us to screen the available NCs (almost 150,000) in the ZINC12 database for AChE inhibitory activity. The compounds were screened virtually by molecular docking, filtered for suitable ADME properties, and 32 ligands from 23 structural groups were selected. The stability of the complexes was estimated via 1 μs molecular dynamics simulation. Ten compounds formed stable complexes with the enzyme and had a vendor and a reasonable price per mg. They were tested for AChE inhibitory and antioxidant activity. Five compounds showed weak AChE inhibition and three of them exhibited high antioxidant activity.     

Chemical and Pharmacological Profiling of Wrightia coccinea (Roxb. Ex Hornem.) Sims Focusing Antioxidant,Cytotoxic, Antidiarrheal,Hypoglycemic, and Analgesic Properties

The aim of the study was to conduct phytochemical and pharmacological investigations of Wrightia coccinea (Roxb. ex Hornem.) Sims via several in vitro, in vivo, and in silico models. A total of four compounds were identified and isolated from the methanol extract of the bark and the methanol extract of the seed pulp of W. coccinea through successive chromatographic techniques and were characterized as 3β-acetyloxy-olean-12-en-28-ol (1), wrightiadione (2), 22β-hydroxylupeol (3), and β-sitosterol (4) by spectroscopic analysis. The aqueous fraction of the bark and chloroform fraction of the fruits provided the most potent antioxidant capacity (IC₅₀ = 7.22 and 4.5 µg/mL, respectively) in DPPH free radical scavenging assay compared with the standard ascorbic acid (IC₅₀ = 17.45 µg/mL). The methanol bark extract and the methanol fruit coat extract exerted anti-diarrheal activity by inhibiting 74.55 ± 0.67% and 77.78 ± 1.5% (mean ± SEM) of the diarrheal episode in mice, respectively, after four hours of loading the samples. In the hypoglycemic test, the methanol bark extract and the methanol fruit coat extract (400 mg/kg) produced a significant (p < 0.05) reduction in the blood glucose level in mice. Both doses of the plant extracts (200 mg/kg and 400 mg/kg) used in the study induced a significant (p < 0.05) increase in pain reaction time. The in vitro and in vivo findings were supported by the computational studies. The isolated compounds exhibited higher binding affinity compared with the standard drugs towards the active binding sites of glutathione reductase, epidermal growth factor receptor (EGFR), kappa opioid receptor, glucose transporter 3 (GLUT 3), Mu opioid receptor, and cyclooxygenase 2 (COX-2) proteins due to their potent antioxidant, cytotoxic, anti-diarrheal, hypoglycemic, and central and peripheral analgesic properties, respectively. The current findings concluded that W. coccinea might be a potential natural source for managing oxidative stress, diarrhea, hyperglycemia, and pain. Further studies are warranted for extensively phytochemical screening and establishing exact mechanisms of action.     

Investigation Driven by Network Pharmacology on Potential Components and Mechanism of DGS,a Natural Vasoprotective Combination,for the Phytotherapy of Coronary Artery Disease

Phytotherapy offers obvious advantages in the intervention of Coronary Artery Disease (CAD), but it is difficult to clarify the working mechanisms of the medicinal materials it uses. DGS is a natural vasoprotective combination that was screened out in our previous research, yet its potential components and mechanisms are unknown. Therefore, in this study, HPLC-MS and network pharmacology were employed to identify the active components and key signaling pathways of DGS. Transgenic zebrafish and HUVECs cell assays were used to evaluate the effectiveness of DGS. A total of 37 potentially active compounds were identified that interacted with 112 potential targets of CAD. Furthermore, PI3K-Akt, MAPK, relaxin, VEGF, and other signal pathways were determined to be the most promising DGS-mediated pathways. NO kit, ELISA, and Western blot results showed that DGS significantly promoted NO and VEGFA secretion via the upregulation of VEGFR2 expression and the phosphorylation of Akt, Erk1/2, and eNOS to cause angiogenesis and vasodilation. The result of dynamics molecular docking indicated that Salvianolic acid C may be a key active component of DGS in the treatment of CAD. In conclusion, this study has shed light on the network molecular mechanism of DGS for the intervention of CAD using a network pharmacology-driven strategy for the first time to aid in the intervention of CAD.     

Insights into the Allosteric Effect of SENP1 Q597A Mutation on the Hydrolytic Reaction of SUMO1 via an Integrated Computational Study

Small ubiquitin-related modifier (SUMO)-specific protease 1 (SENP1) is a cysteine protease that catalyzes the cleavage of the C-terminus of SUMO1 for the processing of SUMO precursors and deSUMOylation of target proteins. SENP1 is considered to be a promising target for the treatment of hepatocellular carcinoma (HCC) and prostate cancer. SENP1 Gln597 is located at the unstructured loop connecting the helices α4 to α5. The Q597A mutation of SENP1 allosterically disrupts the hydrolytic reaction of SUMO1 through an unknown mechanism. Here, extensive multiple replicates of microsecond molecular dynamics (MD) simulations, coupled with principal component analysis, dynamic cross-correlation analysis, community network analysis, and binding free energy calculations, were performed to elucidate the detailed mechanism. Our MD simulations showed that the Q597A mutation induced marked dynamic conformational changes in SENP1, especially in the unstructured loop connecting the helices α4 to α5 which the mutation site occupies. Moreover, the Q597A mutation caused conformational changes to catalytic Cys603 and His533 at the active site, which might impair the catalytic activity of SENP1 in processing SUMO1. Moreover, binding free energy calculations revealed that the Q597A mutation had a minor effect on the binding affinity of SUMO1 to SENP1. Together, these results may broaden our understanding of the allosteric modulation of the SENP1−SUMO1 complex.     

物理科学发展史的回顾与聚集力学的创建

本文简单地阐述了物理科学的发展电,在19世纪末期,物珲科学已经有相当发展,并形成了三个科学分支--研究物体运动,有牛顿力学;研究物质热运动,有热力学和统计力学;研究电磁波和光波,有电动力学,可是,这三种经典力学在20世纪初面临着新的挑战(困难),从而,相应地产生了三种新的基础理论,即狭义相对论,广义相对论;聚集理论,聚集力学;量子理论,量子力学,具体实践表明,它们在解决新的难题方面都取得很大成功.     

香烟燃烧产生的亚微米颗粒物动态粒径谱特征

应用SMPS (Scanning Mobility Particle Sizer)对ETS (Environmental Tobacco Smoke)亚微米颗粒物的粒径谱演变进行了测量分析.结果发现,ETS颗粒物在10~500nm范围内呈对数正态单峰分布,数量粒径谱和质量粒径谱的演化有类似的递减趋势,但其浓度衰减率有明显的不同.分析得知,由于在演化过程中颗粒物直径是动态变化的,并不能用简单的方法获得凝并和沉积损失率.