Efficient Screening for Ternary Molecular Ionic Cocrystals Using a Complementary Mechanosynthesis and Computational Structure Prediction Approach

The discovery of molecular ionic cocrystals (ICCs) of active pharmaceutical ingredients (APIs) widens the opportunities for optimizing the physicochemical properties of APIs whilst facilitating the delivery of multiple therapeutic agents. However, ICCs are often observed serendipitously in crystallization screens and the factors dictating their crystallization are poorly understood. We demonstrate here that mechanochemical ball milling is a versatile technique for the reproducible synthesis of ternary molecular ICCs in less than 30 min of grinding with or without solvent. Computational crystal structure prediction (CSP) calculations have been performed on ternary molecular ICCs for the first time and the observed crystal structures of all the ICCs were correctly predicted. Periodic dispersion-corrected DFT calculations revealed that all the ICCs are thermodynamically stable (mean stabilization energy=−2 kJ mol⁻¹) relative to the crystallization of a physical mixture of the binary salt and acid. The results suggest that a combined mechanosynthesis and CSP approach could be used to target the synthesis of higher-order molecular ICCs with functional properties.     

Cheminformatics in MS-based environmental exposomics: Current achievements and future directions

Compound annotation using MS/MS data is the major bottleneck in interpretation of mass spectrometry data during non-targeted screening and suspect screening exposomics studies. Apart from compound identification using available databases or mass spectral libraries, the true challenge comes when completely new compounds have to be identified. Along with recent advances in MS instrumentation that set grounds to a new revolutionary age in environmental exposomics, a multitude of cheminformatics annotation approaches has been developed. Herein, we review the basic principles of the cutting-edge cheminformatics MS-based approaches employed in eco-exposome annotation.We give a solid background discussing the eco-exposome concept in relation to the advances in MS instrumentation, and define the three crucial cheminformatics tasks used in the eco-exposome annotation: molecular formula assignment, compound prioritization and compound annotation. The basic principles of compound annotation are discussed, which are based on three approaches of utilizing structural information inherent to MS data. These involve direct, indirect and joint annotation approaches. We assess their performance through the ability to annotate eco-exposome constituents. We discuss future perspectives and give directions to new annotation strategies and performance evaluation protocols aiming to solve current issues hampering the incorporation of cheminformatics annotation approaches in regular eco-exposome annotation workflows.     

Structure-based virtual screening of natural products as potential stearoyl-coenzyme a desaturase 1 (SCD1) inhibitors

Stearyl coenzyme A desaturase enzyme 1 (SCD1) is a key enzyme that catalyzes the conversion of saturated fatty acids (SFA) into monounsaturated fatty acids (MUFA) and plays a vital role in lipid metabolism of tumor cells. SCD1 is overexpressed in a variety of malignant tumors, and its related inhibitors showed significant anti-tumor activity in vitro and in vivo experiments, which is a new target for tumor therapy. The focus of this study is to identify novel SCD1 inhibitors from natural products through computer simulations. First, 176,602 compounds from natural product databases were virtually screened. By molecular dynamics (MD) simulations, the ligand-protein interactions of 5 compounds with high docking manifestation were analyzed accurately. Then, MM-GBSA and MM-PBMA methods were used to verify the results. Finally, ADMET prediction was performed for the 5 compounds. As a result, two natural products with potential inhibition towards SCD1 were identified, which had the excellent docking manifestation, binding mode within SCD1 pocket and stability during molecular dynamics simulation. This study provides a meaningful model for the development and optimization of new inhibitors and anti-tumor drugs targeting SCD1.     

Linked drug-drug conjugates based on triterpene and phenol structures. Rational synthesis,molecular properties,toxicity and bioactivity prediction

One of the tasks of modern medicinal chemistry is to produce new molecules that have interesting and desired biological effects. In addition, the synthetic procedure for obtaining these compounds should be at least partially smart and rational e.g. “Lego” and green approaches. The study focuses on the synthesis of several hybrid type compounds that are expected to be characterized by beneficial bioactivities. In order to hybridize natural triterpene oleanolic acid and phenol structures, the linker-mode concept was selected. The synthetic goal was achieved in two stages. The first concerns the rapid introduction of the halogenoacidic linker to active phenols selected as a result of microwave-ultrasonic (MW-US) assisted O-alkylation with the use of 2-halogenoacetic acid. The next stage of the synthetic studies involves the reaction of phenoxyacetic acid derivatives obtained containing an active carboxylic group with oleanolic acid/oxime units by the methods typical of triterpene chemistry. Novel linked ester- and iminoester-type triterpene derivatives with phenols (thymol, eugenol, paracetamol, nipagins, naphthols, curcumin and genistein) were obtained and characterized. Additionally, based on the analysis of numerous references and selected methods of computational chemistry (Molinspiration Cheminformatics, Osiris Property Explorer and PASS method) the molecular parameters and the preliminary anti-inflammatory and antinociceptive activity characterising these molecules as potential drugs were calculated and predicted.     

开式轴流风扇气动噪声预测

本文采用LES/FW-H的匹配方法,研究了开式轴流风扇内部旋涡流动特征及其与叶片表面干涉引起的气动噪声之间的联系,同时进行了远场噪声预测,探讨了叶轮不同表面辐射噪声时的频谱分布特征.研究结果表明,开式轴流风扇吸力面附近形成的叶尖涡和前缘分离涡在吸力面叶片表面相应位置形成大压力波动,形成主要噪声源;叶片吸力面的辐射噪声可以通过改善吸力面附近的旋涡流动来降低;低速轴流叶轮由叶轮壁面辐射的噪声以宽频成分为主.     

A Hybrid Method Using HAVOK Analysis and Machine Learning for Predicting Chaotic Time Series

The prediction of chaotic time series systems has remained a challenging problem in recent decades. A hybrid method using Hankel Alternative View Of Koopman (HAVOK) analysis and machine learning (HAVOK-ML) is developed to predict chaotic time series. HAVOK-ML simulates the time series by reconstructing a closed linear model so as to achieve the purpose of prediction. It decomposes chaotic dynamics into intermittently forced linear systems by HAVOK analysis and estimates the external intermittently forcing term using machine learning. The prediction performance evaluations confirm that the proposed method has superior forecasting skills compared with existing prediction methods.     

半色调荧光图像的光谱反射与透射模型

荧光油墨半色调印刷品的显色预测规律是彩色成像领域内十分关键的课题。把荧光半色调印刷品反射出来的光分成两个独立的部分,即由最初入射光组成的主光流和由于吸收了主光流而产生的荧光流;并且采用了一个指数矩阵来描述墨层产生的荧光光强,从而得出了荧光半色调图像色彩的光反射规律。考虑到入射光中从一种颜色油墨入射后再由同色油墨出射的概率要比从其它色油墨出射的概率要大的事实,讨论中引入权重因子描述从同色油墨出射部分与从整个表面出射部分比例不同的现象,建立了荧光油墨半色调图像的Clapper-Yule新光谱反射率模型。     

线型优化最大熵线性预测方法自回归模型三种求解方法的比较

采用三种方法：修正协方差法MCOV(Modified Covariance Method)、递推极大似然估计法RMLE(Recursive Maximum Likelihood Estimator)和伯格法(Burg Method)求解线型优化最大熵线性预测方法中的自回归模型系数,并且在不同求解方法情况下,将阶次、信噪比对光谱复原的影响作了详尽的比较.研究结果表明:在线型优化最大熵线性预测方法的自回归模型系数三种求解方法中,修正协方差法要优于递推极大似然估计法和伯格法.     

电拓扑状态预测有机磷酸酯类化合物的气相色谱保留指数

以原子类型电拓扑状态指数(ETSI)有效表征35个有机磷酸酯类化合物(OP)的分子结构, 应用基于预测的变量选择与模型化(VSMP)方法建立OP化合物在3种不同固定相上的气相色谱保留指数(RI)与分子结构(ETSI)的定量相关模型. 结果表明, 影响不同固定相上OP色谱保留的主要结构因素都是由7个ETSI描述子对应的子结构碎片, 即: ＝CH₂,≡C—, aaC—, ＝O, —O—, Cl和Br. 其中子结构aaC—, ＝O和—O与OP化合物母体骨架密切相关, 而＝CH₂,≡C—, —Cl和—Br反映支链或取代基的变化. 通过多元线性回归法建立OP化合物在三个固定相上的定量结构-保留相关模型(QSRR)发现, 各QSAR模型的估计相关系数均在0.99以上, LOO检验相关系数在0.98以上, 表明模型具有良好估计能力与稳定性. 应用28个OP训练集样本构建的QSRR模型预测外部7个检验集RI结果表明训练集模型具有良好预测能力.