Heterocyclic Substitutions Greatly Improve Affinity and Stability of Folic Acid towards FRα. an In Silico Insight

Folate receptor alpha (FRα) is known as a biological marker for many cancers due to its overexpression in cancerous epithelial tissue. The folic acid (FA) binding affinity to the FRα active site provides a basis for designing more specific targets for FRα. Heterocyclic rings have been shown to interact with many receptors and are important to the metabolism and biological processes within the body. Nineteen FA analogs with substitution with various heterocyclic rings were designed to have higher affinity toward FRα. Molecular docking was used to study the binding affinity of designed analogs compared to FA, methotrexate (MTX), and pemetrexed (PTX). Out of 19 FA analogs, analogs with a tetrazole ring (FOL03) and benzothiophene ring (FOL08) showed the most negative binding energy and were able to interact with ASP81 and SER174 through hydrogen bonds and hydrophobic interactions with amino acids of the active site. Hence, 100 ns molecular dynamics (MD) simulations were carried out for FOL03, FOL08 compared to FA, MTX, and PTX. The root mean square deviation (RMSD) and root mean square fluctuation (RMSF) of FOL03 and FOL08 showed an apparent convergence similar to that of FA, and both of them entered the binding pocket (active site) from the pteridine part, while the glutamic part was stuck at the FRα pocket entrance during the MD simulations. Molecular mechanics Poisson-Boltzmann surface accessible (MM-PBSA) and H-bond analysis revealed that FOL03 and FOL08 created more negative free binding and electrostatic energy compared to FA and PTX, and both formed stronger H-bond interactions with ASP81 than FA with excellent H-bond profiles that led them to become bound tightly in the pocket. In addition, pocket volume calculations showed that the volumes of active site for FOL03 and FOL08 inside the FRα pocket were smaller than the FA–FRα system, indicating strong interactions between the protein active site residues with these new FA analogs compared to FA during the MD simulations.     

基于改进免疫遗传算法的近红外光谱变量选择方法

该文在免疫遗传算法（IGA）的基础上,提出一种改进免疫遗传算法（iIGA）用于近红外光谱波长变量的选择。该算法舍去了原算法中固定抗体相似度阈值的思想,取而代之的是抗体相似度阈值自适应,同时引入精英保留策略和贪心算法思想,使得算法朝着正确的方向进行局部性探优。将该算法在玉米的淀粉和蛋白质含量数据集上进行实验测试,建立偏最小二乘（PLS）分析模型,并与IGA、遗传算法（GA）以及全谱方法进行了对比。结果表明,在玉米淀粉含量的预测上,iIGA相较于原IGA算法,预测集均方根误差（RMSEP）从0.312 0降至0.298 0,预测集预测精度提升4.5%;在玉米蛋白质含量的预测上,RMSEP从0.124 4降至0.110 3,预测集预测精度提升11.3%。分别对预测淀粉和蛋白质模型的RMSEP值进行显著性检验,F值分别为165.22和182.05,P值分别为9.5 × 10－23和4.5 × 10－24,P值均小于0.05,因此,iIGA能显著提升模型预测精度。     

A simulation method of aircraft plumes for real-time imaging

Real-time infrared simulation technology can provide a large number of infrared images under different conditions to support the design, test and evaluation of a system having infrared imaging equipment with very low costs. By synthesizing heat transfer, infrared physics, fluid mechanics and computer graphics, a real-time infrared simulation method is proposed based on the method of characteristics to predict the infrared feature of aircraft plumes, which tries to obtain a good balance between simulation precision and computation efficiency. The temperature and pressure distribution in the under-expansion status can be rapidly solved with dynamically changing flight statuses and engine working states. And a modified C–G (Curtis–Godson) spectral band model that combines the plume streamlines with the conventional C–G spectral band model was implemented to calculate the non-uniformly distributed radiation parameters inside a plume field. The simulation result was analyzed and compared with the CFD++, which validates the credibility and efficiency of the proposed simulation method.     

Biselective refocusing pulses and the SERF experiment

The SERF experiment is a variant of the homonuclear J-resolved experiment, in which a single coupling constant is measured. It consists of a single chemical shift selective excitation that is followed by a biselective spin echo. Recent articles mention the existence of artefacts in SERF spectra that are supposedly related to pulse imperfections. This article presents a detailed study of the biselective refocusing pulses. It also reports a method for predicting the position and amplitude of the expected and unexpected 2D spectral peaks in SERF spectra. Artefacts can be partially eliminated by phase cycling or by the introduction of static field gradient pulses in the acquisition sequence. A procedure to obtain of pure absorption peaks in SERF spectra is proposed.     

Inherent Ethyl Acetate Selectivity in a Trianglimine Molecular Solid

Ethyl acetate is an important chemical raw material and solvent. It is also a key volatile organic compound in the brewing industry and a marker for lung cancer. Materials that are highly selective toward ethyl acetate are needed for its separation and detection. Here, we report a trianglimine macrocycle ( TAMC ) that selectively adsorbs ethyl acetate by forming a solvate. Crystal structure prediction showed this to be the lowest energy solvate structure available. This solvate leaves a metastable, “templated” cavity after solvent removal. Adsorption and breakthrough experiments confirmed that TAMC has adequate adsorption kinetics to separate ethyl acetate from azeotropic mixtures with ethanol, which is a challenging and energy-intensive industrial separation.     

面向数据挖掘的静态电源综合故障诊断研究

静态电源是机场桥载设备最重要的组成部件之一,应用非常广泛。然而,其产生的频发故障会造成设备利用率低、修复率时长和经济损失等问题,在基于桥载设备的安监系统上,提出了静态电源综合故障诊断方法,通过数据挖掘软件,建立了静态电源故障诊断预测模型。通过在线数据库测试结果表明得到了综合故障诊断方法在预测静态电源故障上显现的特点,得到了静态电源的未来状态,实现了对静态电源的实时故障进行预测,进而为解决故障提供方向和目标,最终达到降低经济损失最大化的目的。     

Predicting New Ugi–Smiles Couplings: A Combined Experimental and Theoretical Study

Following our previous mechanistic studies of multicomponent Ugi‐type reactions, theoretical calculations have been performed to predict the efficiency of new substrates in Ugi–Smiles couplings. First, as predicted, 2,4,6‐trichlorophenol experimentally gave the corresponding aryl‐imidate. Theoretical predictions of nitrosophenols as good acidic partners were then successfully confirmed by experiments. In the latter case, the reaction offers a new access to benzimidazoles.     

Predicting Regioselectivity in Radical C−H Functionalization of Heterocycles through Machine Learning

Radical C−H bond functionalization provides a versatile approach for elaborating heterocyclic compounds. The synthetic design of this transformation relies heavily on the knowledge of regioselectivity, while a quantified and efficient regioselectivity prediction approach is still elusive. Herein, we report the feasibility of using a machine learning model to predict the transition state barrier from the computed properties of isolated reactants. This enables rapid and reliable regioselectivity prediction for radical C−H bond functionalization of heterocycles. The Random Forest model with physical organic features achieved 94.2 % site accuracy and 89.9 % selectivity accuracy in the out-of-sample test set. The prediction performance was further validated by comparing the machine learning results with additional substituents, heteroarene scaffolds and experimental observations. This work revealed that the combination of mechanism-based computational statistics and machine learning model can serve as a useful strategy for selectivity prediction of organic transformations.     

Exploring the Limits of Transition-Metal Fluorination at High Pressures

Fluorination is a proven method for challenging the limits of chemistry, both structurally and electronically. Here we explore computationally how pressures below 300 GPa affect the fluorination of several transition metals. A plethora of new structural phases are predicted along with the possibility for synthesizing four unobserved compounds: TcF₇, CdF₃, OsF₈, and IrF₈. The Ir and Os octaflourides are both predicted to be stable as quasi-molecular phases with an unusual cubic ligand coordination, and both compounds formally correspond to a high oxidation state of +8. Electronic-structure analysis reveals that otherwise unoccupied 6p levels are brought down in energy by the combined effects of pressure and a strong ligand field. The valence expansion of Os and Ir enables ligand-to-metal F 2p→M 6p charge transfer that strengthens M−F bonds and decreases the overall bond polarity. The lower stability of IrF₈, and the instability of PtF₈ and several other compounds below 300 GPa, is explained by the occupation of M−F antibonding orbitals in octafluorides with a metal-valence-electron count exceeding 8.     

A refined numerical model for determining inflation-burst behavior of composite membrane structures

The airship structures made of multi-layer composite fabrics or membranes can offer the platform for earth observations, wireless communications and space research due to light weight and good mechanical performance. The structural safety and serviceability strongly depend on material properties and working conditions. Available studies are limited within service stress limits or are lack of suitable biaxial tensile constitutive models for understanding structural behavior. This paper thus focuses on a refined numerical model for determining inflation-burst behavior of composite airship structures considering new biaxial constitutive equations, novel failure criteria and manufacture factors.The differences between ideal and real forms of airship structures, e.g. volume difference, demonstrate the necessity for incorporating cutting-pattern effects in the initial numerical model. For structural analysis, stress distributions on real structural forms are different from those on ideal forms because of welding parts that can enhance local stiffness. The ultimate pressures are 56.7 kPa and 59.5 kPa for ideal and real structural forms. Structural breaking initiated at the maximum diameter of ideal structural forms propagates fast while welding parts can prevent breaking propagation for real structural forms. Therefore, the refined numerical model can reveal basic structural behavior and safety performance of airship structures in the inflation-burst processes.