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ACS Combinatorial Science: January, 1999–December, 2020 ACS组合科学:1999年1月- 2020年12月
IF 3.784 3区 化学 Q1 Chemistry Pub Date : 2020-12-14 DOI: 10.1021/acscombsci.0c00181
M. G. Finn*
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引用次数: 0
Aldol Reactions of Biorenewable Triacetic Acid Lactone Precursor Evaluated Using Desorption Electrospray Ionization Mass Spectrometry High-Throughput Experimentation and Validated by Continuous Flow Synthesis 生物可再生三乙酸内酯前体醛醇反应的解吸电喷雾质谱高通量实验及连续流合成验证
IF 3.784 3区 化学 Q1 Chemistry Pub Date : 2020-11-19 DOI: 10.1021/acscombsci.0c00119
H. Samuel Ewan, Shruti A. Biyani, Jaycie DiDomenico, David Logsdon, Tiago J. P. Sobreira, Larisa Avramova, R. Graham Cooks, David H. Thompson*

Desorption electrospray ionization-mass spectrometry (DESI-MS) was used as a high-throughput experimentation (HTE) tool to rapidly identify derivatives of the biobased platform molecule triacetic acid lactone (TAL). TAL is a platform molecule capable of conversion to a wide range of useful commodity chemicals, agrochemicals, and advanced pharmaceutical intermediates. In the present study, a diverse family of aldol reaction mixtures were prepared in high-density microtiter plates with a liquid handling robot, then printed with a pin tool onto a PTFE surface for analysis by DESI-MS. Our DESI-MS results indicate that aldol products of TAL were obtained for each substrate tested, in good agreement with previously reported TAL reactivity. These HTE experiments also revealed solvent-dependent reactivity trends that facilitated reaction scale up. Our findings suggest that DESI-MS analysis can rapidly inform the selection of optimal reaction conditions from a wide variety of conditions for scale up using continuous synthesis conditions.

采用解吸电喷雾质谱(DESI-MS)作为高通量实验(HTE)工具,快速鉴定生物基平台分子三乙酸内酯(TAL)的衍生物。TAL是一种平台分子,能够转化为各种有用的商品化学品,农用化学品和先进的医药中间体。在本研究中,利用液体处理机器人在高密度微量滴度板上制备了多种醛醇反应混合物,然后用pin工具打印到聚四氟乙烯表面上进行DESI-MS分析。我们的DESI-MS结果表明,每种底物都得到了TAL的醛醇产物,与先前报道的TAL反应性很好地一致。这些HTE实验还揭示了溶剂依赖的反应性趋势,促进了反应规模的扩大。我们的研究结果表明,DESI-MS分析可以快速地从各种条件中选择最佳反应条件,以便使用连续合成条件扩大规模。
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引用次数: 5
Fe3O4@[email protected]: A Magnetic Metal–Organic Framework as a Recoverable Catalyst for the Hydration of Nitriles and Reduction of Isothiocyanates, Isocyanates, and Isocyanides Fe3O4@[email protected]:一种磁性金属-有机骨架作为可回收催化剂用于硝基水化和还原异硫氰酸酯、异氰酸酯和异氰酸酯
IF 3.784 3区 化学 Q1 Chemistry Pub Date : 2020-11-13 DOI: 10.1021/acscombsci.0c00178
Arash Ghorbani-Choghamarani*, Zahra Taherinia*

A novel magnetic metal–organic framework (Fe3O4@[email?protected]) has been prepared and characterized by spectroscopic, microscopic, and magnetic techniques. This magnetically separable catalyst exhibited high catalytic activity for nitrile hydration and the ability to reduce isothiocyanates, isocyanates, and isocyanides with excellent activity and selectivity without any additional reducing agent.

制备了一种新型磁性金属有机骨架(Fe3O4@[email?protected]),并通过光谱、微观和磁性技术对其进行了表征。该磁性可分离催化剂对丁腈水化具有较高的催化活性,并具有还原异硫氰酸酯、异氰酸酯和异氰酸酯的能力,具有优异的活性和选择性,无需任何额外的还原剂。
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引用次数: 10
Expanding the Chemical Diversity of Genetically Encoded Libraries 扩大基因编码文库的化学多样性
IF 3.784 3区 化学 Q1 Chemistry Pub Date : 2020-11-09 DOI: 10.1021/acscombsci.0c00179
Sabrina E. Iskandar, Victoria A. Haberman, Albert A. Bowers*

The power of ribosomes has increasingly been harnessed for the synthesis and selection of molecular libraries. Technologies, such as phage display, yeast display, and mRNA display, effectively couple genotype to phenotype for the molecular evolution of high affinity epitopes for many therapeutic targets. Genetic code expansion is central to the success of these technologies, allowing researchers to surpass the intrinsic capabilities of the ribosome and access new, genetically encoded materials for these selections. Here, we review techniques for the chemical expansion of genetically encoded libraries, their abilities and limits, and opportunities for further development. Importantly, we also discuss methods and metrics used to assess the efficiency of modification and library diversity with these new techniques.

核糖体的功能越来越多地用于分子文库的合成和选择。噬菌体展示、酵母展示和mRNA展示等技术有效地将基因型与表型相结合,从而为许多治疗靶点提供高亲和力表位的分子进化。遗传密码扩展是这些技术成功的核心,使研究人员能够超越核糖体的内在能力,并获得用于这些选择的新的遗传编码材料。在此,我们回顾了化学扩增基因编码文库的技术,它们的能力和局限性,以及进一步发展的机会。重要的是,我们还讨论了使用这些新技术评估修改效率和文库多样性的方法和指标。
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引用次数: 15
High Throughput Synthesis and Screening of Oxygen Reduction Catalysts in the MTiO3 (M = Ca, Sr, Ba) Perovskite Phase Diagram MTiO3 (M = Ca, Sr, Ba)钙钛矿相图中氧还原催化剂的高通量合成与筛选
IF 3.784 3区 化学 Q1 Chemistry Pub Date : 2020-11-05 DOI: 10.1021/acscombsci.0c00094
Alexandra R. Groves, Thomas E. Ashton, Jawwad A. Darr*

A library of 66 perovskite BaxSryCazTiO3 (x + y + z = 1) samples (ca. three grams per sample) was made in ca. 14 h using a high-throughput continuous hydrothermal flow synthesis system. The as-synthesized samples were collected from the outlet of the process and then cleaned and freeze-dried before being evaluated individually as oxygen reduction catalysts using a rotating disk electrode testing technique. To establish any correlations between physical and electrochemical characterization data, the as-synthesized samples were investigated using analytical methods including BET surface area, powder X-ray diffraction (PXRD) and in selected cases, transmission electron microscopy (TEM). The aforementioned approach was validated as being able to quickly identify oxygen reduction catalysts from new libraries of electrocatalysts.

采用高通量连续热液合成系统,在约14小时内合成了66个钙钛矿BaxSryCazTiO3 (x + y + z = 1)样品库(每个样品约3克)。合成的样品从该工艺的出口收集,然后清洗和冷冻干燥,然后使用旋转圆盘电极测试技术单独评估氧还原催化剂。为了建立物理和电化学表征数据之间的相关性,利用BET表面积、粉末x射线衍射(PXRD)和透射电子显微镜(TEM)等分析方法对合成样品进行了研究。上述方法被证实能够从新的电催化剂库中快速识别氧还原催化剂。
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引用次数: 2
High-Throughput Characterization of (FexCo1–x)3O4 Thin-Film Composition Spreads (FexCo1-x)3O4薄膜组成膜的高通量表征
IF 3.784 3区 化学 Q1 Chemistry Pub Date : 2020-11-05 DOI: 10.1021/acscombsci.0c00126
Tobias H. Piotrowiak, Xiao Wang, Lars Banko, Swati Kumari, Suchismita Sarker, Apurva Mehta, Alfred Ludwig*

Thin-film continuous composition spreads of Fe–Co–O were fabricated by reactive cosputtering from elemental Fe and Co targets in reactive Ar/O2 atmosphere using deposition temperatures ranging from 300 to 700 °C. Fused silica and platinized Si/SiO2 strips were used as substrates. Ti and Ta were investigated as adhesion layer for Pt and the fabrication of the Fe–Co–O films. The thin-film composition spreads were characterized by high-throughput electron-dispersive X-ray spectroscopy, X-ray diffraction, X-ray photoelectron spectroscopy, atomic force microscopy, scanning electron microscopy, and optical transmission spectroscopy. The Fe-content ranged from 28 to 72 at. %. The spinel phases Fe2CoO4 and FeCo2O4 could be synthesized and stabilized at all deposition temperatures with a continuous variation in spinel composition in between. The dependence of the film surface microstructure on the deposition temperature and the composition was mapped. Moreover, the band gap values, ranging from 2.41 eV for FeCo2O4 to 2.74 eV for Fe2CoO4, show a continuous variation with the composition.

在反应性Ar/O2气氛中,在300 ~ 700℃的沉积温度下,采用反应溅射法制备了Fe - Co - o连续组成薄膜。采用熔融二氧化硅和镀铂Si/SiO2条作为衬底。研究了Ti和Ta作为Pt的粘附层以及Fe-Co-O薄膜的制备。采用高通量电子色散x射线能谱、x射线衍射、x射线光电子能谱、原子力显微镜、扫描电镜和透射光谱学对薄膜的组成进行表征。铁含量在28 ~ 72 at之间。%。尖晶石相Fe2CoO4和FeCo2O4可以在所有沉积温度下合成并稳定,而尖晶石组成在不同温度下连续变化。绘制了薄膜表面微观结构与沉积温度和成分的关系图。Fe2CoO4的带隙值在2.41 eV ~ 2.74 eV之间,随组分的变化呈连续变化。
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引用次数: 8
Ni-Nitrilotriacetic Acid Affinity SELEX Method for Selection of DNA Aptamers Specific to the N-Cadherin Protein Ni-Nitrilotriacetic Acid Affinity SELEX方法选择N-Cadherin蛋白特异性DNA适体
IF 3.784 3区 化学 Q1 Chemistry Pub Date : 2020-11-04 DOI: 10.1021/acscombsci.0c00165
Luyan Yang, Tian Gao, Wenjing Li, Yu Luo, Salim Ullah, Xiaona Fang, Yanwei Cao*, Renjun Pei*

Nucleic acid aptamers are single-stranded oligonucleotides that may be evolved for affinity and specificity for their targets and can be easily produced, regenerated, and stabilized. In this study, we adapted Ni-NTA (nickle-charged nitrilotriacetic acid) affinity-chromatography in the development of single-stranded DNA aptamers against N-cadherin protein by systematic evolution of ligands by exponential enrichment (SELEX). After ten rounds of selection, two aptamers, designated NS13 and NC23, were selected, which showed low dissociation constants of 93 and 174 nM, respectively. The 5′-carboxyfluorescein-labeled NS13 was used for the sensitive detection of N-cadherin protein by the enzyme-linked oligonucleotide assay (ELONA) method.

核酸适体是单链寡核苷酸,可以进化为对其靶标的亲和力和特异性,并且易于产生,再生和稳定。在这项研究中,我们采用Ni-NTA(带镍的硝基三乙酸)亲和色谱法,通过指数富集(SELEX)配体的系统进化,开发了针对n -钙粘蛋白的单链DNA适体。经过10轮筛选,最终获得解离常数较低的适配体NS13和NC23,分别为93 nM和174 nM。采用5′-羧基荧光素标记的NS13,采用酶联寡核苷酸法(ELONA)灵敏检测n-钙粘蛋白。
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引用次数: 7
Activity Prediction of Small Molecule Inhibitors for Antirheumatoid Arthritis Targets Based on Artificial Intelligence 基于人工智能的类风湿性关节炎小分子抑制剂活性预测
IF 3.784 3区 化学 Q1 Chemistry Pub Date : 2020-11-04 DOI: 10.1021/acscombsci.0c00169
Guomeng Xing, Li Liang, Chenglong Deng, Yi Hua, Xingye Chen, Yan Yang, Haichun Liu, Tao Lu, Yadong Chen*, Yanmin Zhang*

Rheumatoid arthritis (RA) is a chronic autoimmune disease, which is compared to “immortal cancer” in industry. Currently, SYK, BTK, and JAK are the three major targets of protein tyrosine kinase for this disease. According to existing research, marketed and research drugs for RA are mostly based on single target, which limits their efficacy. Therefore, designing multitarget or dual-target inhibitors provide new insights for the treatment of RA regarding of the specific association between SYK, BTK, and JAK from two signal transduction pathways. In this study, machine learning (XGBoost, SVM) and deep learning (DNN) models were combined for the first time to build a powerful integrated model for SYK, BTK, and JAK. The predictive power of the integrated model was proved to be superior to that of a single classifier. In order to accurately assess the generalization ability of the integrated model, comprehensive similarity analysis was performed on the training and the test set, and the prediction accuracy of the integrated model was specifically analyzed under different similarity thresholds. External validation was conducted using single-target and dual-target inhibitors, respectively. Results showed that our model not only obtained a high recall rate (97%) in single-target prediction, but also achieved a favorable yield (54.4%) in dual-target prediction. Furthermore, by clustering dual-target inhibitors, the prediction performance of model in various classes were proved, evaluating the applicability domain of the model in the dual-target drug screening. In summary, the integrated model proposed is promising to screen dual-target inhibitors of SYK/JAK or BTK/JAK as RA drugs, which is beneficial for the clinical treatment of rheumatoid arthritis.

类风湿性关节炎(RA)是一种慢性自身免疫性疾病,在工业上被比作“不死的癌症”。目前,SYK、BTK和JAK是蛋白酪氨酸激酶治疗此病的三个主要靶点。根据现有的研究,市场上和研究中的RA药物大多基于单一靶点,这限制了它们的疗效。因此,设计多靶点或双靶点抑制剂,对于SYK、BTK和JAK在两种信号转导途径上的特异性关联,为RA的治疗提供了新的见解。本文首次将机器学习(XGBoost、SVM)和深度学习(DNN)模型相结合,构建了SYK、BTK和JAK的强大集成模型。综合模型的预测能力优于单一分类器的预测能力。为了准确评估集成模型的泛化能力,对训练集和测试集进行了综合相似度分析,具体分析了不同相似度阈值下集成模型的预测精度。分别使用单靶点和双靶点抑制剂进行外部验证。结果表明,该模型不仅在单目标预测中获得了较高的召回率(97%),而且在双目标预测中也获得了良好的召回率(54.4%)。此外,通过对双靶点抑制剂进行聚类,验证了该模型在不同类别中的预测性能,评估了该模型在双靶点药物筛选中的适用范围。综上所述,提出的综合模型有望筛选SYK/JAK或BTK/JAK双靶点抑制剂作为RA药物,有利于类风湿关节炎的临床治疗。
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引用次数: 11
Exploring the First High-Entropy Thin Film Libraries: Composition Spread-Controlled Crystalline Structure 探索第一个高熵薄膜库:组成扩散控制的晶体结构
IF 3.784 3区 化学 Q1 Chemistry Pub Date : 2020-11-04 DOI: 10.1021/acscombsci.0c00159
Thi Xuyen Nguyen, Yen-Hsun Su, Jason Hattrick-Simpers, Howie Joress, Takahiro Nagata, Kao-Shuo Chang, Suchismita Sarker, Apurva Mehta, Jyh-Ming Ting*

Thin films of two types of high-entropy oxides (HEOs) have been deposited on 76.2 mm Si wafers using combinatorial sputter deposition. In one type of the oxides, (MgZnMnCoNi)Ox, all the metals have a stable divalent oxidation state and similar cationic radii. In the second type of oxides, (CrFeMnCoNi)Ox, the metals are more diverse in the atomic radius and valence state, and have good solubility in their sub-binary and ternary oxide systems. The resulting HEO thin films were characterized using several high-throughput analytical techniques. The microstructure, composition, and electrical conductivity obtained on defined grid maps were obtained for the first time across large compositional ranges. The crystalline structure of the films was observed as a function of the metallic elements in the composition spreads, that is, the Mn and Zn in (MgZnMnCoNi)Ox and Mn and Ni in (CrFeMnCoNi)Ox. The (MgZnMnCoNi)Ox sample was observed to form two-phase structures, except single spinel structure was found in (MgZnMnCoNi)Ox over a range of Mn > 12 at. % and Zn < 44 at. %, while (CrFeMnCoNi)Ox was always observed to form two-phase structures. Composition-controlled crystalline structure is not only experimentally demonstrated but also supported by density function theory calculation.

采用组合溅射沉积的方法在76.2 mm硅片上制备了两种类型的高熵氧化物薄膜。在一种氧化物(MgZnMnCoNi)Ox中,所有的金属都具有稳定的二价氧化态和相似的阳离子半径。在第二类氧化物(CrFeMnCoNi)Ox中,金属的原子半径和价态更加多样化,并且在亚二元和三元氧化物体系中具有良好的溶解度。用几种高通量分析技术对所得HEO薄膜进行了表征。在确定的网格图上获得的微观结构、成分和电导率首次在大成分范围内获得。观察到薄膜的晶体结构是组成层中金属元素的函数,即(MgZnMnCoNi)Ox中的Mn和Zn和(CrFeMnCoNi)Ox中的Mn和Ni。在Mn >范围内,(MgZnMnCoNi)Ox样品除存在单尖晶石结构外,其余均形成两相结构;12。%和Zn <44。%,而(CrFeMnCoNi)Ox总是形成两相结构。成分控制的晶体结构不仅得到了实验证明,而且得到了密度函数理论计算的支持。
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引用次数: 17
Identifying Optimal Strain in Bismuth Telluride Thermoelectric Film by Combinatorial Gradient Thermal Annealing and Machine Learning 基于组合梯度退火和机器学习的碲化铋热电薄膜最佳应变识别
IF 3.784 3区 化学 Q1 Chemistry Pub Date : 2020-11-04 DOI: 10.1021/acscombsci.0c00112
Michiko Sasaki*, Shenghong Ju, Yibin Xu, Junichiro Shiomi, Masahiro Goto

The thermoelectric properties of bismuth telluride thin film (BTTF) was tuned by inducing internal strain through a combination of combinatorial gradient thermal annealing (COGTAN) and machine learning. BTTFs were synthesized via magnetron sputter coating and then treated by COGTAN. The crystal structure and thermoelectric properties, namely Seebeck coefficient and thermal conductivity, of the treated samples were analyzed via micropoint X-ray diffraction and scanning thermal probe microimaging, respectively. The obtained combinatorial data reveals the correlation between internal strain and the thermoelectric properties. The Seebeck coefficient of BTTF exhibits largest sensitivity, where the value ranges from 7.9 to ?108 μV/K. To further explore the possibility to enhance Seebeck coefficient, the combinatorial data were subjected to machine learning. The trained model predicts that optimal strains of 3–4% and 1–2% along the a- and c-axis, respectively, significantly improve Seebeck coefficient. The technique demonstrated herein can be used to predict and enhance the performance of thermoelectric materials by inducing internal strain.

采用组合梯度热退火(COGTAN)和机器学习相结合的方法,通过诱导内部应变来调节碲化铋薄膜(BTTF)的热电性能。采用磁控溅射镀膜法制备了bttf,并对其进行了COGTAN处理。通过微点x射线衍射和扫描热探针显微成像分别分析了处理后样品的晶体结构和热电性能,即塞贝克系数和导热系数。得到的组合数据揭示了内部应变与热电性能之间的相关性。BTTF的塞贝克系数灵敏度最高,在7.9 ~ - 108 μV/K之间。为了进一步探索提高塞贝克系数的可能性,对组合数据进行机器学习。经训练的模型预测,a轴方向3-4%和c轴方向1-2%的最优应变可显著提高塞贝克系数。本文所展示的技术可用于通过诱导内部应变来预测和提高热电材料的性能。
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引用次数: 6
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ACS Combinatorial Science
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