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Biochemistry and chemoinformatics Guided Classification of Hirsutane Sesquiterpenes Isolated from Mushroom

JACS AU 2025年第2期5卷 740-746页

作者： Liu, Yaping Nishishita, Jumpei Liu, Chengwei Oikawa, Hideaki Minami, Atsushi Hokkaido Univ Fac Sci Dept Chem Sapporo 0600810 Japan Tokyo Inst Technol Dept Chem Tokyo 1528551 Japan Northeast Forestry Univ Coll Life Sci Key Lab Enzyme & Enzyme Like Mat Engn Heilongjiang Harbin 150040 Peoples R China Inst Sci Tokyo Dept Chem Tokyo 1528551 Japan

Hirsutanes are mushroom-derived sesquiterpenes with a characteristic 5-5-5 tricyclic ring skeleton. To date, more than 70 derivatives have been isolated from nature. In this study, we applied heterologous expression, in vitro enzymatic reactions, and biotransformation to characterize the function of nine enzymes involved in the synthesis of anhydroarthrosporone and six novel hirsutanes. The elucidated biosynthesis involves oxidative modifications of the A-ring followed by structural diversification of the B- and C-rings. Most importantly, biosynthetic pathways provide crucial insights into the classification and organization of isolated hirsutanes. We successfully classified 69 natural hirsutanes into three groups based on their A-ring modification patterns. Our classification covered 92% of the natural hirsutanes. A comprehensive understanding of their biosynthesis will provide opportunities to isolate structurally diverse hirsutanes using genetic engineering techniques.

关键词： basidiomycota fungi hirsutanes heterologousexpression chemoinformatics

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chemoinformatics-Driven Design of New Physical Solvents for Selective CO₂ Absorption

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ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021年第22期55卷 15542-15553页

作者： Orlov, Alexey A. Demenko, Daryna Yu Bignaud, Charles Valtz, Alain Marcou, Gilles Horvath, Dragos Coquelet, Christophe Varnek, Alexandre de Meyer, Frederick Univ Strasbourg Fac Chem Lab Chemoinformat F-67081 Strasbourg France TotalEnergies SE Explorat Prod Dev & Support Operat Liquefied Nat CCUS R&D Program F-92078 Paris France PSL Univ Ctr Thermodynam Proc CTP Mines ParisTech 35 Rue St Honore F-77300 Fontainebleau France

The removal of CO2 from gases is an important industrial process in the transition to a low-carbon economy. The use of selective physical (co-)solvents is especially perspective in cases when the amount of CO2 is large as it enables one to lower the energy requirements for solvent regeneration. However, only a few physical solvents have found industrial application and the design of new ones can pave the way to more efficient gas treatment techniques. Experimental screening of gas solubility is a labor-intensive process, and solubility modeling is a viable strategy to reduce the number of solvents subject to experimental measurements. In this paper, a chemoinformatics-based modeling workflow was applied to build a predictive model for the solubility of CO2 and four other industrially important gases (CO, CH4, H-2, and N-2). A dataset containing solubilities of gases in 280 solvents was collected from literature sources and supplemented with the new data for six solvents measured in the present study. A modeling workflow based on the usage of several state-of-the-art machine learning algorithms was applied to establish quantitative structure-solubility relationships. The best models were used to perform virtual screening of the industrially produced chemicals. It enabled the identification of compounds with high predicted CO2 solubility and selectivity toward other gases. The prediction for one of the compounds, 4-methylmorpholine, was confirmed experimentally.

关键词： gas solubility industrial gases carbon dioxide methane nitrogen hydrogen carbon monoxide chemoinformatics machine learning

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chemoinformatics-assisted development of new anti-biofilm compounds

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APPLIED MICROBIOLOGY AND BIOTECHNOLOGY 2010年第1期87卷 309-317页

作者： Durig, Anna Kouskoumvekaki, Irene Vejborg, Rebecca M. Klemm, Per Tech Univ Denmark Microbial Genom Grp Ctr Biol Sequence Anal DK-2800 Lyngby Denmark Tech Univ Denmark Dept Syst Biol Ctr Biol Sequence Anal DK-2800 Lyngby Denmark

Bacterial biofilms are associated with a large number of infections. Biofilm-dwelling bacteria are particularly resistant to antibiotics, making it hard to eradicate biofilm-associated infections. Here, we use a novel cross-disciplinary approach combining microbiology and chemoinformatics to identify new and efficient anti-biofilm drugs. We found that ellagic acid (present in green tea) significantly inhibited biofilm formation of Streptococcus dysgalactiae. Based on ellagic acid, we performed in silico screening of the Chinese Natural Product Database to predict a 2nd-generation list of compounds with similar characteristics. One of these, esculetin, proved to be more efficient in preventing biofilm formation by Staphylococcus aureus. From esculetin a 3rd-generation list of compounds was predicted. One of them, fisetin, was even better to abolish biofilm formation than the two parent compounds. Fisetin dramatically inhibited biofilm formation of both S. aureus and S. dysgalactiae. The compounds did not affect planktonic growth in concentrations where they affected biofilm formation and appeared to be specific antagonists of biofilms. Arguably, since all three compounds are natural ingredients of dietary plants, they should be well-tolerated by humans. Our results indicate that such small plant components, with bacterial lifestyle altering properties are promising candidates for novel generations of antimicrobial drugs. The study underlines the potential in combining chemoinformatics and biofilm research.

关键词： Anti-biofilm drugs Bacterial biofilms chemoinformatics Dietary plant components Staphylococcus aureus Streptococcus dysgalactiae

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chemoinformatics as a Theoretical Chemistry Discipline

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MOLECULAR INFORMATICS 2011年第1期30卷 20-32页

作者： Varnek, Alexandre Baskin, Igor I. Univ Strasbourg Lab Infochim CNRS UMR 7177 F-67000 Strasbourg France Moscow MV Lomonosov State Univ Dept Chem Moscow 119991 Russia

Here, chemoinformatics is considered as a theoretical chemistry discipline complementary to quantum chemistry and force-field molecular modeling. These three fields are compared with respect to molecular representation, inference mechanisms, basic concepts and application areas. A chemical space, a fundamental concept of chemoinformatics, is considered with respect to complex relations between chemical objects (graphs or descriptor vectors). Statistical Learning Theory, one of the main mathematical approaches in structure-property modeling, is briefly reviewed. Links between chemoinformatics and its "sister" fields - machine learning, chemometrics and bioinformatics are discussed.

关键词： chemoinformatics Chemical space Similarity Computational learning theory

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chemoinformatics and stereoisomerism: A stereo graph kernel together with three new extensions

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PATTERN RECOGNITION LETTERS 2017年 87卷 222-230页

作者： Grenier, Pierre-Anthony Brun, Luc Villemin, Didier Normandie Univ ENSICAEN GREYC Caen France Normandie Univ ENSICAEN LCMT Caen France

In chemoinformatics, Quantitative Structure Activity and Property Relationships (QSAR and QSPR) are two fields which aim to predict properties of molecules thanks to computational techniques. In these fields, graph kernels provide a powerful tool which allows to combine the natural encoding of molecules by graphs with usual statistical tools. However, some molecules may have a same graph but differ by the three dimensional orientation of their atoms in space. These molecules, called stereoisomers, may have different properties which cannot be correctly predicted using usual graph encodings. In a previous study we proposed to encode the stereoisomerism property of each atom by a local subgraph, called minimal stereo subgraph, and we designed a kernel based on the comparison of bags of such subgraphs. This kernel allows to predict properties induced by the stereoisomerism which cannot be correctly predicted using usual graph kernels. However, it has two major drawbacks : it considers each minimal stereo subgraph without taking into account its surroundings, and it considers that two non identical minimal stereo subgraphs have a null similarity. In this paper we present three extensions to tackle those drawbacks. The first extension allows to take into account interactions between minimal stereo subgraphs. The second extension allows to compare the neighborhood of minimal stereo subgraphs. And finally, the third extension provides a measure of similarity between different minimal stereo subgraphs. (C) 2016 Elsevier B.V. All rights reserved.

关键词： chemoinformatics Stereoisomerism Graph kernel

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MOLECULAR DIVERSITY 2006年第1期10卷 39-79页

作者： Maldonado, AG Doucet, JP Petitjean, M Fan, BT Univ Paris 07 ITODYS CNRS UMR 7086 F-75005 Paris France

This review is dedicated to a survey on molecular similarity and diversity. Key findings reported in recent investigations are selectively highlighted and Summarized. Even if this overview is mainly centered inchemoinformatics, applications in other areas (pharmaceutical and medical chemistry, combinatorial chemistry, chemical databases management, etc.) are also introduced. The approaches used to define and descript the concepts of molecular similarity and diversity in the context of chemoinformatics are discussed in the first part of this review. We introduce, in the second and third parts, the descriptions and analyses of different methods and techniques. Finally, current applications and problems are enumerated and discussed in the last part.

关键词： chemoinformatics classification methods clustering methods combinatorial chemistry compound selection descriptors drug design high throughput screening library design molecular diversity molecular similarity partitioning selection methods similar property principle validation methods

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chemoinformatics Profiling of Ionic LiquidsuAutomatic and Chemically Interpretable Cytotoxicity Profiling, Virtual Screening, and Cytotoxicophore Identification

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TOXICOLOGICAL SCIENCES 2013年第2期136卷 548-565页

作者： Cruz-Monteagudo, Maykel Ancede-Gallardo, Evys Jorge, Miguel Dias Soeiro Cordeiro, Maria Natalia Univ Porto Fac Sci Dept Chem & Biochem REQUIMTE P-4169007 Oporto Portugal Univ Cent Marta Abreu Las Villas CEQA Fac Quim & Farm Santa Clara 54830 Villa Clara Cuba Univ Cent Marta Abreu Las Villas CBQ Mol Simulat & Drug Design Grp Santa Clara 54830 Villa Clara Cuba Univ Strathclyde Dept Chem & Proc Engn Glasgow G1 1XJ Lanark Scotland

Ionic liquids (ILs) possess a unique physicochemical profile providing a wide range of applications. Their almost limitless structural possibilities allow the design of task-specific ILs. However, their greenness, specifically their claimed relative nontoxicity has been frequently questioned, hindering their REACH registration processes and, so, their final application. Because the vast majority of ILs is yet to be synthesized, the development of chemoinformatics tools efficiently profiling their hazardous potential becomes essential. In this work, we introduce a reliable, predictive, simple, and chemically interpretable Classification and Regression Trees (CART) classifier, enabling the prioritization of ILs with a favorable cytotoxicity profile. Besides a good predictive capability (81% or 75% or 83% of accuracy or sensitivity or specificity in an external evaluation set), the other salient feature of the proposed cytotoxicity CART classifier is their simplicity and transparent chemical interpretation based on structural molecular fragments. The essentials of the current structure-cytotoxicity relationships of ILs are faithfully reproduced by this model, supporting its biophysical relevance and the reliability of the resultant predictions. By inspecting the structure of the CART, several moieties that can be regarded as cytotoxicophores were identified and used to establish a set of SAR trends specifically aimed to prioritize low-cytotoxicity ILs. Finally, we demonstrated the suitability of the joint use of the CART classifier and a group fusion similarity search as a virtual screening strategy for the automatic prioritization of safe ILs disperse in a data set of ILs of moderate to very high cytotoxicity.

关键词： chemoinformatics cytotoxicophores Ionic liquids IPC-81 cytotoxicity structure-cytotoxicity relationships virtual screening

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chemoinformatics: A view of the field and current trends in method development

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BIOORGANIC & MEDICINAL CHEMISTRY 2012年第18期20卷 5317-5323页

作者： Vogt, Martin Bajorath, Juergen Rhein Friedrich Wilhelms Univ LIMES Program Unit Chem Biol & Med Chem B IT Dept Life Sci Informat D-53113 Bonn Germany

The chemoinformatics field continues to evolve at the interface between computer science and chemistry. Chemical information and computational approaches in pharmaceutical research are major focal points of chemoinformatics. However, the boundaries of this discipline are rather fluid and the chemoinformatics spectrum is difficult to delineate. The field is in flux, which also provides opportunities for further developments. As a lead-in to the chemoinformatics Symposium-in-Print, we present a brief view of this discipline (with a little anecdotal touch), highlight current trends in method development, and discuss a number of representative examples. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： chemoinformatics Computational methods Algorithms Molecular similarity Molecular representations Machine learning SAR data mining Computational efficiency Drug discovery

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chemoinformatics: a perspective from an academic setting in Latin America

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MOLECULAR DIVERSITY 2018年第1期22卷 247-258页

作者： Jesus Naveja, J. Iluhi Oviedo-Osornio, C. Trujillo-Minero, Nicole N. Medina-Franco, Jose L. Univ Nacl Autonoma Mexico Dept Pharm Sch Chem Ave Univ 3000 Mexico City 04510 DF Mexico Univ Nacl Autonoma Mexico Fac Med PECEM Ave Univ 3000 Mexico City 04510 DF Mexico

This perspective discusses the current progress of a chemoinformatics group in a major university in Latin America. Three major aspects are discussed in a critical manner: research, education, and collaboration with industry and other public research networks. It is also presented an overview of the progress in applied research and development of research concepts. Efforts to teach chemoinformatics at the undergraduate and graduate levels are discussed. It is addressed how the partnership with industry and other not-for-profit research institutions not only brings additional sources of funding but, more importantly, increases the impact of the multidisciplinary work and offers the students to be exposed to other research environments. We also discuss the main perspectives and challenges that remain to be addressed in these settings.

关键词： Activity landscape chemoinformatics Computer-aided drug design D-Tools Epi-informatics Structure-activity relationships Collaboration ChemMaps

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chemoinformatics and chemical genomics: potential utility of in silico methods

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JOURNAL OF APPLIED TOXICOLOGY 2012年第11期32卷 880-889页

作者： Valerio, Luis G., Jr. Choudhuri, Supratim US FDA Off Pharmaceut Sci Ctr Drug Evaluat & Res Silver Spring MD 20993 USA US FDA Div Biotechnol & GRAS Notice Review Off Food Addit Safety Ctr Food Safety & Appl Nutr Silver Spring MD 20993 USA

Computational life sciences and informatics are inseparably intertwined and they lie at the heart of modern biology, predictive quantitative modeling and high-performance computing. Two of the applied biological disciplines that are poised to benefit from such progress are pharmacology and toxicology. This review will describe in silico chemoinformatics methods such as (quantitative) structureactivity relationship modeling and will overview how chemoinformatic technologies are considered in applied regulatory research. Given the post-genomics era and large-scale repositories of omics data that are available, this review will also address potential applications of in silico techniques in chemical genomics. Chemical genomics utilizes small molecules to explore the complex biological phenomena that may not be not amenable to straightforward genetic approach. The reader will gain the understanding that chemoinformatics stands at the interface of chemistry and biology with enabling systems for mapping, statistical modeling, pattern recognition, imaging and database tools. The great potential of these technologies to help address complex issues in the toxicological sciences is appreciated with the applied goal of the protection of public health. Published 2012. This article is a US Government work and is in the public domain in the USA.

关键词： in silico toxicology in silico methods informatics QSAR computational toxicology drug safety safety assessment genotoxicity cardiac safety chemoinformatics chemical genomics chemical epigenomics

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