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HIGH-PERFORMANCE COMPUTATION AND ARTIFICIAL INTELLIGENCE IN PESTICIDE DISCOVERY: STATUS AND OUTLOOK

Frontiers of Agricultural Science and Engineering 2022, Volume 9, Issue 1,   Pages 150-154 doi: 10.15302/J-FASE-2021419

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Liquid metal material genome: Initiation of a new research track towards discovery of advanced energy

Lei WANG, Jing LIU

Frontiers in Energy 2013, Volume 7, Issue 3,   Pages 317-332 doi: 10.1007/s11708-013-0271-9

Abstract: As the basis of modern industry, the roles materials play are becoming increasingly vital in this day and age. With many superior physical properties over conventional fluids, the low melting point liquid metal material, especially room-temperature liquid metal, is recently found to be uniquely useful in a wide variety of emerging areas from energy, electronics to medical sciences. However, with the coming enormous utilization of such materials, serious issues also arise which urgently need to be addressed. A biggest concern to impede the large scale application of room-temperature liquid metal technologies is that there is currently a strong shortage of the materials and species available to meet the tough requirements such as cost, melting point, electrical and thermal conductivity, etc. Inspired by the Material Genome Initiative as issued in 2011 by the United States of America, a more specific and focused project initiative was proposed in this paper—the liquid metal material genome aimed to discover advanced new functional alloys with low melting point so as to fulfill various increasing needs. The basic schemes and road map for this new research program, which is expected to have a worldwide significance, were outlined. The theoretical strategies and experimental methods in the research and development of liquid metal material genome were introduced. Particularly, the calculation of phase diagram (CALPHAD) approach as a highly effective way for material design was discussed. Further, the first-principles (FP) calculation was suggested to combine with the statistical thermodynamics to calculate the thermodynamic functions so as to enrich the CALPHAD database of liquid metals. When the experimental data are too scarce to perform a regular treatment, the combination of FP calculation, cluster variation method (CVM) or molecular dynamics (MD), and CALPHAD, referred to as the mixed FP-CVM-CALPHAD method can be a promising way to solve the problem. Except for the theoretical strategies, several parallel processing experimental methods were also analyzed, which can help improve the efficiency of finding new liquid metal materials and reducing the cost. The liquid metal material genome proposal as initiated in this paper will accelerate the process of finding and utilization of new functional materials.

Keywords： liquid metal material genome     energy material     material discovery     advanced material     room-temperature liquid    

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An econometric investigation using price discovery theory

Yeli ZENG, Cong DONG, Mikael HÖÖK, Jinhua SUN, Danyang SHI

Frontiers in Energy 2020, Volume 14, Issue 4,   Pages 726-739 doi: 10.1007/s11708-020-0701-4

Abstract: reflect the average price level and market movements, but the market information transparency and price discovery

Keywords： liquefied natural gas     price index     Shanghai Petroleum and Gas Exchange     price discovery     market reforms    

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New Technology promotes the Discovery of the Tarim Natural Gas Province

Qiu Zhongjian

Strategic Study of CAE 2000, Volume 2, Issue 9,   Pages 38-41

Abstract: The discovery is a catalyst for the commencement of the project to transmit natural gas from the Tarim

Keywords： key technology     innovation     discovery     Tarim gas province    

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Symbolic representation based on trend features for knowledge discovery in long time series

Hong YIN,Shu-qiang YANG,Xiao-qian ZHU,Shao-dong MA,Lu-min ZHANG

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 9,   Pages 744-758 doi: 10.1631/FITEE.1400376

Abstract: an essential task for decision-making activities such as classification, prediction, and knowledge discoveryA time series is represented by trend symbols, which are also suitable for use in knowledge discoverybetter segmentation efficiency and classification accuracy, but also is applicable for use in knowledge discovery

Keywords： Long time series     Segmentation     Trend features     Symbolic     Knowledge discovery    

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Facile discovery of red blood cell deformation and compromised membrane/skeleton assembly in Prader–Willi

Frontiers of Medicine 2022, Volume 16, Issue 6,   Pages 946-956 doi: 10.1007/s11684-022-0962-x

Abstract: Prader–Willi syndrome (PWS) is a rare congenital disease with genetic alterations in chromosome 15. Although genetic disorders and DNA methylation abnormalities involved in PWS have been investigated to a significant degree, other anomalies such as those in erythrocytes may occur and these have not been clearly elucidated. In the present study, we uncovered slight anemia in children with PWS that was associated with increased red blood cell (RBC) distribution width (RDW) and contrarily reduced hematocrit (HCT) values. Intriguingly, the increased ratio in RDW to HCT allowed sufficient differentiation between the PWS patients from the healthy controls and, importantly, with individuals exhibiting conventional obesity. Further morphologic examinations revealed a significant deformity in erythrocytes and mild hemolysis in PWS patients. Comprehensive mechanistic investigations unveiled compromised membrane skeletal assembly and membrane lipid composition, and revealed a reduced F-actin/G-actin ratio in PWS patients. We ascribed these phenotypic changes in erythrocytes to the observed genetic defects, including DNA methylation abnormalities. Our collective data allowed us to uncover RBC deformation in children with PWS, and this may constitute an auxiliary indicator of PWS in early childhood.

Keywords： Prader–Willi syndrome     early diagnosis     erythrocyte deformation     membrane skeleton     membrane lipid    

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Discovery and repurposing of artemisinin

Frontiers of Medicine 2022, Volume 16, Issue 1,   Pages 1-9 doi: 10.1007/s11684-021-0898-6

Abstract: The discovery of artemisinin, inspired by traditional Chinese medicine (TCM), has brought in a paradigmHere, we will first review the initial discovery of artemisinin, an extraordinary journey that was in

Keywords： artemisinin     drug repurposing     cancer     inflammation     COVID-19     traditional Chinese medicine    

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Li Siguang and China's Big Discovery of Petroleum

Zhao Wenjing

Strategic Study of CAE 2005, Volume 7, Issue 2,   Pages 26-34

Abstract: with full historical materials, that Li Siguang made irreplaceable contribution to China's big discovery

Keywords： Li Siguang     China's oil resource     China's big discovery and development of petroleum    

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Discovery for New Herbicide Sites of Action by Quantification of plant Primary Metabolite and Enzyme Perspective

Franck E. Dayan, Stephen O. Duke

Engineering 2020, Volume 6, Issue 5,   Pages 509-514 doi: 10.1016/j.eng.2020.03.004

Abstract: Two untried strategies for the discovery on new herbicide SOAs are discussed.Targeting SOAs that result in accumulation of phytotoxic compounds is the first novel approach to herbicide discoveryModern proteomic methods can identify low enzyme level SOAs for biorational herbicide discovery.These approaches might be useful in discovery of herbicides more closely related to natural compounds

Keywords： Natural products     Biorational discovery     Mode of action     Herbicide    

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Semantically condensed multi-relational frequent pattern discovery based on conjunctive query containment

Yang Bingru,Zhang Wei,Qian Rong

Strategic Study of CAE 2008, Volume 10, Issue 9,   Pages 47-53

Abstract: Multi-relational frequent pattern discovery approaches directly look for frequent patterns that involveWhile the state-of-the-art of multi-relational frequent pattern discovery approaches is based on theprogramming techniques, we propose an approach to semantically condensed multi-relational frequent pattern discovery, function, efficiency and scalability of the state-of-the-art of multi-relational frequent pattern discovery

Keywords： multi-relational data mining     frequent pattern discovery     conjunctive query     condensed pattern    

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The Application of Artificial Intelligence Accelerates G Protein-Coupled Receptor Ligand Discovery Review

Wei Chen,Chi Song,Liang Leng,Sanyin Zhang,Shilin Chen

Engineering 2024, Volume 32, Issue 1,   Pages 19-29 doi: 10.1016/j.eng.2023.09.011

Abstract: are crucial players in various physiological processes, making them attractive candidates for drug discoveryHowever, traditional approaches to GPCR ligand discovery are time-consuming and resource-intensive.In this study, we provide guidelines for effectively utilizing AI methods for GPCR ligand discovery,First, the online resources that are instrumental in GPCR ligand discovery were summarized, includingSubsequently, the key applications of AI methods in the different stages of GPCR drug discovery were

Keywords： G protein-coupled receptor     Ligand     Artificial intelligence     Multi-omics     Drug discovery    

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Discovery of small molecule degraders for modulating cell cycle

Frontiers of Medicine   Pages 823-854 doi: 10.1007/s11684-023-1027-5

Abstract: The cell cycle is a complex process that involves DNA replication, protein expression, and cell division. Dysregulation of the cell cycle is associated with various diseases. Cyclin-dependent kinases (CDKs) and their corresponding cyclins are major proteins that regulate the cell cycle. In contrast to inhibition, a new approach called proteolysis-targeting chimeras (PROTACs) and molecular glues can eliminate both enzymatic and scaffold functions of CDKs and cyclins, achieving targeted degradation. The field of PROTACs and molecular glues has developed rapidly in recent years. In this article, we aim to summarize the latest developments of CDKs and cyclin protein degraders. The selectivity, application, validation and the current state of each CDK degrader will be overviewed. Additionally, possible methods are discussed for the development of degraders for CDK members that still lack them. Overall, this article provides a comprehensive summary of the latest advancements in CDK and cyclin protein degraders, which will be helpful for researchers working on this topic.

Keywords： PROTAC     molecular glue     degrader     cell cycle     CDK     cyclin    

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Discovery of cryptolepine derivatives as novel promising agents against phytopathogenic bacteria

Frontiers of Chemical Science and Engineering 2023, Volume 17, Issue 2,   Pages 156-166 doi: 10.1007/s11705-022-2196-5

Abstract: To ensure the production of food crops, a series of cryptolepine derivatives were synthesised, after which their antibacterial activities and mechanism of action against three plant pathogens were investigated. Our bioassay results indicated that most of the target compounds displayed potent inhibitory effects against Xanthomonas oryzae (X. oryzae) and Xanthomonas axonopodis pv. citri (X. axonopodis pv. c.). Remarkably, compound 9 exhibited the best in vitro antibacterial activity against X. oryzae, with a minimum inhibitory concentration (MIC) value of 0.78 μg·mL–1. Compound 2 exhibited the best in vitro antibacterial activity against X. axonopodis pv. c., with an MIC value of 0.39 μg·mL–1. These activities were superior to those of copper quinolate (MIC = 6.25, 25 μg·mL–1) and thiodiazole copper (MIC = 100, 200 μg·mL–1) against X. oryzae and X. axonopodis pv. c. In vivo experiments demonstrated the promising applicability of compound 9 for the control of rice bacterial infections. Furthermore, compound 9 was selected as a candidate to conduct preliminary analyses of the antibacterial mechanisms of cryptolepine derivatives. Scanning electron microscopy and transmission electron microscopy observations, extracellular polysaccharide production, biofilm formation, transcriptomic, quantitative reverse transcription-polymerase chain reaction analyses, and molecular docking assays were performed. Collectively, our findings demonstrated that compound 9 might act via multifarious mechanisms to down-regulate virulence factors and cause cell death.

Keywords： cryptolepine derivatives     phytopathogenic bacteria     antibacterial activity     mechanism of action    

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DISCOVERY OF TRIKETONE-QUINOXALINE HYBRIDS AS POTENT HPPD INHIBITORS USING STRUCTURE-BASED DRUG DESIGN

Frontiers of Agricultural Science and Engineering 2022, Volume 9, Issue 1,   Pages 133-145 doi: 10.15302/J-FASE-2021401

Abstract:

p-Hydroxyphenylpyruvate dioxygenase (EC 1.13.11.27, HPPD) belongs to the family of Fe(II)-dependent non-heme oxygenases that occur in the majority of aerobic organisms. HPPD has proved to be a promising target in herbicide research and development. A battery of novel triketone-quinoxaline compounds has been designed using a structure-based drug design strategy and then prepared. Enzyme inhibition assays show that these synthesized derivatives possess favorable inhibition capability against Arabidopsis thaliana HPPD with IC50 values ranging from 0.317 to 0.891 μmol·L−1. Subsequently, the molecular docking results indicate that two adjacent carbonyls of the triketone moiety of the representative compound 2-(2,3-dimethyl-8-(o-tolyl)quinoxaline-6-carbonyl)-3-hydroxycyclohex-2-en-1-one (7d) engage in chelation with the ferrous ion of A. thaliana HPPD in a bidentate pose, and its quinoxaline scaffold forms two sets of parallel π-stacking interaction between two phenylalanine residues (Phe424 and Phe381). In addition, the extended phenyl group also interacts with Phe392 in a π-π stacking way. This study indicates that triketone-quinoxaline is a promising scaffold for discovering HPPD inhibitors with substantially increased potency, providing insight into the molecular design of new herbicides.

 

Keywords： herbicide / HPPD / inhibitor / quinoxaline / triketon    

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Discovery of the mechanisms of acupuncture in the treatment of migraine based on functional magnetic

Frontiers of Medicine   Pages 993-1005 doi: 10.1007/s11684-023-0989-7

Abstract: Migraine is one of the most prevalent and disabling neurological disease, but the current pharmacotherapies show limited efficacy and often accompanied by adverse effects. Acupuncture is a promising complementary therapy, but further clinical evidence is needed. The influence of acupuncture on migraine is not an immediate effect, and its mechanism remains unclear. This study aims to provide further clinical evidence for the anti-migraine effects of acupuncture and explore the mechanism involved. A randomized controlled trial was performed among 10 normal controls and 38 migraineurs. The migraineurs were divided into blank control, sham acupuncture, and acupuncture groups. Patients were subjected to two courses of treatment, and each treatment lasted for 5 days, with an interval of 1 day between the two courses. The effectiveness of treatment was evaluated using pain questionnaire. The functional magnetic resonance imaging (fMRI) data were analyzed for investigating brain changes induced by treatments. Blood plasma was collected for metabolomics and proteomics studies. Correlation and mediation analyses were performed to investigate the interaction between clinical, fMRI and omics changes. Results showed that acupuncture effectively relieved migraine symptoms in a way different from sham acupuncture in terms of curative effect, affected brain regions, and signaling pathways. The anti-migraine mechanism involves a complex network related to the regulation of the response to hypoxic stress, reversal of brain energy imbalance, and regulation of inflammation. The brain regions of migraineurs affected by acupuncture include the lingual gyrus, default mode network, and cerebellum. The effect of acupuncture on patients’ metabolites/proteins may precede that of the brain.

Keywords： acupuncture     migraine     fMRI     metabolome     proteome    

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Title Author Date Type Operation

HIGH-PERFORMANCE COMPUTATION AND ARTIFICIAL INTELLIGENCE IN PESTICIDE DISCOVERY: STATUS AND OUTLOOK

Journal Article

Liquid metal material genome: Initiation of a new research track towards discovery of advanced energy

Lei WANG, Jing LIU

Journal Article

An econometric investigation using price discovery theory

Yeli ZENG, Cong DONG, Mikael HÖÖK, Jinhua SUN, Danyang SHI

Journal Article

New Technology promotes the Discovery of the Tarim Natural Gas Province

Qiu Zhongjian

Journal Article

Symbolic representation based on trend features for knowledge discovery in long time series

Hong YIN,Shu-qiang YANG,Xiao-qian ZHU,Shao-dong MA,Lu-min ZHANG

Journal Article

Facile discovery of red blood cell deformation and compromised membrane/skeleton assembly in Prader–Willi

Journal Article

Discovery and repurposing of artemisinin

Journal Article

Li Siguang and China's Big Discovery of Petroleum

Zhao Wenjing

Journal Article

Discovery for New Herbicide Sites of Action by Quantification of plant Primary Metabolite and Enzyme

Franck E. Dayan, Stephen O. Duke

Journal Article

Semantically condensed multi-relational frequent pattern discovery based on conjunctive query containment

Yang Bingru,Zhang Wei,Qian Rong

Journal Article

The Application of Artificial Intelligence Accelerates G Protein-Coupled Receptor Ligand Discovery

Wei Chen,Chi Song,Liang Leng,Sanyin Zhang,Shilin Chen

Journal Article

Discovery of small molecule degraders for modulating cell cycle

Journal Article

Discovery of cryptolepine derivatives as novel promising agents against phytopathogenic bacteria

Journal Article

DISCOVERY OF TRIKETONE-QUINOXALINE HYBRIDS AS POTENT HPPD INHIBITORS USING STRUCTURE-BASED DRUG DESIGN

Journal Article

Discovery of the mechanisms of acupuncture in the treatment of migraine based on functional magnetic

Journal Article