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Review Article

Enalos工具套件：通过KNIME增强化学信息学和纳米信息学

卷 27, 期 38, 2020

页: [6523 - 6535] 页: 13

弟呕挨: 10.2174/0929867327666200727114410

价格: $65

摘要

药物发现以及（纳米）材料设计项目要求对具有相应性质/活性的化合物的大型数据集进行计算机分析，并需要对更多结构进行检索和虚拟筛选，以识别出新的有效药物。这是一个苛刻的过程，必须将各种工具与不同的输入和输出格式结合使用。为了自动化所需的数据分析，我们开发了必要的工具来促进各种重要任务来构建工作流，这些工作流将简化化学信息学数据的处理，处理和建模，并提供可重复且易于维护的省时，低成本的解决方案。因此，我们开发并展示了一个包含25个以上处理模块的工具箱，即Enalos +节点，该工具箱可在KNIME平台内为对化学和生物学数据的纳米信息学和化学信息学分析感兴趣的用户提供非常有用的操作。通过用户友好的界面，Enalos +节点提供了广泛的重要功能，包括数据挖掘以及从大型可用数据库中检索以及用于健壮和预测性模型开发和验证的工具。 Enalos +节点可通过KNIME作为附件使用，并提供了宝贵的工具，可用于提取有用的信息以及在化学或纳米信息学框架中分析实验和虚拟筛选结果。最重要的是，为了：（i）通过Enalos + KNIME节点进行大数据分析，（ii）加速在Enalos + KNIME节点内执行的耗时计算，以及（iii）提出集成在Enalos +工具箱中的新的具有时间和成本效益的节点，我们已经研究并验证了Enalos +节点中GPU计算的优势。演示数据集，教程和教学视频使用户可以轻松理解可用于计算机数据分析的节点功能。

关键词: Enalos + KNIME节点，化学信息学辅助的材料设计，纳米信息学，Enalos Suite，化学数据库，KINME，高效数据挖掘，PubChem。

« Previous Next »
[1]
NovaMechanics Ltd. Enalos+ KNIME Nodes, available at http://enalosplus.novamechanics.com (Access date: November 2017.).
[2]
Berthold, M.R.; Cebron, N.; Dill, F.; Gabriel, T.R.; Kötter, T.; Meinl, T.; Ohl, P.; Thiel, K.; Wiswedel, B. KNIME - The konstanz information miner. SIGKDD Explor., 2009, 11(1), 26-31.
[http://dx.doi.org/10.1145/1656274.1656280]
[3]
Kim, S.; Thiessen, P.A.; Bolton, E.E.; Chen, J.; Fu, G.; Gindulyte, A.; Han, L.; He, J.; He, S.; Shoemaker, B.A.; Wang, J.; Yu, B.; Zhang, J.; Bryant, S.H. Pubchem substance and compound databases. Nucleic Acids Res., 2016, 44(D1), D1202-D1213.
[http://dx.doi.org/10.1093/nar/gkv951 ] [PMID: 26400175]
[4]
Melagraki, G.; Afantitis, A. Enalos KNIME nodes: exploring corrosion inhibition of Steel in acidic medium. Chemom. Intell. Lab. Syst., 2013, 123, 9-14.
[http://dx.doi.org/10.1016/j.chemolab.2013.02.003]
[5]
Chambers, J.; Davies, M.; Gaulton, A.; Hersey, A.; Velankar, S.; Petryszak, R.; Hastings, J.; Bellis, L.; McGlinchey, S.; Overington, J.P. UniChem: a unified chemical structure cross-referencing and identifier tracking system. J. Cheminform., 2013, 5(1), 3.
[http://dx.doi.org/10.1186/1758-2946-5-3 ] [PMID: 23317286]
[6]
KNIME Cheminformatics Extensions. Available at https://www.knime. com/cheminformatics-extensions (Accessed Nov 13, 2017).
[7]
Greg Landrum. RDKit: Open-Source Cheminformatics. Available at , http://www.rdkit.org/ (Accessed Nov 13, 2017).
[8]
Steinbeck, C.; Han, Y.; Kuhn, S.; Horlacher, O.; Luttmann, E.; Willighagen, E. The Chemistry Development Kit (CDK): an open-source Java library for chemo- and bioinformatics. J. Chem. Inf. Comput. Sci., 2003, 43(2), 493-500.
[http://dx.doi.org/10.1021/ci025584y ] [PMID: 12653513]
[9]
McGuire, R.; Verhoeven, S.; Vass, M.; Vriend, G.; de Esch, I.J.P.; Lusher, S.J.; Leurs, R.; Ridder, L.; Kooistra, A.J.; Ritschel, T.; de Graaf, C. 3D-e-Chem-VM: structural cheminformatics research infrastructure in a freely available virtual machine. J. Chem. Inf. Model., 2017, 57(2), 115-121.
[http://dx.doi.org/10.1021/acs.jcim.6b00686 ] [PMID: 28125221]
[10]
Gütlein, M.; Karwath, A.; Kramer, S. CheS-mapper - chemical space mapping and visualization in 3D. J. Cheminform., 2012, 4(1), 7.
[http://dx.doi.org/10.1186/1758-2946-4-7 ] [PMID: 22424447]
[11]
BioSolveIT KNIME Interfaces. Available at https://www.biosolveit.de/KNIME/ (Accessed November 2017).
[12]
Schrodinger KNIME Extensions. Available at https://www.schrodinger. com/KNIME-Extensions (Accessed November 2017).
[13]
KNIME Technology Partners. Available at https://www.knime.com/ (Accessed November 2017).
[14]
Melagraki, G.; Afantitis, A. A risk assessment tool for the virtual screening of metal oxide nanoparticles through enalos in silico nano platform. Curr. Top. Med. Chem., 2015, 15(18), 1827-1836.
[http://dx.doi.org/10.2174/1568026615666150506144536 ] [PMID: 26002591]
[15]
Varnek, a; Tropsha, a. Chemoinformatics approaches to virtual screening 2008.
[16]
NIH. NCI/CADD Chemical Identifier Resolver. Available at https://cactus.nci.nih.gov/chemical/structure (Accessed November 2017).
[17]
NanoCommons H2020 Project. Available at www.nanocommons.eu (Accessed November 2017).
[18]
Tsoumanis, A.; Afantitis, A.; Melagraki, G. Enalos APIs for NanoCommons Knowledge Base. Available at, http://enaloscloud. novamechanics.com/EnalosWebServices/KnimeDBWebService?wsdl (Accessed November 2017).
[19]
Hong, H.; Xie, Q.; Ge, W.; Qian, F.; Fang, H.; Shi, L.; Su, Z.; Perkins, R.; Tong, W. Mold(2), molecular descriptors from 2D structures for chemoinformatics and toxicoinformatics. J. Chem. Inf. Model., 2008, 48(7), 1337-1344.
[http://dx.doi.org/10.1021/ci800038f ] [PMID: 18564836]
[20]
Willighagen, E.L.; Mayfield, J.W.; Alvarsson, J.; Berg, A.; Carlsson, L.; Jeliazkova, N.; Kuhn, S.; Pluskal, T.; Rojas-Chertó, M.; Spjuth, O.; Torrance, G.; Evelo, C.T.; Guha, R.; Steinbeck, C. The Chemistry Development Kit (CDK) v2.0: atom typing, depiction, molecular formulas, and substructure searching. J. Cheminform., 2017, 9(1), 33.
[http://dx.doi.org/10.1186/s13321-017-0220-4] [PMID: 29086040]
[21]
Chambers, J.; Davies, M.; Gaulton, A.; Papadatos, G.; Hersey, A.; Overington, J.P. UniChem: extension of InChI-based compound mapping to salt, connectivity and stereochemistry layers. J. Cheminform., 2014, 6(1), 43.
[http://dx.doi.org/10.1186/s13321-014-0043-5] [PMID: 25221628]
[22]
Tropsha, A. Best Practices for QSAR model development, validation, and exploitation. Mol. Inform., 2010, 29(6-7), 476-488.
[http://dx.doi.org/10.1002/minf.201000061 ] [PMID: 27463326]
[23]
Kennard, R.W.; Stone, L.A. Computer aided design of experiments. Technometrics, 1969, 11(1), 137-148.
[http://dx.doi.org/10.1080/00401706.1969.10490666]
[24]
Hudson, B.D.; Hyde, R.M.; Rahr, E.; Wood, J.; Osman, J. Parameter based methods for compound selection from chemical databases. Quant. Struct. Relationships, 1996, 15(4), 285-289.
[http://dx.doi.org/10.1002/qsar.19960150402]
[25]
Afantitis, A.; Melagraki, G.; Sarimveis, H.; Koutentis, P.A.; Markopoulos, J.; Igglessi-Markopoulou, O. Development and evaluation of a QSPR model for the prediction of diamagnetic susceptibility. QSAR Comb. Sci., 2008, 27(4), 432-436.
[http://dx.doi.org/10.1002/qsar.200730083]
[26]
Afantitis, A.; Melagraki, G.; Tsoumanis, A.; Valsami-Jones, E.; Lynch, I. A nanoinformatics decision support tool for the virtual screening of gold nanoparticle cellular association using protein corona fingerprints. Nanotoxicology, 2018, 12(10), 1148-1165.
[http://dx.doi.org/10.1080/17435390.2018.1504998 ] [PMID: 30182778]
[27]
Varsou, D-D.; Afantitis, A.; Tsoumanis, A.; Papadiamantis, A.; Valsami-Jones, E.; Lynch, I.; Melagraki, G. zeta-potential read-across model utilizing nanodescriptors extracted via the nanoxtract image analysis tool available on the enalos nanoinformatics cloud platform. Small, 2020, 16(21)e1906588
[http://dx.doi.org/10.1002/smll.201906588 ] [PMID: 32174008]
[28]
Afantitis, A. Nanoinformatics: artificial intelligence and nanotechnology in the new decade. Comb. Chem. High Throughput Screen., 2020, 23(1), 4-5.
[http://dx.doi.org/10.2174/138620732301200316112000 ] [PMID: 32189589]
[29]
Harris, M.J.; Baxter, W.V., III; Scheuermann, T.; Lastra, A. Simulation of cloud dynamics on graphics hardware. Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware, 2003, pp. 92-102.
[30]
Varsou, D.D.; Tsoumanis, A.; Afantitis, A.; Melagraki, G. Enalos cloud platform: nanoinformatics and cheminformatics tools. Methods in Pharmacology and Toxicology; Humana Press Inc., 2020, pp. 789-800.
[http://dx.doi.org/10.1007/978-1-0716-0150-1_3]
[31]
Varsou, D-D.; Nikolakopoulos, S.; Tsoumanis, A.; Melagraki, G.; Afantitis, A. Enalos suite: new cheminformatics platform for drug discovery and computational toxicology. Methods Mol. Biol., 2018, 1800, 287-311.
[http://dx.doi.org/10.1007/978-1-4939-7899-1_14 ] [PMID: 29934899]
[32]
NanoSolveIT H2020 Nanoinformatics Project. Available at: www.nanosolveit.eu (Access date: November 2017).
[33]
Afantitis, A.; Melagraki, G.; Isigonis, P.; Tsoumanis, A.; Varsou, D.D.; Valsami-Jones, E.; Papadiamantis, A.; Ellis, L.A.; Sarimveis, H.; Doganis, P.; Karatzas, P.; Tsiros, P.; Liampa, I.; Lobaskin, V.; Greco, D.; Serra, A.; Kinaret, P.A.S.; Saarimäki, L.A.; Grafström, R.; Kohonen, P.; Nymark, P.; Willighagen, E.; Puzyn, T.; Rybinska-Fryca, A.; Lyubartsev, A.; Alstrup Jensen, K.; Brandenburg, J.G.; Lofts, S.; Svendsen, C.; Harrison, S.; Maier, D.; Tamm, K.; Jänes, J.; Sikk, L.; Dusinska, M.; Longhin, E.; Rundén-Pran, E.; Mariussen, E.; El Yamani, N.; Unger, W.; Radnik, J.; Tropsha, A.; Cohen, Y.; Leszczynski, J.; Ogilvie Hendren, C.; Wiesner, M.; Winkler, D.; Suzuki, N.; Yoon, T.H.; Choi, J-S.; Sanabria, N.; Gulumian, M.; Lynch, I. NanoSolveIT project: driving nanoinformatics research to develop innovative and integrated tools for in silico nanosafety assessment. Comput. Struct. Biotechnol. J., 2020, 18, 583-602.
[http://dx.doi.org/10.1016/j.csbj.2020.02.023 ] [PMID: 32226594]

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