Literature DB >> 32718281

Enalos Suite of Tools: Enhancing Cheminformatics and Nanoinfor - matics through KNIME.

Antreas Afantitis1, Andreas Tsoumanis1, Georgia Melagraki1.   

Abstract

Drug discovery as well as (nano)material design projects demand the in silico analysis of large datasets of compounds with their corresponding properties/activities, as well as the retrieval and virtual screening of more structures in an effort to identify new potent hits. This is a demanding procedure for which various tools must be combined with different input and output formats. To automate the data analysis required we have developed the necessary tools to facilitate a variety of important tasks to construct workflows that will simplify the handling, processing and modeling of cheminformatics data and will provide time and cost efficient solutions, reproducible and easier to maintain. We therefore develop and present a toolbox of >25 processing modules, Enalos+ nodes, that provide very useful operations within KNIME platform for users interested in the nanoinformatics and cheminformatics analysis of chemical and biological data. With a user-friendly interface, Enalos+ Nodes provide a broad range of important functionalities including data mining and retrieval from large available databases and tools for robust and predictive model development and validation. Enalos+ Nodes are available through KNIME as add-ins and offer valuable tools for extracting useful information and analyzing experimental and virtual screening results in a chem- or nano- informatics framework. On top of that, in an effort to: (i) allow big data analysis through Enalos+ KNIME nodes, (ii) accelerate time demanding computations performed within Enalos+ KNIME nodes and (iii) propose new time and cost efficient nodes integrated within Enalos+ toolbox we have investigated and verified the advantage of GPU calculations within the Enalos+ nodes. Demonstration data sets, tutorial and educational videos allow the user to easily apprehend the functions of the nodes that can be applied for in silico analysis of data. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.

Keywords:  Chemical data base; Efficient data mining; Enalos Suite; Enalos+ KNIME nodes; KINME; Nanoinformatics; PubChem; chemoinformatics-aided material design

Mesh:

Year:  2020        PMID: 32718281     DOI: 10.2174/0929867327666200727114410

Source DB:  PubMed          Journal:  Curr Med Chem        ISSN: 0929-8673            Impact factor:   4.530


  5 in total

Review 1.  Nanotechnology and artificial intelligence to enable sustainable and precision agriculture.

Authors:  Peng Zhang; Zhiling Guo; Sami Ullah; Georgia Melagraki; Antreas Afantitis; Iseult Lynch
Journal:  Nat Plants       Date:  2021-06-24       Impact factor: 15.793

2.  Can an InChI for Nano Address the Need for a Simplified Representation of Complex Nanomaterials across Experimental and Nanoinformatics Studies?

Authors:  Iseult Lynch; Antreas Afantitis; Thomas Exner; Martin Himly; Vladimir Lobaskin; Philip Doganis; Dieter Maier; Natasha Sanabria; Anastasios G Papadiamantis; Anna Rybinska-Fryca; Maciej Gromelski; Tomasz Puzyn; Egon Willighagen; Blair D Johnston; Mary Gulumian; Marianne Matzke; Amaia Green Etxabe; Nathan Bossa; Angela Serra; Irene Liampa; Stacey Harper; Kaido Tämm; Alexander CØ Jensen; Pekka Kohonen; Luke Slater; Andreas Tsoumanis; Dario Greco; David A Winkler; Haralambos Sarimveis; Georgia Melagraki
Journal:  Nanomaterials (Basel)       Date:  2020-12-11       Impact factor: 5.076

Review 3.  Advances in de Novo Drug Design: From Conventional to Machine Learning Methods.

Authors:  Varnavas D Mouchlis; Antreas Afantitis; Angela Serra; Michele Fratello; Anastasios G Papadiamantis; Vassilis Aidinis; Iseult Lynch; Dario Greco; Georgia Melagraki
Journal:  Int J Mol Sci       Date:  2021-02-07       Impact factor: 5.923

4.  Effects of Phthalate Esters (PAEs) on Cell Viability and Nrf2 of HepG2 and 3D-QSAR Studies.

Authors:  Huan Liu; Huiying Huang; Xueman Xiao; Zilin Zhao; Chunhong Liu
Journal:  Toxics       Date:  2021-06-05

5.  Structure-Based Discovery of Novel Chemical Classes of Autotaxin Inhibitors.

Authors:  Christiana Magkrioti; Eleanna Kaffe; Elli-Anna Stylianaki; Camelia Sidahmet; Georgia Melagraki; Antreas Afantitis; Alexios N Matralis; Vassilis Aidinis
Journal:  Int J Mol Sci       Date:  2020-09-23       Impact factor: 5.923

  5 in total

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