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NEEMP: software for validation, accurate calculation and fast parameterization of EEM charges

Overview of attention for article published in Journal of Cheminformatics, October 2016
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Title
NEEMP: software for validation, accurate calculation and fast parameterization of EEM charges
Published in
Journal of Cheminformatics, October 2016
DOI 10.1186/s13321-016-0171-1
Pubmed ID
Authors

Tomáš Raček, Jana Pazúriková, Radka Svobodová Vařeková, Stanislav Geidl, Aleš Křenek, Francesco Luca Falginella, Vladimír Horský, Václav Hejret, Jaroslav Koča

Abstract

The concept of partial atomic charges was first applied in physical and organic chemistry and was later also adopted in computational chemistry, bioinformatics and chemoinformatics. The electronegativity equalization method (EEM) is the most frequently used approach for calculating partial atomic charges. EEM is fast and its accuracy is comparable to the quantum mechanical charge calculation method for which it was parameterized. Several EEM parameter sets for various types of molecules and QM charge calculation approaches have been published and new ones are still needed and produced. Methodologies for EEM parameterization have been described in a few articles, but a software tool for EEM parameterization and EEM parameter sets validation has not been available until now. We provide the software tool NEEMP (http://ncbr.muni.cz/NEEMP), which offers three main functionalities: EEM parameterization [via linear regression (LR) and differential evolution with local minimization (DE-MIN)]; EEM parameter set validation (i.e., validation of coverage and quality) and EEM charge calculation. NEEMP functionality is shown using a parameterization and a validation case study. The parameterization case study demonstrated that LR is an appropriate approach for smaller and homogeneous datasets and DE-MIN is a suitable solution for larger and heterogeneous datasets. The validation case study showed that EEM parameter set coverage and quality can still be problematic. Therefore, it makes sense to verify the coverage and quality of EEM parameter sets before their use, and NEEMP is an appropriate tool for such verification. Moreover, it seems from both case studies that new EEM parameterizations need to be performed and new EEM parameter sets obtained with high quality and coverage for key structural databases. We provide the software tool NEEMP, which is to the best of our knowledge the only available software package that enables EEM parameterization and EEM parameter set validation. Additionally, its DE-MIN parameterization method is an innovative approach, developed by ourselves and first published in this work. In addition, we also prepared four high-quality EEM parameter sets tailored to ligand molecules.Graphical abstract.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 4 24%
Student > Ph. D. Student 3 18%
Student > Master 2 12%
Professor 2 12%
Lecturer 1 6%
Other 3 18%
Unknown 2 12%
Readers by discipline Count As %
Computer Science 5 29%
Chemistry 4 24%
Chemical Engineering 1 6%
Agricultural and Biological Sciences 1 6%
Biochemistry, Genetics and Molecular Biology 1 6%
Other 2 12%
Unknown 3 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 October 2016.
All research outputs
#16,388,648
of 24,143,470 outputs
Outputs from Journal of Cheminformatics
#808
of 891 outputs
Outputs of similar age
#203,662
of 320,159 outputs
Outputs of similar age from Journal of Cheminformatics
#24
of 26 outputs
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