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Optimized SQE atomic charges for peptides accessible via a web application.
Schindler, Ondrej; Racek, Tomás; Marsavelski, Aleksandra; Koca, Jaroslav; Berka, Karel; Svobodová, Radka.
Afiliación
  • Schindler O; CEITEC-Central European Institute of Technology, Masaryk University, Kamenice 5, 602 00, Brno, Czech Republic.
  • Racek T; National Centre for Biomolecular Research, Faculty of Science, Masaryk University, Kamenice 5, 625 00, Brno, Czech Republic.
  • Marsavelski A; CEITEC-Central European Institute of Technology, Masaryk University, Kamenice 5, 602 00, Brno, Czech Republic.
  • Koca J; National Centre for Biomolecular Research, Faculty of Science, Masaryk University, Kamenice 5, 625 00, Brno, Czech Republic.
  • Berka K; Faculty of Informatics, Masaryk University, Botanická 68a, 602 00, Brno, Czech Republic.
  • Svobodová R; Division of Biochemistry, Department of Chemistry, Faculty of Science, University of Zagreb, Horvatovac 102a, 10000, Zagreb, Croatia.
J Cheminform ; 13(1): 45, 2021 Jun 30.
Article en En | MEDLINE | ID: mdl-34193251
ABSTRACT

BACKGROUND:

Partial atomic charges find many applications in computational chemistry, chemoinformatics, bioinformatics, and nanoscience. Currently, frequently used methods for charge calculation are the Electronegativity Equalization Method (EEM), Charge Equilibration method (QEq), and Extended QEq (EQeq). They all are fast, even for large molecules, but require empirical parameters. However, even these advanced methods have limitations-e.g., their application for peptides, proteins, and other macromolecules is problematic. An empirical charge calculation method that is promising for peptides and other macromolecular systems is the Split-charge Equilibration method (SQE) and its extension SQE+q0. Unfortunately, only one parameter set is available for these methods, and their implementation is not easily accessible.

RESULTS:

In this article, we present for the first time an optimized guided minimization method (optGM) for the fast parameterization of empirical charge calculation methods and compare it with the currently available guided minimization (GDMIN) method. Then, we introduce a further extension to SQE, SQE+qp, adapted for peptide datasets, and compare it with the common approaches EEM, QEq EQeq, SQE, and SQE+q0. Finally, we integrate SQE and SQE+qp into the web application Atomic Charge Calculator II (ACC II), including several parameter sets.

CONCLUSION:

The main contribution of the article is that it makes SQE methods with their parameters accessible to the users via the ACC II web application ( https//acc2.ncbr.muni.cz ) and also via a command-line application. Furthermore, our improvement, SQE+qp, provides an excellent solution for peptide datasets. Additionally, optGM provides comparable parameters to GDMIN in a markedly shorter time. Therefore, optGM allows us to perform parameterizations for charge calculation methods with more parameters (e.g., SQE and its extensions) using large datasets.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Cheminform Año: 2021 Tipo del documento: Article País de afiliación: República Checa

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Cheminform Año: 2021 Tipo del documento: Article País de afiliación: República Checa