PAZÚRIKOVÁ, Jana, Aleš KŘENEK and Luděk MATYSKA. Guided Optimization Method for Fast and Accurate Atomic Charges Computation. In José Évora-Gómez and José Juan Hernandéz-Cabrera. Proceedings of the 2016 European Simulation and Modelling Conference. Ghent, Belgicko: EUROSIS - ETI, 2016. p. 267-274. ISBN 978-90-77381-95-3.
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Original name Guided Optimization Method for Fast and Accurate Atomic Charges Computation
Authors PAZÚRIKOVÁ, Jana (703 Slovakia, guarantor, belonging to the institution), Aleš KŘENEK (203 Czech Republic, belonging to the institution) and Luděk MATYSKA (203 Czech Republic, belonging to the institution).
Edition Ghent, Belgicko, Proceedings of the 2016 European Simulation and Modelling Conference, p. 267-274, 8 pp. 2016.
Publisher EUROSIS - ETI
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Belgium
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
RIV identification code RIV/00216224:14330/16:00091643
Organization unit Faculty of Informatics
ISBN 978-90-77381-95-3
Keywords in English optimization problem; computational chemistry; atomic charges; local vs. global optimization
Tags firank_B
Tags International impact, Reviewed
Changed by Changed by: Mgr. Aleš Křenek, Ph.D., učo 3086. Changed: 30/11/2016 10:54.
Abstract
Current advances in hardware and algorithm develop- ment allow the life science researchers to replace the experiment with a computer simulation. A key ob- ject of these computations is a molecule - a group of atoms interconnected via a cloud of electrons. For its computational processing, electrons around the atom are often represented by one number: partial atomic charge. It can be calculated by quantum mechan- ics (QM), which offers high accuracy at the cost of long computation time, or markedly faster by empirical methods such as Electronegativity Equalization Method (EEM). Empirical methods calibrate their parameters to the particular QM charge calculation approach by multi-dimensional optimization procedure. This work systematically summarizes and compares the accuracy and computational performance of available EEM pa- rameterization approaches with local, global or com- bined optimization (least squares, evolutionary and ge- netic algorithms). Moreover, we propose a new method- ology called guided minimization. We found that local optimization plays a crucial role in the parametrization, and only methodologies combining a global and a lo- cal optimization provide high-quality EEM parameters. Furthermore, we observed that global iterations of evo- lutionary of genetic algorithm often do not contribute to the result. Therefore, we reduced the global search method to guided minimization that achieves same or better accuracy than state-of-the-art methods and sur- passes them with simplicity and speed.
Links
LM2015085, research and development projectName: CERIT Scientific Cloud (Acronym: CERIT-SC)
Investor: Ministry of Education, Youth and Sports of the CR, Large Infrastructures for Research, Development and Innovation
MUNI/A/0945/2015, internal MU codeName: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace V.
Investor: Masaryk University, Grant Agency of Masaryk University, Category A
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