Detailed Information on Publication Record
2015
Accurate Fitting SAXS Curves with NMR Structure Ensembles
KŘENEK, Aleš, Karel KUBÍČEK, Richard ŠTEFL and Jiří FILIPOVIČBasic information
Original name
Accurate Fitting SAXS Curves with NMR Structure Ensembles
Authors
KŘENEK, Aleš (203 Czech Republic, guarantor, belonging to the institution), Karel KUBÍČEK (203 Czech Republic, belonging to the institution), Richard ŠTEFL (203 Czech Republic, belonging to the institution) and Jiří FILIPOVIČ (203 Czech Republic, belonging to the institution)
Edition
Pissa, Proceedings of International Symposium on Grids and Clouds 2015, p. nestránkováno, 9 pp. 2015
Publisher
Proceedings of Science
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
10600 1.6 Biological sciences
Confidentiality degree
není předmětem státního či obchodního tajemství
Publication form
electronic version available online
References:
RIV identification code
RIV/00216224:14610/15:00083645
Organization unit
Institute of Computer Science
ISSN
Keywords (in Czech)
saxs; nmr; ensamble fit
Keywords in English
saxs; nmr; ensamble fit
Tags
Tags
International impact, Reviewed
Změněno: 27/4/2018 14:31, Mgr. Alena Mokrá
Abstract
V originále
Typical NMR analyses of a biomolecule yields a set of up to few dozens candidate 3D structures of the analyzed molecule without any clues to discriminate among them further. A parallel SAXS experiment on the same sample can be used for this purpose. Previous implementations of “ensemble fit” (search for a mix of molecular conformations which matches the SAXS curve) were designed to choose from a huge ensemble generated by molecular dynamics. Therefore the methods must trade off accuracy for manageable speed, and they end up in mixing curves computed with rather different values of parameters which have physical meaning, which should be avoided. On the contrary, with a relatively small input set of candidate NMR structures we take a more accurate approach. Both the model parameters, considered globally now, and weights of individ- ual candidate structures (reflecting their presence in the solution) become independent variables of a multidimensional global optimization problem; the optimized value is the accuracy of the fit to the experimental data. The optimization must escape from traps of many local minima there- fore we use Monte Carlo with stochastic tunnelling. The method also offers opportunities for parallelization. The final issue is user friendliness of the entire workflow, which is quite complex, involving several programs to be run, handling different file formats, and setting multiple parameters, ending up with visualization of results. We outline design of a web portal hiding these complexities to the end user.
Links
| MUNI/M/1038/2013, interní kód MU |
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