Naslov
Electroanalytical characterization and determination of imidazole dipeptides carnosine and anserine

Autori
Jozanović, Marija ; Jakobović, Danijela ; Sakač, Nikola ; Sak-Bosnar, Milan

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
15th Ružička days "Today science - tomorrow industry" BOOK OF ABSTRACTS / Šubarić, Drago - , 2014

ISBN
978-953-6894-52-9

Skup
15th Ružička days "Today science - tomorrow industry"

Mjesto i datum
Vukovar, Hrvatska, 11.09.2014. - 12.09.2014

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
carnosine ; anserine ; titrations ; potentiometry

Sažetak
Carnosine and anserine are dipeptides that are contained in the skeletal muscles or brains of vertebrates in high concentrations. These substances may function to reduce muscle fatigue and improve learning ability because of an anti-oxidative effect and buffering capacity due to the presence of an imidazole group. L- Carnosine (ß-alanyl-L-histidine) is a dipeptide composed of ß-alanine and L- histidine, which performs multiple biological functions including pH buffering, anti- oxidation, anti- glycation, ant-aging, and chelation of divalent metal cations [1]. Anserine (ß-alanyl-N- methylhistidine) is an N- methylated analogue of carnosine found mainly in fish and birds. Anserine has similar properties to carnosine in many aspects but is mainly found in non- mammalian species. Carnosine and anserine can be determined in biological materials by means of HPLC using fluorescent [2] and electrochemical detection [3], capillary electrophoresis [4] and microchip electrophoresis [5]. In these investigations carnosine and anserine were potentiometrically studied, single and in a mixture. Their acid- base properties were studied by use of potentiometric titrations that were carried out in aqueous and nonaqueous solvents. The generated potentiometric data were used for defining buffering capacities (buffer strength) of both dipeptides and for determination of the corresponding species distribution diagrams. The experimental data were compared with an appropriate theoretical curve in which the unknown properties (sample concentration, dissociation constant) are optimized. By using Solver (Excel), the values for those variables can be found that minimize the sum of the squares of the differences between the theoretical and experimental curve by using the least-squares criterion to fit a theoretical curve to the experimental data [6].

Izvorni jezik
Engleski

Znanstvena područja
Kemija

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