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Adsorption of Native Amino Acids on Nanocrystalline TiO2: Physical Chemistry, QSPR, and Theoretical Modeling
- Source :
- RUO. Repositorio Institucional de la Universidad de Oviedo, instname
- Publication Year :
- 2018
- Publisher :
- American Chemical Society (ACS), 2018.
-
Abstract
- The affinity of biomolecules, such as peptides and proteins, with inorganic surfaces, is a fundamental topic in biotechnology and bionanotechnology. Amino acids are often used as “model” bits of peptides or proteins for studying their properties in different environments and/or developing functional surfaces. Despite great demand for knowledge about amino acid interactions with metal oxide surfaces, studies on the issue represent a fragmentary picture. In this paper, we describe amino acid adsorption on nanocrystalline anatase systematically at uniform conditions. Analysis of the Gibbs free adsorption energy indicated how the aliphatic, aromatic, polar, and charged side chain groups affect the binding affinity of the amino acids. Thermodynamic features of the L-amino acid adsorption receive thorough interpretation with calculated molecular descriptors. Theoretical modelling shows that amino acids complex with TiO2 nanoparticles as zwitterions via ammonium group.<br />This work was financially supported by the Russian Foundation for Basic Research (grant no. 15-03-07834-a). I.K. acknowledge the financial support from Spanish MINECO (CTQ2014-52956-C3-1-R and MAT2016-78155-C2-1-R).
- Subjects :
- Quantitative structure–activity relationship
02 engineering and technology
010402 general chemistry
01 natural sciences
symbols.namesake
Adsorption
Computational chemistry
Molecular descriptor
Electrochemistry
Side chain
Nanobiotechnology
titania
General Materials Science
Spectroscopy
chemistry.chemical_classification
Chemistry
Biomolecule
Surfaces and Interfaces
021001 nanoscience & nanotechnology
Condensed Matter Physics
proteins
0104 chemical sciences
Gibbs free energy
Amino acid
adsorption
symbols
0210 nano-technology
Subjects
Details
- ISSN :
- 15205827 and 07437463
- Volume :
- 35
- Database :
- OpenAIRE
- Journal :
- Langmuir
- Accession number :
- edsair.doi.dedup.....0117289bb1e82eac4b3598e155c72d05
- Full Text :
- https://doi.org/10.1021/acs.langmuir.8b02007