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Metal-Ion Selectivity from Quantum-Chemical Perspective
Gutten, Ondrej ; Rulíšek, Lubomír (advisor) ; Dudev, Todor (referee) ; Baldauf, Carsten (referee)
Metal ions are a tempting tool for organisms thanks to the diversity of func- tions they have to offer, if they can be distinguished properly. Examining metal-ion selectivity computationally is challenging mainly due to complex- ity of electronic structure and solvation effects. A DFT-based protocol for predicting metal-ion selectivity of metal-binding systems was developed. The most essential part of the thesis is discussion of the magnitudes and sources of inherent errors, both for metal-ion complexes and small peptides. The thesis connects the work of four original papers. It includes computational and ex- perimental benchmarks, a case-study validating the computational protocol for obtaining energetic and structural insights, and attempts applying the protocol to peptidic systems. ii
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Modelling of the interaction of proteins and peptides with metal ions
Gutten, Ondrej ; Konvalinka, Jan (advisor) ; Obšil, Tomáš (referee)
Modelling of interactions of proteins and peptides with metal ions Ondrej Gutten - Diploma thesis Keywords: Metalloproteins, metal ion selectivity, in silico prediction Abstract: An approach for in silico prediction and estimation of selectivity properties of metal-binding peptides is suggested. An in-depth analysis is performed to disclose the justifiability and limitations of this approach. The study is divided into three parts. First part investigates the soundness of two quantum chemical methods (MP2 and DFT) for their use in the set-up quest. The testing includes comparison with CCSD(T), effect of basis selection, performance of the two methods in geometry optimizations and effect of implicit solvent model. Second part foreshadows the approach of searching for a metal selective peptide by thoroughly investigating the ability of simple representative systems, derived from their metalloprotein templates, to retain the property of interest. Final part describes the initial step of extensive combinatorial approach towards examination of vast number of simple systems that represent metal-binding sites, and which are to be used for prediction of metal-selectivity through exploitation of the described approach and, ultimately, to the de novo design of metalloproteins with desired properties.
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Metal-Ion Selectivity from Quantum-Chemical Perspective
Gutten, Ondrej ; Rulíšek, Lubomír (advisor) ; Dudev, Todor (referee) ; Baldauf, Carsten (referee)
Metal ions are a tempting tool for organisms thanks to the diversity of func- tions they have to offer, if they can be distinguished properly. Examining metal-ion selectivity computationally is challenging mainly due to complex- ity of electronic structure and solvation effects. A DFT-based protocol for predicting metal-ion selectivity of metal-binding systems was developed. The most essential part of the thesis is discussion of the magnitudes and sources of inherent errors, both for metal-ion complexes and small peptides. The thesis connects the work of four original papers. It includes computational and ex- perimental benchmarks, a case-study validating the computational protocol for obtaining energetic and structural insights, and attempts applying the protocol to peptidic systems. ii
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Modelling of the interaction of proteins and peptides with metal ions
Gutten, Ondrej ; Konvalinka, Jan (advisor) ; Obšil, Tomáš (referee)
Modelling of interactions of proteins and peptides with metal ions Ondrej Gutten - Diploma thesis Keywords: Metalloproteins, metal ion selectivity, in silico prediction Abstract: An approach for in silico prediction and estimation of selectivity properties of metal-binding peptides is suggested. An in-depth analysis is performed to disclose the justifiability and limitations of this approach. The study is divided into three parts. First part investigates the soundness of two quantum chemical methods (MP2 and DFT) for their use in the set-up quest. The testing includes comparison with CCSD(T), effect of basis selection, performance of the two methods in geometry optimizations and effect of implicit solvent model. Second part foreshadows the approach of searching for a metal selective peptide by thoroughly investigating the ability of simple representative systems, derived from their metalloprotein templates, to retain the property of interest. Final part describes the initial step of extensive combinatorial approach towards examination of vast number of simple systems that represent metal-binding sites, and which are to be used for prediction of metal-selectivity through exploitation of the described approach and, ultimately, to the de novo design of metalloproteins with desired properties.
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