Quantum chemistry and conformational sampling meet together : a powerful approach to study and design metalloprotein reactivity

Metalloprotein are proteins containing metal ion cofactors. Compared to chemical catalysts, metalloproteins have a well-defined configuration around the active site which ensures higher specificity, selectivity and reaction rates. Metalloproteins are soluble in water, their function can be optimized...

Descripción completa

Detalles Bibliográficos
Autor: Monza, Emanuele
Tipo de recurso: tesis doctoral
Fecha de publicación:2016
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/106489
Acceso en línea:https://hdl.handle.net/2117/106489
https://dx.doi.org/10.5821/dissertation-2117-106489
Access Level:acceso abierto
Palabra clave:QM/MM
PELE
Computational protein design
In silico enzyme engineering
Laccases
Hemoglobin
Oxidoreductases
Allostery
Cooperativity
Biocatalysis
Àrees temàtiques de la UPC::Física
Descripción
Sumario:Metalloprotein are proteins containing metal ion cofactors. Compared to chemical catalysts, metalloproteins have a well-defined configuration around the active site which ensures higher specificity, selectivity and reaction rates. Metalloproteins are soluble in water, their function can be optimized genetically by modifying an host (e.g. a bacteria) and are biodegradable. Therefore, they are ideal templates for the creation of novel green catalysts and therapeutics. Nonetheless, metalloproteins, as found in nature, are usually not ready for industrial scale-up and may need to be re-designed. Molecular simulations can guide the search for new metalloprotein functionality, cutting the costs of the experimental work. Modeling metalloproteins' function requires the sampling of both the electronic and nuclear degrees of freedom to exhaustively describe their chemical reactivity. The combination of conformational sampling and quantum chemical technique allows to model how they catalyze a reaction or covalently bind a ligand, without missing information about the dynamics of the whole protein. In this thesis, these computational techniques are systematically employed to study and guide present and future design efforts of laccases and hemoglobin. Laccases are copper-containing oxidoreductases that can oxidize a large variety of substrates at expenses of oxygen, which is reduced to water. Therefore, their interest in green chemistry applications: they work with air and produce water as sole by-product. So far, most efforts made to enlarge the chemical space of laccases have focused on increasing the redox potential of the first copper-based electron acceptor, a choice that yielded limited success. Here, it is proposed to focus on the desired substrate, modeling the active site of laccases to better fit and oxidize it. To do so, a computational protocol was developed, based on Monte Carlo sampling of the enzyme-substrate conformational space, followed by quick quantum chemical calculations to score oxidation. The protocol was first validated against experimental data, proving its capability to reproduce data and provide a rationale to laccases functioning. This new tool was then used to improve the oxidation of aniline by a laccase by simulating the effect of certain mutations (amino acid substitutions) which were tested in the lab by our collaborators. As a result, the design mutations significantly improved the oxidation of aniline (which leads to the formation of polyaniline, an organic semiconductor). Another design was carried out which lead to a significant improvement in activity of another laccase toward three different substrates. Therefore, the methodology developed proved to be capable of reproducing and rationalizing experimental results and rendering a la carte design of laccases toward a given (class of) substrates possible. A similar protocol, which uses an empirical computational method instead of quantum chemical techniques, was used to selectively attach a photosensitizer (a molecule that produces a chemical change in another molecule in a photochemical process) to the surface of a laccase. Hemoglobin, a heme-containing protein that carries oxygen from the lungs to the tissue in the body, is a candidate for blood substituent design. However, its design is rendered difficult by the limited knowledge of its functioning. Here, a mixed Monte Carlo-quantum chemical approach was used to support a theory about hemoglobin's allosteric mechanism and structurally characterize the tertiary end-states of the allosteric transition for the first time. These calculations, which were benchmarked against available experimental data, disclosed the role of the amino acids next to the oxygen binding site. This information was used in a subsequent molecular dynamics study which showed how the four subunits of hemoglobin give rise the allosteric response, highlighting the signalling paths and their hierarchy