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Prediction of ligand binding sites from protein structure
Krivák, Radoslav ; Hoksza, David (advisor) ; Berka, Karel (referee) ; Brezovský, Jan (referee)
Ligand binding site prediction from protein structure is a fundamental prob- lem in the field of structural bioinformatics that has many applications related to the elucidation of protein function and structure-based drug discovery. The first focus of this thesis was the application of machine learning to this and related problems. The second focus was the development of practically usable tools based on our research. The machine learning based tools produced as a result of the work on this thesis include the pocket re-scoring method PRANK, a stand-alone ligand binding site prediction method P2Rank (together with its extended web interface PrankWeb) and the peptide binding prediction method P2Rank-Pept. We have shown that our methods outperformed available state- of-the-art tools while providing other benefits like prediction speed and stability. Furthermore, we have developed AHoJ, a flexible tool for the search and align- ment of Apo-Holo protein pairs in the PDB. AHoJ that is ideal for creating Apo-Holo datasets which can in turn help to better evaluate binding site pre- diction methods in the future. 1
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Development and analysis of a database of reactions catalyzed by cytochrome P450 enzymes for machine learning applications
Komorníková, Natália ; Pluskal, Tomáš (advisor) ; Berka, Karel (referee)
Cytochrome P450 enzymes are hemoproteins showing extraordinary di- versity in the reactions they catalyze. We developed a database containing all the needed data to provide a comprehensive data source on reactions cat- alyzed by cytochrome P450 enzymes. This data mainly includes information about the substrates, products of characterized reactions, and the sequence of these enzymes. The database was developed by collecting data from reliable protein and reaction databases like UniProt and RHEA. The work presents an in-depth analysis of the created database of reactions catalyzed by cy- tochrome P450 enzymes. This database can be utilized for future machine learning approaches to predict the function of uncharacterized cytochrome P450s.
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Computational Studies of Interactions of Small Molecules with their Biological Targets
Nekardová, Michaela ; Hobza, Pavel (advisor) ; Berka, Karel (referee) ; Kabeláč, Martin (referee)
The thesis specializes in the computational description of pharmaceutically important compounds. A substantial number of pharmaceutical drugs are small molecules that are bound to an active site of an enzyme by the "lock (binding site) and key (drug)" model through non-covalent interactions. The association of enzymes with drugs cause an increase or decrease in the activity of enzymes. The main topic is focused on the computational elucidation of the structural basis for the interactions of the purine-like compounds with the enzyme cyclin- dependent kinase 2 that belongs to the protein-kinase enzyme family. These enzymes play an important role in the cell cycle regulation; their increased activity significantly contributes to the loss of control over cell proliferation, which is one of the primary causes of cancer cell formation. The study describes the binding motifs of roscovitine, which shows an inhibitory effect on the function of cyclin-dependent kinases, and its analogues containing bioisosteric central heterocycles in the complex with cyclin-dependent kinase 2. The binding affinity between the cyclin-dependent kinase 2 enzyme and the inhibitors was quantified as calculated binding scores and evaluated in relation to the conformation of the optimized structures. The hybrid model combining the...
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Interaction preferences in protein - DNA complexes
Jakubec, Dávid ; Vondrášek, Jiří (advisor) ; Berka, Karel (referee)
Interaction preferences in protein - DNA complexes Dávid Jakubec Abstract Interactions of proteins with DNA lie at the basis of many fundamental bio- logical processes. Despite ongoing efforts, the rules governing the recognition of specific nucleic acid sequences have still not been universally elucidated. In this work, I attempt to explore the recognition process by splitting the intricate network of contacts at the protein - DNA interface into contribu- tions of individual amino acid - nucleotide pairs. These pairs are extracted from existing high-resolution structures of protein - DNA complexes and in- vestigated by bioinformatics and computational-chemistry based methods. Criteria of specificity based on the coupling of observed geometrical prefer- ences and the respective interaction energies are introduced. The application of these criteria is used to expand the library of amino acid - nucleotide pairs potentially significant for direct sequence recognition. Electrostatic poten- tial maps are calculated for individual nucleotides as well as for selected complexes to investigate the physical basis of the observed specificity. 1
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Computational Studies of Interactions of Small Molecules with their Biological Targets
Nekardová, Michaela ; Hobza, Pavel (advisor) ; Berka, Karel (referee) ; Kabeláč, Martin (referee)
The thesis specializes in the computational description of pharmaceutically important compounds. A substantial number of pharmaceutical drugs are small molecules that are bound to an active site of an enzyme by the "lock (binding site) and key (drug)" model through non-covalent interactions. The association of enzymes with drugs cause an increase or decrease in the activity of enzymes. The main topic is focused on the computational elucidation of the structural basis for the interactions of the purine-like compounds with the enzyme cyclin- dependent kinase 2 that belongs to the protein-kinase enzyme family. These enzymes play an important role in the cell cycle regulation; their increased activity significantly contributes to the loss of control over cell proliferation, which is one of the primary causes of cancer cell formation. The study describes the binding motifs of roscovitine, which shows an inhibitory effect on the function of cyclin-dependent kinases, and its analogues containing bioisosteric central heterocycles in the complex with cyclin-dependent kinase 2. The binding affinity between the cyclin-dependent kinase 2 enzyme and the inhibitors was quantified as calculated binding scores and evaluated in relation to the conformation of the optimized structures. The hybrid model combining the...
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Influence of phosphorylation on the conformation of peptides and proteins
Jurásková, Veronika ; Vondrášek, Jiří (advisor) ; Berka, Karel (referee)
Title: Influence of phosphorylation on the conformation of peptides and proteins Author: Ing. Veronika Jurásková Department: Department of Physical and Macromolecular Chemistry Supervisor: RNDr. Jiří Vondrášek, CSc. Consultant: Mgr. Jiří Vymětal, PhD. Abstract: The aim of the thesis was to study the effect of phosphorylation on the conformation of peptides and proteins. I focused on three amino acids which are phos- phorylated the most - serine, threonine and tyrosine. I studied the conformational changes upon phosphorylation in dipeptides and pentapeptides by the metadynamics technique. I found out that the phosphorylation of amino acid residues led to the conformational changes characteristic for each amino acid. Whereas the phosphoryla- tion of serine increased the preference of right-handed alpha helix conformation, the phosphorylation of threonine led to the extended structure and the conformation of tyrosine was not influenced by phosphorylation at all. Using classical molecular dy- namics, I also studied the conformational changes in longer peptides derived from the phosphorylation sites of disordered proteins. Moreover, I simulated phosphorylated and unphosphorylated variants of three proteins with a known structure from the RCSB PDB database. I compared the calculated results with available...
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