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Detection of Related Proteins with Modified Function
Hon, Jiří ; Bendl, Jaroslav (referee) ; Martínek, Tomáš (advisor)
Protein engineering is a young dynamic discipline with great amount of potential practical applications. However, its success is primarily based on perfect knowledge and usage of all existing information about protein function and structure. To achieve that, protein engineering is supported by plenty of bioinformatic tools and analysis. The goal of this project is to create a new tool for protein engineering that would enable researchers to identificate related proteins with modified function in still growing biological databases. The tool is designed as an automated workflow of existing bioinformatic analyses that leads to identification of proteins with the same type of enzymatic function, but with slightly modified properties - primarily in terms of selectivity, reaction speed and stability.
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Bioinformatic Tool for Estimation of Abundances of Bacterial Functional Molecules in Biological Samples Based on 16S rRNA Metagenomic Data
Bieliková, Michaela ; Hon, Jiří (referee) ; Smatana, Stanislav (advisor)
Ľudské telo je prostredím pre život neuveriteľného množstva mikróbov. Niektoré z nich môžu spôsobovať rôzne choroby, ale ďalšie, napríklad črevný mikrobióm, sú pre život a zdravie človeka nepostrádateľné. Nanešťastie, črevný mikrobióm nie je detailne preštudovaný, pretože obsahuje tisíce rôznych druhov baktérií, z ktorých väčšina sa nedá kultivovať v laboratórnych podmienkach. Riešením tohto problému sú nové rýchle metódy sekvenovania v kombináciou s bioinformatickými nástrojmi na výpočet funkčného profilu baktérií vo vzorke. V tejto práci si predstavíme existujúce nástroje predpovedajúce funkčný profil, a následne navrhneme nový nástroj, ktorý môže implementovať konsenzus nad výsledkami existujúcich nástrojov, alebo sa môže jednať o úplne nový nástroj.
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Prediction of the Effect of Mutation on Protein Solubility
Marko, Július ; Smatana, Stanislav (referee) ; Hon, Jiří (advisor)
Protein solubility is a key problem in production of functional proteins. Prediction of the effect of mutation on protein solubility could save a lot of time and money, as it would provide in silico prediction of solubility enhancing mutations before performing deep mutational scanning in laboratory. In this work, new predictor of the effect of mutation on protein solubility SoluProtMut is introduced that is based on machine learning methods. Most of the existing predictors predict the effect from the amino acid sequence. In addition to the sequence, the tool presented in this work also uses the spatial structure of the protein, which can significantly increase it's accuracy.
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Optimization of G-Quadruplex Identification Algorithm
Labudová, Dominika ; Martínek, Tomáš (referee) ; Hon, Jiří (advisor)
Identification of G-quadruplexes in DNA has been the interest of many studies in recent years. As a result, many identification tools were created. This bachelor's thesis focuses on analysis and optimization of a tool called pqsfinder along with creating a web interface for this tool. The optimization provided significant increase in the algorithm's speed and ability to process long DNA sequences. The web interface was designed and implemented using modern and effective technologies with emphasis on the user friendliness of the web application.
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Mining of soluble enzymes from genomic databases
Hon, Jiří ; Brejová, Bronislava (referee) ; Šafránek, David (referee) ; Zendulka, Jaroslav (advisor)
Enzymy jsou proteiny urychlující chemické reakce s velkým potenciálem pro farmaceutický a obecně chemický průmysl. Enzymatická funkce je obvykle zajištěna několika nepostradatelnými aminokyselinami, které tvoří tzv. aktivní místo, kde se odehrává chemická reakce. V této práci jsou prezentovány dva integrované softwarové nástroje pro dolování a racionální výběr nových rozpustných enzymů - EnzymeMiner a SoluProt. EnzymeMiner slouží k hledání nových enzymů. Na vstupu vyžaduje jednu nebo více sekvencí zvoleného enzymu spolu se seznamem klíčových aminokyselin. Tento seznam slouží k zvýšení pravděpodobnosti, že nalezený enzym bude mít podobnou funkci jako vstupní enzym. Výstupem EnzymeMineru je množina anotovaných sekvencí nalezených v databázi. Za účelem ulehčení výběru několika málo kandidátů pro experimentální ověření v laboratoři integruje EnzymeMiner anotace z dostupných databází - informaci o zdrojovém organismu a prostředí, ve kterém se vyskytuje, a informaci o proteinových doménách, ze kterých se enzym skládá. Hlavním kritériem pro výběr kandidátů je rozpustnost predikovaná druhým prezentovaným nástrojem, SoluProtem. SoluProt je metoda založená na strojovém učení, která predikuje heterologní rozpustnou expresi proteinu v organismu Escherichia coli . Vstupem je sekvence a výstupem je pravděpodobnost, že protein bude exprimován v rozpustné formě. SoluProt využívá model gradient boosting machine a byl trénován na datové sadě odvozené od databáze TargetTrack. Při srovnání na vyvážené nezávislé datové sadě odvozené z databáze NESG dosáhl SoluProt přesnosti 58,5 % a hodnoty AUC 0,62, čímž lehce převyšuje ostatní existující nástroje. Nástroje EnzymeMiner i SoluProt jsou často využívány řadou uživatelů z oblasti proteinového inženýrství za účelem hledání nových rozpustných biokatalyzátorů chemických reakcí. Ty mají velký potenciál snížit energetickou náročnost a ekologickou zátěž mnoha průmyslových procesů.
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Bacteria Classification Based on Marker Genes
Pelantová, Lucie ; Hon, Jiří (referee) ; Smatana, Stanislav (advisor)
The aim of this work is proposal of new method for bacteria classification based on sequences of marker genes. For this purpose was chosen 10 marker genes. Resulting MultiGene classifier processes data set by dividing it in several groups and choosing gene for each group which can distinguish this group with best results. This work describes implementation of MultiGene classifier and its results in comparison with other bacteria classifiers and with classification based entirely on gene 16S rRNA.
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Prediction of the Effect of Mutation on Protein Solubility
Velecký, Jan ; Martínek, Tomáš (referee) ; Hon, Jiří (advisor)
The goal of the thesis is to create a predictor of the effect of a mutation on protein solubility given its initial 3D structure. Protein solubility prediction is a bioinformatics problem which is still considered unsolved. Especially a prediction using a 3D structure has not gained much attention yet. A relevant knowledge about proteins, protein solubility and existing predictors is included in the text. The principle of the designed predictor is inspired by the Surface Patches article and therefore it also aims to validate the results achieved by its authors. The designed tool uses changes of positive regions of the electric potential above the protein's surface to make a prediction. The tool has been successfully implemented and series of computationally expensive experiments have been performed. It was shown that the electric potential, hence the predictor itself too, can be successfully used just for a limited set of proteins. On top of that, the method used in the article correlates with a much simpler variable - the protein's net charge.
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Bacteria Classification into Taxonomic Categories Based on Properties of 16s rRNA
Grešová, Katarína ; Hon, Jiří (referee) ; Smatana, Stanislav (advisor)
The main goal of this thesis was to design and implement a tool that would be able to classify the sequences of the 16S rRNA gene into taxonomic categories using the properties of the 16S rRNA gene. The created tool analyzes all input sequences simultaneously, which differs from common classification approaches, which classify input sequences individually. This tool relies on the fact that bacteria contain several copies of the 16S rRNA gene, which may differ in sequence. The main contribution of this work is design, implementation and evaluation of the capabilities of this tool. Experiments have shown that the proposed tool is able to identify the corresponding bacteria for smaller datasets and determine the correct ratios of their abundances. However, with larger datasets, the state space becomes very large and fragmented, which requires further improvements in order for it to search the state space in an efficient way.
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Prediction of the Effect of Mutation on Protein Solubility
Marko, Július ; Smatana, Stanislav (referee) ; Hon, Jiří (advisor)
Protein solubility is a key problem in production of functional proteins. Prediction of the effect of mutation on protein solubility could save a lot of time and money, as it would provide in silico prediction of solubility enhancing mutations before performing deep mutational scanning in laboratory. In this work, new predictor of the effect of mutation on protein solubility SoluProtMut is introduced that is based on machine learning methods. Most of the existing predictors predict the effect from the amino acid sequence. In addition to the sequence, the tool presented in this work also uses the spatial structure of the protein, which can significantly increase it's accuracy.
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Search of Related Enzymes
Borko, Simeon ; Smatana, Stanislav (referee) ; Hon, Jiří (advisor)
Millions of new proteins discovered each year cannot be characterized by classical biochemical methods due to their demands of time and cost. Among the unexplored proteins, there may be enzymes useful in both industry and academy, mostly for ecological production of chemical compounds. The result of the thesis is a web application which, based on the input proteins, searches the database for similar proteins. The proteins are filtered using essential residues of the input proteins and marked as putative biocatalysts. Finally, the proteins are annotated so that the user can make an informed decision about which proteins to select for experimental laboratory verification. The developed tool facilitates multi-step analysis and recommends proteins for experimental verification of their enzymatic function. The web interface is freely available at https://loschmidt.chemi.muni.cz/enzymeminer/. The tool was published in the international journal Nucleic Acids Research.
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