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Computational Design of Stable Proteins
Musil, Miloš ; Lexa, Matej (oponent) ; Vinař, Tomáš (oponent) ; Zendulka, Jaroslav (vedoucí práce)
Stable proteins are utilized in a vast number of medical and biotechnological applications. However, the native proteins have mostly evolved to function under mild conditions inside the living cells. As a result, there is a great interest in increasing protein stability to enhance their utility in the harsh industrial conditions. In recent years, the field of protein engineering has matured to the point that enables tailoring of native proteins for specific practical applications. However, the identification of stable mutations is still burdened by costly and laborious experimental work. Computational methods offer attractive alternatives that allow a rapid search of the pool of potentially stabilizing mutations to prioritize them for further experimental validation. A plethora of the computational strategies was developed: i) force-field-based energy calculations, ii) evolution-based techniques, iii) machine learning, or iv) the combination of several approaches. Those strategies are usually limited in their predictions to less impactful single-point mutations, while some more sophisticated methods for prediction of multiple-point mutations require more complex inputs from the side of the user. The main aim of this Thesis is to provide users with a fully automated workflow that would allow for the prediction of the highly stable multiple-point mutants without the requirement of the extensive knowledge of the bioinformatics tools and the protein of interest. FireProt is a fully automated workflow for the design of the highly stable multiple-point mutants. It is a hybrid method that combines both energy- and evolution-based approaches in its calculation core, utilizing sequence information as a filter for robust force-field calculations. FireProt workflow not only detects a pool of potentially stabilizing mutations but also tries to combine them together while reducing the risk of antagonistic effects. FireProt-ASR is a fully automated workflow for ancestral sequence reconstruction, allowing users to utilize this protein engineering strategy without the need for the laborious manual work and the knowledge of the system of interest. It resolves all the steps required during the process of ancestral sequence reconstruction, including the collection of the biologically relevant homologs, construction of the rooted tree, and the reconstruction of the ancestral sequences and ancestral gaps.HotSpotWizard is a workflow for the automated design of mutations and smart libraries for the engineering of protein function and stability. It allows for a wider analysis of the protein of interest by utilizing four different protein engineering strategies: i) identification of the highly mutable residues located in the catalytic pockets and tunnels, ii) identification of the flexible regions, iii) calculation of the sequence consensus, and iv) identification of the correlated residues.FireProt-DB is a database of the known experimental data quantifying a protein stability. The main aim of this database is to standardize protein stability data, provide users with well-manageable storage, and allow them to construct protein stability datasets to use them as training sets for various machine learning applications.
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Vyhledávání přibližných palindromů v DNA sekvencích
Divila, Jaroslav ; Lexa, Matej (oponent) ; Martínek, Tomáš (vedoucí práce)
Tato práce se zabývá návrhem a implementací nástroje pro vyhledávání přibližných palindromů v sekvencích DNA. Zaměřuje se na popis DNA struktury, významu palindromů v DNA sekvencích a na popis metod pro vyhledávání přibližných palindromů. Hlavní část práce je zaměřena na návrh a popis implementace nástroje pro vyhledávání přibližných palindromů.
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Reconstruction of Repetitive DNA Segments
Bikár, Robert ; Lexa, Matej (oponent) ; Martínek, Tomáš (vedoucí práce)
The main motivation for master's thesis is to find suitable algorithm that creates a graph representation of NGS sequencing data in linear time. De Bruijn graph was chosen as a method for research. Next, the tool was designed to be able to transform the graph and correct errors created during construction of the graph. The main aim of the thesis is to implement a tool that reconstructs repetitive segments in DNA. Implemented tool was tested and is able to identify repetitive segments, specify types, visualize them properly and is also able to assemble their sequence with fine accuracy on simpler genomes. When using complex genomes, tool is able to reconstruct only fragments of repetitive segments.
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Methods for Comparative Analysis of Metagenomic Data
Sedlář, Karel ; Vinař,, Tomáš (oponent) ; Lexa, Matej (oponent) ; Provazník, Ivo (vedoucí práce)
Modern research in environmental microbiology utilizes genomic data, especially sequencing of DNA, to describe microbial communities. The field studying all genetic material present in an environmental sample is referred to as metagenomics. This doctoral thesis deals with metagenomics from the perspective of bioinformatics that is unreplaceable during the data processing. In the theoretical part of this thesis, two different approaches of metagenomics are described including their main principles and weaknesses. The first approach, based on targeted sequencing, is a well-established field with a wide range of bioinformatics techniques. Yet, methods for comparison of samples from several environments can be highly improved. The approach introduced in this thesis uses unique transformation of data into a bipartite graph, where one partition is formed by taxa, while the other by samples or environments. Such a graph fully reflects qualitative as well as quantitative aspect of analyzed microbial networks. It allows a massive data reduction to provide human comprehensible visualization without affecting the automatic community detection that can found clusters of similar samples and their typical microbes. The second approach utilizes whole metagenome shotgun sequencing. This strategy is newer and the corresponding bioinformatics techniques are less developed. The main challenge lies in fast clustering of sequences, in metagenomics referred to as binning. The method introduced in this thesis utilizes a genomic signal processing approach. By thorough analysis of redundancy of genetic information stored in genomic signals, a unique technique was proposed. The technique utilizes transformation of character sequences into several variants of phase signals. Moreover, it is able to directly process nanopore sequencing data in the form of a native current signal.
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Vyhledávání kvadruplexů v DNA sekvencích
Sečka, Martin ; Lexa, Matej (oponent) ; Martínek, Tomáš (vedoucí práce)
Tato diplomová práce se zabývá vyhledáváním, vizualizací a filtrací sekvencí potenciálně tvořících kvadruplexy v sekvencích DNA. Ve spolupráci s Biofyzikálním ústavem AV ČR byla za tímto účelem vytvořena webová aplikace, která využívá nový algoritmus pro hledání všech možných umístění kvadruplexů v rámci zadané sekvence. Návrh a implementace tohoto algoritmu jsou také součástí této práce.
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Computational Design of Stable Proteins
Musil, Miloš ; Lexa, Matej (oponent) ; Vinař, Tomáš (oponent) ; Zendulka, Jaroslav (vedoucí práce)
Stable proteins are utilized in a vast number of medical and biotechnological applications. However, the native proteins have mostly evolved to function under mild conditions inside the living cells. As a result, there is a great interest in increasing protein stability to enhance their utility in the harsh industrial conditions. In recent years, the field of protein engineering has matured to the point that enables tailoring of native proteins for specific practical applications. However, the identification of stable mutations is still burdened by costly and laborious experimental work. Computational methods offer attractive alternatives that allow a rapid search of the pool of potentially stabilizing mutations to prioritize them for further experimental validation. A plethora of the computational strategies was developed: i) force-field-based energy calculations, ii) evolution-based techniques, iii) machine learning, or iv) the combination of several approaches. Those strategies are usually limited in their predictions to less impactful single-point mutations, while some more sophisticated methods for prediction of multiple-point mutations require more complex inputs from the side of the user. The main aim of this Thesis is to provide users with a fully automated workflow that would allow for the prediction of the highly stable multiple-point mutants without the requirement of the extensive knowledge of the bioinformatics tools and the protein of interest. FireProt is a fully automated workflow for the design of the highly stable multiple-point mutants. It is a hybrid method that combines both energy- and evolution-based approaches in its calculation core, utilizing sequence information as a filter for robust force-field calculations. FireProt workflow not only detects a pool of potentially stabilizing mutations but also tries to combine them together while reducing the risk of antagonistic effects. FireProt-ASR is a fully automated workflow for ancestral sequence reconstruction, allowing users to utilize this protein engineering strategy without the need for the laborious manual work and the knowledge of the system of interest. It resolves all the steps required during the process of ancestral sequence reconstruction, including the collection of the biologically relevant homologs, construction of the rooted tree, and the reconstruction of the ancestral sequences and ancestral gaps.HotSpotWizard is a workflow for the automated design of mutations and smart libraries for the engineering of protein function and stability. It allows for a wider analysis of the protein of interest by utilizing four different protein engineering strategies: i) identification of the highly mutable residues located in the catalytic pockets and tunnels, ii) identification of the flexible regions, iii) calculation of the sequence consensus, and iv) identification of the correlated residues.FireProt-DB is a database of the known experimental data quantifying a protein stability. The main aim of this database is to standardize protein stability data, provide users with well-manageable storage, and allow them to construct protein stability datasets to use them as training sets for various machine learning applications.
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Methods for Comparative Analysis of Metagenomic Data
Sedlář, Karel ; Vinař,, Tomáš (oponent) ; Lexa, Matej (oponent) ; Provazník, Ivo (vedoucí práce)
Modern research in environmental microbiology utilizes genomic data, especially sequencing of DNA, to describe microbial communities. The field studying all genetic material present in an environmental sample is referred to as metagenomics. This doctoral thesis deals with metagenomics from the perspective of bioinformatics that is unreplaceable during the data processing. In the theoretical part of this thesis, two different approaches of metagenomics are described including their main principles and weaknesses. The first approach, based on targeted sequencing, is a well-established field with a wide range of bioinformatics techniques. Yet, methods for comparison of samples from several environments can be highly improved. The approach introduced in this thesis uses unique transformation of data into a bipartite graph, where one partition is formed by taxa, while the other by samples or environments. Such a graph fully reflects qualitative as well as quantitative aspect of analyzed microbial networks. It allows a massive data reduction to provide human comprehensible visualization without affecting the automatic community detection that can found clusters of similar samples and their typical microbes. The second approach utilizes whole metagenome shotgun sequencing. This strategy is newer and the corresponding bioinformatics techniques are less developed. The main challenge lies in fast clustering of sequences, in metagenomics referred to as binning. The method introduced in this thesis utilizes a genomic signal processing approach. By thorough analysis of redundancy of genetic information stored in genomic signals, a unique technique was proposed. The technique utilizes transformation of character sequences into several variants of phase signals. Moreover, it is able to directly process nanopore sequencing data in the form of a native current signal.
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Reconstruction of Repetitive DNA Segments
Bikár, Robert ; Lexa, Matej (oponent) ; Martínek, Tomáš (vedoucí práce)
The main motivation for master's thesis is to find suitable algorithm that creates a graph representation of NGS sequencing data in linear time. De Bruijn graph was chosen as a method for research. Next, the tool was designed to be able to transform the graph and correct errors created during construction of the graph. The main aim of the thesis is to implement a tool that reconstructs repetitive segments in DNA. Implemented tool was tested and is able to identify repetitive segments, specify types, visualize them properly and is also able to assemble their sequence with fine accuracy on simpler genomes. When using complex genomes, tool is able to reconstruct only fragments of repetitive segments.
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Vyhledávání kvadruplexů v DNA sekvencích
Sečka, Martin ; Lexa, Matej (oponent) ; Martínek, Tomáš (vedoucí práce)
Tato diplomová práce se zabývá vyhledáváním, vizualizací a filtrací sekvencí potenciálně tvořících kvadruplexy v sekvencích DNA. Ve spolupráci s Biofyzikálním ústavem AV ČR byla za tímto účelem vytvořena webová aplikace, která využívá nový algoritmus pro hledání všech možných umístění kvadruplexů v rámci zadané sekvence. Návrh a implementace tohoto algoritmu jsou také součástí této práce.
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