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Prediction of the Effect of Amino Acid Substitutions on the Secondary Structure of Proteins
Kadlec, Miroslav ; Vogel, Ivan (referee) ; Bendl, Jaroslav (advisor)
This thesis is focused on amino acid substitutions and their impact on protein secondary structure. The main aim is to prove, that although the protein sequence is frequently mutated during the evolution, protein secondary structure is more robust against changes. In this case, the elements of protein secondary structure stay almost unchanged although a significant number of substitutions is observed. The proof of this hypothesis was obtained by developed simulator of evolution which employs two well-estabilished predicting tools: PSIPRED for prediction of protein secondary structure and PhD-SNP for prediction of the effect of amino acid substitution on protein function. The results of the experiments are provided as graphs and their meainings is discussed.
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Prediction of Protein Stability upon Amino Acid Mutations Using Evolution Strategy
Kadlec, Miroslav ; Burgetová, Ivana (referee) ; Bendl, Jaroslav (advisor)
This thesis is focused on predicting the impact of amino acid substitution on protein stability. The main goal is to create a consensual predictor that uses the outputs of chosen existing tools in order to improve accuracy of prediction. The optimal consensus of theese tools was designed using evolution strategies in three variants: 1/5 success rule, self-adaptation variant and the CMA-ES method. Then, the quality of calculated weight vectors was tested on the independent dataset. Although the highest prediction performance was attained by self-adaptation method, the differences between all three variants were not significant. Compared to the individual tools, the predictions provided by consensual methods were generally more accurate - the self-adaptation variant imporved the Pearson's corelation coeficient of the predictions by 0,057 on the training dataset. On the testing dataset, the improvement of designed method was smaller (0,040). Relatively low improvement of prediction performance (both on the training and the testing dataset) were caused by the fact, that for some records of testing dataset, some individual tools vere not able to provide their results. When omitting these records, consensual method improved the Pearson's corelations coeficient by 0,118.
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Predicting the Effect of Amino Acid Substitutions on Protein Function Using MAPP Method
Pelikán, Ondřej ; Vogel, Ivan (referee) ; Bendl, Jaroslav (advisor)
This thesis discusses the issue of predicting the effect of amino acid substitutions on protein function using MAPP method. This method requires the multiple sequence alignment and phylogenetic tree constructed by third-party tools. Main goal of this thesis is to find the combination of suitable tools and their parameters to generate the inputs of MAPP method on the basis of analysis on one massively mutated protein. Then, the MAPP method is tested with chosen combination of parameters and tools on two large independent datasets and consequently is compared with the other tools focused on prediction of the effect of mutations. Apart from this the web interface for the MAPP method was created. This interface simplifies the use of the method since the user need not to install any tools or set any parameters.
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Predicting the Effect of Amino Acid Substitutions on Protein Function Using MAPP Method
Pelikán, Ondřej ; Vogel, Ivan (referee) ; Bendl, Jaroslav (advisor)
This thesis discusses the issue of predicting the effect of amino acid substitutions on protein function using MAPP method. This method requires the multiple sequence alignment and phylogenetic tree constructed by third-party tools. Main goal of this thesis is to find the combination of suitable tools and their parameters to generate the inputs of MAPP method on the basis of analysis on one massively mutated protein. Then, the MAPP method is tested with chosen combination of parameters and tools on two large independent datasets and consequently is compared with the other tools focused on prediction of the effect of mutations. Apart from this the web interface for the MAPP method was created. This interface simplifies the use of the method since the user need not to install any tools or set any parameters.
|
|
|
Prediction of the Effect of Amino Acid Substitutions on the Secondary Structure of Proteins
Kadlec, Miroslav ; Vogel, Ivan (referee) ; Bendl, Jaroslav (advisor)
This thesis is focused on amino acid substitutions and their impact on protein secondary structure. The main aim is to prove, that although the protein sequence is frequently mutated during the evolution, protein secondary structure is more robust against changes. In this case, the elements of protein secondary structure stay almost unchanged although a significant number of substitutions is observed. The proof of this hypothesis was obtained by developed simulator of evolution which employs two well-estabilished predicting tools: PSIPRED for prediction of protein secondary structure and PhD-SNP for prediction of the effect of amino acid substitution on protein function. The results of the experiments are provided as graphs and their meainings is discussed.
|
|
|
Prediction of Protein Stability upon Amino Acid Mutations Using Evolution Strategy
Kadlec, Miroslav ; Burgetová, Ivana (referee) ; Bendl, Jaroslav (advisor)
This thesis is focused on predicting the impact of amino acid substitution on protein stability. The main goal is to create a consensual predictor that uses the outputs of chosen existing tools in order to improve accuracy of prediction. The optimal consensus of theese tools was designed using evolution strategies in three variants: 1/5 success rule, self-adaptation variant and the CMA-ES method. Then, the quality of calculated weight vectors was tested on the independent dataset. Although the highest prediction performance was attained by self-adaptation method, the differences between all three variants were not significant. Compared to the individual tools, the predictions provided by consensual methods were generally more accurate - the self-adaptation variant imporved the Pearson's corelation coeficient of the predictions by 0,057 on the training dataset. On the testing dataset, the improvement of designed method was smaller (0,040). Relatively low improvement of prediction performance (both on the training and the testing dataset) were caused by the fact, that for some records of testing dataset, some individual tools vere not able to provide their results. When omitting these records, consensual method improved the Pearson's corelations coeficient by 0,118.
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