Proteins are involved in many cell activities (e.g., molecular transport, mechanical functions, message exchange) thus knowing their 3D structure is crucial in order to understand their function. Protein tertiary structure prediction is a research field which aims to create models and software tools able to predict the three-dimensional shape of protein molecules by describing the spatial disposition of each of its atoms starting from the sequence of its amino acids. There exist exact methods to resolve the molecular structure with high precision, but they are both time and resource consuming. Computational based software techniques can predict the tertiary structure of a protein with acceptable precision for many applications with high efficiency allowing for genome-wide investigations, otherwise not feasible. These tools use various intermediate steps, evolutionary considerations and chemical functionals to improve the predicted structure. Nevertheless, due to the high dimensionality of the problem, some of the available computational techniques, e.g., Density Functional Theory, are not efficient enough to be used in practical application scenarios.

Algorithms for structure comparison and analysis: Prediction of tertiary structures of proteins

Tradigo, G.;
2018-01-01

Abstract

Proteins are involved in many cell activities (e.g., molecular transport, mechanical functions, message exchange) thus knowing their 3D structure is crucial in order to understand their function. Protein tertiary structure prediction is a research field which aims to create models and software tools able to predict the three-dimensional shape of protein molecules by describing the spatial disposition of each of its atoms starting from the sequence of its amino acids. There exist exact methods to resolve the molecular structure with high precision, but they are both time and resource consuming. Computational based software techniques can predict the tertiary structure of a protein with acceptable precision for many applications with high efficiency allowing for genome-wide investigations, otherwise not feasible. These tools use various intermediate steps, evolutionary considerations and chemical functionals to improve the predicted structure. Nevertheless, due to the high dimensionality of the problem, some of the available computational techniques, e.g., Density Functional Theory, are not efficient enough to be used in practical application scenarios.
2018
9780128114322; 9780128114148
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11389/36389
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