Integrating protein structural information

Abstract

Dissertação apresentada para obtenção de Grau de Doutor em Bioquímica,Bioquímica Estrutural, pela Universidade Nova de Lisboa, Faculdade de Ciências e TecnologiaThe central theme of this work is the application of constraint programming and other artificial intelligence techniques to protein structure problems, with the goal of better combining experimental data with structure prediction methods. Part one of the dissertation introduces the main subjects of protein structure and constraint programming, summarises the state of the art in the modelling of protein structures and complexes, sets the context for the techniques described later on, and outlines the main points of the thesis: the integration of experimental data in modelling. The first chapter, Protein Structure, introduces the reader to the basic notions of amino acid structure, protein chains, and protein folding and interaction. These are important concepts to understand the work described in parts two and three. Chapter two, Protein Modelling, gives a brief overview of experimental and theoretical techniques to model protein structures. The information in this chapter provides the context of the investigations described in parts two and three, but is not essential to understanding the methods developed. Chapter three, Constraint Programming, outlines the main concepts of this programming technique. Understanding variable modelling, the notions of consistency and propagation, and search methods should greatly help the reader interested in the details of the algorithms, as described in part two of this book. The fourth chapter, Integrating Structural Information, is a summary of the thesis proposed here. This chapter is an overview of the objectives of this work, and gives an idea of how the algorithms developed here could help in modelling protein structures. The main goal is to provide a flexible and continuously evolving framework for the integration of structural information from a diversity of experimental techniques and theoretical predictions. Part two describes the algorithms developed, which make up the main original contribution of this work. This part is aimed especially at developers interested in the details of the algorithms, in replicating the results, in improving the method or in integrating them in other applications. Biochemical aspects are dealt with briefly and as necessary, and the emphasis is on the algorithms and the code

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