Reconstruction and classification of spatial structures via continuous optimization: emphasis on proteins

Author(s)

Rodrigo Silva Lima

• Document type: Doctoral Thesis
• Press: Campinas, SP.
• Institution: Universidade Estadual de Campinas (UNICAMP). Instituto de Matemática, Estatística e Computação Científica
• Defense date: 2012-01-20

Examining board members

José Mario Martínez Pérez; Carlile Campos Lavor; Sandra Augusta Santos; Nelson Maculan Filho; Juliano de Bem Francisco

• Advisor: José Mario Martínez Pérez; Margarida Pinheiro Mello

Abstract

In this work we initially study the problem of reconstruct the 3D structure of a protein given the distances between pairs of its atoms. We formulate this situation as a nonlinear optimization problem with a continuous objective function over the domain of variables. We show by computational experiments that the original protein structure is recovered even when we do not use all the distances between its atoms. Next, we study the problem of representing a set of proteins. The proteins are compared with respect to their 3D structures. We propose some formulations to this problem, where the proteins are represented by objects in euclidean spaces and we elaborate also a form of use these representations to classify new proteins without perform many comparisons between the analyzed structures (AU)

• FAPESP's process: 06/04053-8 - Some issues with global motion optimization
• Grantee: Rodrigo Silva Lima
• Support Opportunities: Scholarships in Brazil - Doctorate