BackgroundTrypanosoma cruzi is the etiological agent of Chagas' disease, an endemic infection that causes thousands of deaths every year in Latin America. Therapeutic options remain inefficient, demanding the search for new drugs and/or new molecular targets. Such efforts can focus on proteins that are specific to the parasite, but analogous enzymes and enzymes with a three-dimensional (3D) structure sufficiently different from the corresponding host proteins may represent equally interesting targets. In order to find these targets we used the workflows MHOLline and AnEnΠ obtaining 3D models from homologous, analogous and specific proteins of Trypanosoma cruzi versus Homo sapiens.ResultsWe applied genome wide comparative modelling techniques to obtain 3D models for 3,286 predicted proteins of T. cruzi. In combination with comparative genome analysis to Homo sapiens, we were able to identify a subset of 397 enzyme sequences, of which 356 are homologous, 3 analogous and 38 specific to the parasite.ConclusionsIn this work, we present a set of 397 enzyme models of T. cruzi that can constitute potential structure-based drug targets to be investigated for the development of new strategies to fight Chagas' disease. The strategies presented here support the concept of structural analysis in conjunction with protein functional analysis as an interesting computational methodology to detect potential targets for structure-based rational drug design. For example, 2,4-dienoyl-CoA reductase (EC 1.3.1.34) and triacylglycerol lipase (EC 3.1.1.3), classified as analogous proteins in relation to H. sapiens enzymes, were identified as new potential molecular targets.

Cisplatin (cddp)-based chemotherapy is one of the most effective therapeutic alternatives for breast cancer treatment, the most common form of cancer, despite the severe side effects related to the high...

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SUMMARYOne variant of the ant colony optimization (ACO) metaheuristic, known as rank-based ant system (RBAS), is proposed for weight minimization of structures involving discrete design variables. Stress and displacements constraints are handled using a penalty technique, and the structural analysis is performed by the finite element method.Results obtained for several discrete weight minimization problems show that the RBAS algorithm implemented is effective and competitive when compared with results found by genetic algorithms and another RBAS variant.