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Computational studies in protein folding and enzymes engineering involved in bioethanol production


This project aims to continue the research that has been developed at IBILCE in the area of theoretical models in molecular biological physics, with emphasis on computational methods. Problems in the area of molecular biological physics have great complexity, and simplified models play an important role in understanding these systems. Such models have served as fundamental tools, from which more elaborate issues can be developed. In this project, the problems to be addressed through simplified models can be divided into three areas: (1) Protein folding, focusing on fundamental questions in the area. The topics covered are: understanding of the diffusion coefficient in the representation of folding, the effects of frustration, hydrophobicity and topology in the folding process, and visualization of the folding funnel. (2) Study of the enzymes involved in the production of bioethanol, in a theoretical and experimental collaboration. We use coarse-grained models in the study of the mechanisms of thermophilic enzymes 1XXN, 1IGO and 2JEN. We will optimize the thermostability of these enzymes {\sl in silico}, we will suggest site-directed mutations to be tested experimentally. We also use simplified models to investigate enzyme activity variations due to conformational changes in the protein domains. (3) Other topics in biological physics involving external collaborators. These include: statistical mechanics applications in bioinformatics and information processing, and the study of ribosome dynamics. (AU)

Scientific publications (7)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
DA SILVA, FERNANDO BRUNO; CONTESSOTO, VINICIUS G.; DE OLIVEIRA, VINICIUS M.; CLARKE, JANE; LEITE, VITOR B. P. Non-Native Cooperative Interactions Modulate Protein Folding Rates. Journal of Physical Chemistry B, v. 122, n. 48, p. 10817-10824, DEC 6 2018. Web of Science Citations: 3.
CONTESSOTO, VINICIUS G.; DE OLIVEIRA, VINICIUS M.; FERNANDES, BRUNO R.; SLADE, GABRIEL G.; LEITE, VITOR B. P. TKSA-MC: A web server for rational mutation through the optimization of protein charge interactions. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, v. 86, n. 11, p. 1184-1188, NOV 2018. Web of Science Citations: 2.
TAMBONIS, TIAGO; BOARETO, MARCELO; LEITE, VITOR B. P. Differential Expression Analysis in RNA-seq Data Using a Geometric Approach. JOURNAL OF COMPUTATIONAL BIOLOGY, v. 25, n. 11, p. 1257-1265, NOV 2018. Web of Science Citations: 0.
DE OLIVEIRA, VINICIUS MARTINS; CONTESSOTO, VINICIUS DE GODOI; DA SILVA, FERNANDO BRUNO; ZAGO CAETANO, DANIEL LUCAS; DE CARVALHO, SIDNEY JURADO; PEREIRA LEITE, VITOR BARBANTI. Effects of pH and Salt Concentration on Stability of a Protein G Variant Using Coarse-Grained Models. BIOPHYSICAL JOURNAL, v. 114, n. 1, p. 65-75, JAN 9 2018. Web of Science Citations: 8.
VINÍCIUS DE GODOI CONTESSOTO; ANTONIO BENTO DE OLIVEIRA JUNIOR; JORGE CHAHINE; RONALDO JUNIO DE OLIVEIRA; VITOR BARBANTI PEREIRA LEITE. Introdução ao problema de enovelamento de proteínas: uma abordagem utilizando modelos computacionais simplificados. Revista Brasileira de Ensino de Física, v. 40, n. 4, p. -, 2018.
CORONADO, MONIKA A.; CARUSO, ICARO P.; DE OLIVEIRA, VINICIUS M.; CONTESSOTO, VINICIUS G.; LEITE, VITOR B. P.; KAWAI, LIEGE A.; ARNI, RAGHUVIR K.; EBERLE, RAPHAEL J. Cold Shock Protein A from Corynebacterium pseudotuberculosis: Role of Electrostatic Forces in the Stability of the Secondary Structure. PROTEIN AND PEPTIDE LETTERS, v. 24, n. 4, p. 358-367, 2017. Web of Science Citations: 6.
MOURO, PAULO RICARDO; CONTESSOTO, VINICIUS DE GODOI; CHAHINE, JORGE; DE OLIVEIRA, RONALDO JUNIO; PEREIRA LEITE, VITOR BARBANTI. Quantifying Nonnative Interactions in the Protein-Folding Free-Energy Landscape. BIOPHYSICAL JOURNAL, v. 111, n. 2, p. 287-293, JUL 26 2016. Web of Science Citations: 5.

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