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Rational Evolution by Computational Methods Applied in Enzymes Related to Bioethanol Production

Grant number: 17/09662-7
Support type:Scholarships abroad - Research Internship - Post-doctor
Effective date (Start): August 01, 2017
Effective date (End): July 31, 2018
Field of knowledge:Biological Sciences - Biophysics - Molecular Biophysics
Principal Investigator:Vitor Barbanti Pereira Leite
Grantee:Vinícius de Godoi Contessoto
Supervisor abroad: Jose Nelson Onuchic
Home Institution: Centro Nacional de Pesquisa em Energia e Materiais (CNPEM). Ministério da Ciência, Tecnologia, Inovações e Comunicações (Brasil). Campinas , SP, Brazil
Local de pesquisa : Rice University, United States  
Associated to the scholarship:16/13998-8 - Rational evolution by computational methods applied to predict mutations in enzymes to biofuels production, BP.PD

Abstract

One of the most difficult challenges in science is to find clean and cheap energy sources. The second generation bioethanol seems to be viable a solution to substitute fossil fuel usage. The bioethanol production makes use of sugarcane biomass residues not used directly in the fermentation process. This process involves the degradation of cellulose by specific enzymatic hydrolysis. The technological challenge now is to obtain and optimize the enzymes to perform the hydrolysis process with more efficiency. The motivation of this project is to work computationally on enzymes thermostability optimization, suggesting mutations to be tested experimentally. This ongoing project seeks to evaluate and optimize enzyme cocktails for second generation bioethanol production. The focus of the optimization is to increase the catalytic activity, the thermostability and pH control, adapting the enzymes to have the optimum activity at the reactor operation conditions. A theoretical method based on optimization of charge-charge interaction in enzyme surface have been used to suggest the mutations. It is under development an approach using bioinformatics tools to suggest mutations based on ancestral sequence reconstruction and consensus-based sequence. It was observed in preliminary data that polar charged residues which are not conserved in the multiple sequence alignments are also pointed as a candidate to be mutated based on the protein charge-charge interaction optimization method. It was also observed that mutations involving polar charged residues happen in pairs. The investigation of the compensatory mutations analyzing the structural information of the pair contacts is a fundamental step to improve the rational mutation methods. The Direct-Coupling Analysis (DCA) and the Structure-Based Models (SBM) developed by Prof. Dr. José Onuchic group ( Rice University - Houston/TX-USA) will be used to improve the accuracy of the suggested mutation. The DCA method is based on a statistical inference framework used to infer direct co-evolutionary couplings among residues pairs in multiple sequence alignments and will be applied to investigate the compensatory mutation. The SBM will be used to capture the essential protein dynamic in the folding process and in the complex formation in the investigation of the enzyme stability and its interaction with other enzymes in reactor cocktail. The suggested mutations will be experimentally validated by the Brazilian Bioethanol Science and Technology Laboratory (CTBE) group.

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 B.; DE OLIVEIRA, VINICIUS M.; SANCHES, MURILO N.; CONTESSOTO, VINICIUS G.; LEITE, VITOR B. P. Rational Design of Chymotrypsin Inhibitor 2 by Optimizing Non-Native Interactions. JOURNAL OF CHEMICAL INFORMATION AND MODELING, v. 60, n. 2, p. 982-988, FEB 2020. Web of Science Citations: 1.
DODERO-ROJAS, ESTEBAN; FERREIRA, LUIZA G.; LEITE, VITOR B. P.; ONUCHIC, JOSE N.; CONTESSOTO, VINICIUS G. Modeling Chikungunya control strategies and Mayaro potential outbreak in the city of Rio de Janeiro. PLoS One, v. 15, n. 1 JAN 28 2020. Web of Science Citations: 0.
FREITAS, FREDERICO CAMPOS; LIMA, ANGELICA NAKAGAWA; CONTESSOTO, VINICIUS DE GODOI; WHITFORD, PAUL C.; DE OLIVEIRA, RONALDO JUNIO. Drift-diffusion (DrDiff) framework determines kinetics and thermodynamics of two-state folding trajectory and tunes diffusion models. Journal of Chemical Physics, v. 151, n. 11 SEP 21 2019. Web of Science Citations: 0.
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.
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.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.