Combined Experimental and Molecular Simulation Study of Insulin-Chitosan Complexation Driven by Electrostatic Interactions

Protein−polysaccharide complexes constructed via self-assembly methods are often used to develop novel 17 biomaterials for a wide range of applications in biomedicine, food, and biotechnology. The objective of this work was to 18 investigate theoretically and to demonstrate via constant-pH Monte Carlo simulations that the complexation phenomenon 19 between insulin (INS) and the cationic polyelectrolyte chitosan (CS) is mainly driven by an electrostatic mechanism. 20 Experimental results obtained from FTIR spectra and ζ-potential determinations allowed us to complement the conclusions. 21 The characteristic absorption bands for the complexes could be assigned to a combination of signals from CS amide I and INS 22 amide II. The second peak corresponds to the interaction between the polymer and the protein at the level of amide II. INS− 23 CS complexation processes not expected when INS is in its monomeric form, but for both tetrameric and hexameric forms, 24 incipient complexation due to charge regulation mechanism took place at pH 5. The complexation range was observed to be 5.5 25 < pH < 6.5. In general, when the number of INS units increases in the simulation process, the solution pH at which the 26 complexation can occur shifts toward acidic conditions. CS’s chain interacts more efficiently, i.e. in a wider pH range, with INS 27 aggregates formed by the highest monomer number. The charge regulation mechanism can be considered as a previous phase 28 toward complexation (incipient complexation) caused by weak interactions of a Coulombic nature.Fil: Prudkin Silva, Cecilia Raquel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Pérez, Carlos E.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Martínez, Karina Dafne. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Industrias. Instituto de Tecnología de Alimentos y Procesos Químicos. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Tecnología de Alimentos y Procesos Químicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Tecnología en Polímeros y Nanotecnología. Universidad de Buenos Aires. Facultad de Ingeniería. Instituto de Tecnología en Polímeros y Nanotecnología; ArgentinaFil: Barroso da silva, Fernando. Universidade do Sao Paulo. Departamento de Bioquímica; Brasi

Combined Experimental and Molecular Simulation Study of Insulin-Chitosan Complexation Driven by Electrostatic Interactions

Protein−polysaccharide complexes constructed via self-assembly methods are often used to develop novel 17 biomaterials for a wide range of applications in biomedicine, food, and biotechnology. The objective of this work was to 18 investigate theoretically and to demonstrate via constant-pH Monte Carlo simulations that the complexation phenomenon 19 between insulin (INS) and the cationic polyelectrolyte chitosan (CS) is mainly driven by an electrostatic mechanism. 20 Experimental results obtained from FTIR spectra and ζ-potential determinations allowed us to complement the conclusions. 21 The characteristic absorption bands for the complexes could be assigned to a combination of signals from CS amide I and INS 22 amide II. The second peak corresponds to the interaction between the polymer and the protein at the level of amide II. INS− 23 CS complexation processes not expected when INS is in its monomeric form, but for both tetrameric and hexameric forms, 24 incipient complexation due to charge regulation mechanism took place at pH 5. The complexation range was observed to be 5.5 25 < pH < 6.5. In general, when the number of INS units increases in the simulation process, the solution pH at which the 26 complexation can occur shifts toward acidic conditions. CS’s chain interacts more efficiently, i.e. in a wider pH range, with INS 27 aggregates formed by the highest monomer number. The charge regulation mechanism can be considered as a previous phase 28 toward complexation (incipient complexation) caused by weak interactions of a Coulombic nature.Fil: Prudkin Silva, Cecilia Raquel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Pérez, Carlos E.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Martínez, Karina Dafne. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Industrias. Instituto de Tecnología de Alimentos y Procesos Químicos. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Tecnología de Alimentos y Procesos Químicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Tecnología en Polímeros y Nanotecnología. Universidad de Buenos Aires. Facultad de Ingeniería. Instituto de Tecnología en Polímeros y Nanotecnología; ArgentinaFil: Barroso da silva, Fernando. Universidade do Sao Paulo. Departamento de Bioquímica; Brasi

Antimicrobial and antibiofilm activities of aqueous extracts of Cucurbita pepo L.

Introduction: Cucurbita pepo L. is an herbaceous plant belonging to the family Cucurbitaceae. The species is popularly used in differentcountries for the treatment of diabetes and parasitic diseases. Objective: This study evaluated the antimicrobial and antibiofilmpotential of aqueous extracts of leaves and seeds of C. pepo. Methodology: the extracts were tested in vitro against strains ofStreptococcus pyogenes, Candida albicans and Candida krusei. The antimicrobial activity was performed by the microtiter method andthe antibiofilm activity by the violet crystal method. Results: the results demonstrated that the extracts tested showed antibacterialand antibiofilm actions against S. pyogenes, but it was not possible to determine the minimum inhibitory concentration (MIC). Theextracts inhibited the growth of C. albicans and C. krusei with MIC of 0.03 mg/mL. The antibiofilm activity of these species did notpresent either a dose dependence relationship or a synergistic effect when associated with the antifungal Fluconazole®. Conclusion:although there are indications of antimicrobial and inhibitory action in the formation of biofilm, additional studies are necessary tocharacterize the possible pharmacological effects of the analyzed speci

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio