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Roberto Pineda   Professor  University Educator/Researcher 
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Roberto Pineda published an article in February 2018.
Top co-authors
Aldhair Médico

1 shared publications

Universidad Ricardo Palma

Cristian Bustamante

1 shared publications

Universidad Ricardo Palma

Daniela Zapata

1 shared publications

Universidad Ricardo Palma

Janny Maza

1 shared publications

Universidad Ricardo Palma

2
Publications
117
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Publication Record
Distribution of Articles published per year 
(2018)
Total number of journals
published in
 
1
 
Publications
CONFERENCE-ARTICLE 53 Reads 0 Citations Molecular Dynamics and In Silico Analysis of Oligomerization Surfaces of CYND Enzymes Aldhair Médico, Cristian Bustamante, Roberto Pineda, Santiag... Published: 01 February 2018
MOL2NET 2018, International Conference on Multidisciplinary Sciences, 4th edition, doi: 10.3390/mol2net-04-05126
DOI See at publisher website ABS Show/hide abstract

Cyanide is a toxic compund widely used in mining. Naturally some bacterias are capable to degrade this molecules. CynD is a type of prokaryote enzyme able to degrade cyanide and its active form seems to be an oligomer. Several attempts to obtain structural models of CynD by crystallography has not success mainly due the insolubility of the oligomeric state of this protein. In this work we aimed to use in silico tools to identify the aminoacids implied in the oligomerization surfaces. These knowledge could lead us to rationally design CynD variants that are not able to form tights oligomers stabilizing other forms such as dimers or monomers that could be better in purification and crystallization assays. For this, we prepared structural models using SWISS-MODEL, PHYRE2, I-TASSER and ROBETTA. Then, we analyzed chemical parameters of the models using RAMPAGE, PDBsum and ModFold6. Next, we did dimer models using dockings in Hex. The monomer and dimer models were used to perform molecular dynamics simulation in order to determine flexible regions, important aminoacids stabilizing the dimeric interface and the stability of the dimer form. We obtain models with good chemical parameters to perform the dynamics simulation. These assays allow us to identify flexible regions that could be removed to stabilize the dimer or monomer in solution. Finally, the docking showed us which are the probable aminoacids stabilizing the dimer interface. Experimental data is now neccesary to confirm those hypotheses.

JANDHYLA, D.; Berman, M.;Meyeres, P.; Sewell, B.; Willson, R.; Benedik, M. cynD, the Cyanide Dihidratase from Bacillus pumilus: Gene Cloning and Structural Studies. Applied and Environmental Microbiology. Vol 69, No. 8. Aug. 2003. p 4794 – 4805

Crum, M. A. N., Park, J. M., Mulelu, A. E., Sewell, B. T., & Benedik, M. J. (2015). Probing C-terminal interactions of the Pseudomonas stutzeri cyanide-degrading CynD protein. Applied microbiology and biotechnology, 99(7), 3093-3102.

CONFERENCE-ARTICLE 64 Reads 0 Citations Modeling and Analysis of AG:IGE Interface of House Dust Mite Allergens of Group 1 Tania Churasacari, Daniela Zapata, Janny Maza, Alicia Arica,... Published: 01 February 2018
MOL2NET 2018, International Conference on Multidisciplinary Sciences, 4th edition, doi: 10.3390/mol2net-04-05125
DOI See at publisher website ABS Show/hide abstract

In Peru, 20-28% of people has hypersensitivity to allergens; of these 80% are sensible to at least one house dust mite. The immunotherapy is based on the administration of increasing doses of protein extracts or purified proteins of allergens. These treatments seem to be effective in some cases but still we do not have yet an equilibrium between stability, specificity and immunogenicity. This work analyzes in silico models of antigen-antibody of house dust mite allergens of group 1 of Acarus siro, Euroglyphus maynei, Sarcoptes scabiei y Tyrophagus putrescentiae. We obtained structural in silico models using I-tasser. The assymetric unit of 4PP1 is formed by two DerP1:Fab5H8 complexes; to generate interfaces models we replaced chain A by the allergen model in analysis. Then, we minimized the potential energy using the Steepest Descent algorithm and finally we analyzed the interactions in the allergen:IgE interface.

We were able to identify three antibody aminoacids interacting with the four allergens in study (Tyr32, Tyr50, Lys92), one that interacts with SarS1 and TyrP1 and others six that interact only with EurM1 and AcaS1. Our results show the identification of possible regions important in the recognition of group 1 allergens, also we show other aminoacids that could recognize specifically a subgroup of these allergens.

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