Universidad Peruana Cayetano Heredia

Prediction of Mycobacterium tuberculosis pyrazinamidase function based on structural stability, physicochemical and geometrical descriptors

Mostrar el registro sencillo del ítem

dc.contributor.author Supo-Escalante, R.R.
dc.contributor.author Médico, A.
dc.contributor.author Gushiken, E.
dc.contributor.author Olivos-Ramírez, G.E.
dc.contributor.author Quispe, Y.
dc.contributor.author Torres, Fiorella
dc.contributor.author Zamudio, M.
dc.contributor.author Antiparra, R.
dc.contributor.author Mario Amzel, L.
dc.contributor.author Gilman, Robert Hugh
dc.contributor.author Sheen Cortavarria, Patricia
dc.contributor.author Zimic-Peralta, Mirko Juan
dc.date.accessioned 2020-12-14T16:10:16Z
dc.date.available 2020-12-14T16:10:16Z
dc.date.issued 2020
dc.identifier.uri https://hdl.handle.net/20.500.12866/8817
dc.description.abstract Background: Pyrazinamide is an important drug against the latent stage of tuberculosis and is used in both first- and second-line treatment regimens. Pyrazinamide-susceptibility test usually takes a week to have a diagnosis to guide initial therapy, implying a delay in receiving appropriate therapy. The continued increase in multi-drug resistant tuberculosis and the prevalence of pyrazinamide resistance in several countries makes the development of assays for prompt identification of resistance necessary. The main cause of pyrazinamide resistance is the impairment of pyrazinamidase function attributed to mutations in the promoter and/or pncA coding gene. However, not all pncA mutations necessarily affect the pyrazinamidase function. Objective: To develop a methodology to predict pyrazinamidase function from detected mutations in the pncA gene. Methods: We measured the catalytic constant (kcat), KM, enzymatic efficiency, and enzymatic activity of 35 recombinant mutated pyrazinamidase and the wild type (Protein Data Bank ID = 3pl1). From all the 3D modeled structures, we extracted several predictors based on three categories: structural stability (estimated by normal mode analysis and molecular dynamics), physicochemical, and geometrical characteristics. We used a stepwise Akaike's information criterion forward multiple log-linear regression to model each kinetic parameter with each category of predictors. We also developed weighted models combining the three categories of predictive models for each kinetic parameter. We tested the robustness of the predictive ability of each model by 6-fold cross-validation against random models. Results: The stability, physicochemical, and geometrical descriptors explained most of the variability (R2) of the kinetic parameters. Our models are best suited to predict kcat, efficiency, and activity based on the root-mean-square error of prediction of the 6-fold cross-validation. Conclusions: This study shows a quick approach to predict the pyrazinamidase function only from the pncA sequence when point mutations are present. This can be an important tool to detect pyrazinamide resistance. Copyright: © 2020 Supo-Escalante et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. en_US
dc.language.iso eng
dc.publisher Public Library of Science
dc.relation.ispartofseries PLoS ONE
dc.rights info:eu-repo/semantics/restrictedAccess
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.subject Statistical distributions en_US
dc.subject Molecular dynamics en_US
dc.subject Mycobacterium tuberculosis en_US
dc.subject Point mutation en_US
dc.subject Forecasting en_US
dc.subject Electrostatics en_US
dc.subject Enzymes en_US
dc.subject Recombinant proteins en_US
dc.title Prediction of Mycobacterium tuberculosis pyrazinamidase function based on structural stability, physicochemical and geometrical descriptors en_US
dc.type info:eu-repo/semantics/article
dc.identifier.doi https://doi.org/10.1371/journal.pone.0235643
dc.subject.ocde https://purl.org/pe-repo/ocde/ford#3.02.07
dc.subject.ocde https://purl.org/pe-repo/ocde/ford#3.01.05
dc.relation.issn 1932-6203


Ficheros en el ítem

Ficheros Tamaño Formato Ver

No hay ficheros asociados a este ítem.

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem

info:eu-repo/semantics/restrictedAccess Excepto si se señala otra cosa, la licencia del ítem se describe como info:eu-repo/semantics/restrictedAccess

Buscar en el Repositorio


Listar

Panel de Control

Estadísticas