Vazquez2014 - Chemical inhibition from amyloid protein aggregation kinetics
Ontology highlight
ABSTRACT:
Vazquez2014 - Chemical inhibition from
amyloid protein aggregation kinetics
This model is described in the article:
Modeling of chemical
inhibition from amyloid protein aggregation kinetics.
Vázquez JA.
BMC Pharmacol Toxicol 2014; 15(1):
9
Abstract:
BACKGROUNDS: The process of amyloid proteins aggregation
causes several human neuropathologies. In some cases, e.g.
fibrillar deposits of insulin, the problems are generated in
the processes of production and purification of protein and in
the pump devices or injectable preparations for diabetics.
Experimental kinetics and adequate modelling of chemical
inhibition from amyloid aggregation are of practical importance
in order to study the viable processing, formulation and
storage as well as to predict and optimize the best conditions
to reduce the effect of protein nucleation. RESULTS: In this
manuscript, experimental data of insulin, A?42 amyloid protein
and apomyoglobin fibrillation from recent bibliography were
selected to evaluate the capability of a bivariate sigmoid
equation to model them. The mathematical functions (logistic
combined with Weibull equation) were used in reparameterized
form and the effect of inhibitor concentrations on kinetic
parameters from logistic equation were perfectly defined and
explained. The surfaces of data were accurately described by
proposed model and the presented analysis characterized the
inhibitory influence on the protein aggregation by several
chemicals. Discrimination between true and apparent inhibitors
was also confirmed by the bivariate equation. EGCG for insulin
(working at pH?=?7.4/T?=?37°C) and taiwaniaflavone for
A?42 were the compounds studied that shown the greatest
inhibition capacity. CONCLUSIONS: An accurate, simple and
effective model to investigate the inhibition of chemicals on
amyloid protein aggregation has been developed. The equation
could be useful for the clear quantification of inhibitor
potential of chemicals and rigorous comparison among them.
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000532.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
DISEASE(S): Alzheimer's Disease
SUBMITTER: Audald Lloret i Villas
PROVIDER: BIOMD0000000532 | BioModels | 2024-09-02
REPOSITORIES: BioModels
ACCESS DATA