Cargando…

Classification model of amino acid sequences prone to aggregation of therapeutic proteins

BACKGROUND: Total body clearance of biological drugs is for the most part dependent on the receptor mechanisms (receptor mediated clearance) and the concentration of antibodies aimed at administered drug – anti-drug-antibodies (ADA). One of the significant factors that induces the increase of ADA le...

Descripción completa

Detalles Bibliográficos
Autores principales: Marczak, Monika, Okoniewska, Krystyna, Grabowski, Tomasz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4937009/
https://www.ncbi.nlm.nih.gov/pubmed/27388622
http://dx.doi.org/10.1186/s40203-016-0019-4
_version_ 1782441631265325056
author Marczak, Monika
Okoniewska, Krystyna
Grabowski, Tomasz
author_facet Marczak, Monika
Okoniewska, Krystyna
Grabowski, Tomasz
author_sort Marczak, Monika
collection PubMed
description BACKGROUND: Total body clearance of biological drugs is for the most part dependent on the receptor mechanisms (receptor mediated clearance) and the concentration of antibodies aimed at administered drug – anti-drug-antibodies (ADA). One of the significant factors that induces the increase of ADA level after drug administration could be the aggregates present in the finished product or formed in the organism. Numerous attempts have been made to identify the sequence fragments that could be responsible for forming the aggregates – aggregate prone regions (APR). PURPOSE: The aim of this study was to find physiochemical parameters specific to APR that would differentiate APR from other sequences present in therapeutic proteins. METHODS: Two groups of amino acid sequences were used in the study. The first one was represented by the sequences separated from the therapeutic proteins (n = 84) able to form APR. A control set (CS) consisted of peptides that were chosen based on 22 tregitope sequences. RESULTS: Classification model and four classes (A, B, C, D) of sequences were finally presented. For model validation Cooper statistics was presented. CONCLUSIONS: The study proposes a classification model of APR. This consists in a distinction of APR from sequences that do not form aggregates based on the differences in the value of physicochemical parameters. Significant share of electrostatic parameters in relation to classification model was indicated.
format Online
Article
Text
id pubmed-4937009
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Springer Berlin Heidelberg
record_format MEDLINE/PubMed
spelling pubmed-49370092016-07-20 Classification model of amino acid sequences prone to aggregation of therapeutic proteins Marczak, Monika Okoniewska, Krystyna Grabowski, Tomasz In Silico Pharmacol Original Research BACKGROUND: Total body clearance of biological drugs is for the most part dependent on the receptor mechanisms (receptor mediated clearance) and the concentration of antibodies aimed at administered drug – anti-drug-antibodies (ADA). One of the significant factors that induces the increase of ADA level after drug administration could be the aggregates present in the finished product or formed in the organism. Numerous attempts have been made to identify the sequence fragments that could be responsible for forming the aggregates – aggregate prone regions (APR). PURPOSE: The aim of this study was to find physiochemical parameters specific to APR that would differentiate APR from other sequences present in therapeutic proteins. METHODS: Two groups of amino acid sequences were used in the study. The first one was represented by the sequences separated from the therapeutic proteins (n = 84) able to form APR. A control set (CS) consisted of peptides that were chosen based on 22 tregitope sequences. RESULTS: Classification model and four classes (A, B, C, D) of sequences were finally presented. For model validation Cooper statistics was presented. CONCLUSIONS: The study proposes a classification model of APR. This consists in a distinction of APR from sequences that do not form aggregates based on the differences in the value of physicochemical parameters. Significant share of electrostatic parameters in relation to classification model was indicated. Springer Berlin Heidelberg 2016-07-07 /pmc/articles/PMC4937009/ /pubmed/27388622 http://dx.doi.org/10.1186/s40203-016-0019-4 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Research
Marczak, Monika
Okoniewska, Krystyna
Grabowski, Tomasz
Classification model of amino acid sequences prone to aggregation of therapeutic proteins
title Classification model of amino acid sequences prone to aggregation of therapeutic proteins
title_full Classification model of amino acid sequences prone to aggregation of therapeutic proteins
title_fullStr Classification model of amino acid sequences prone to aggregation of therapeutic proteins
title_full_unstemmed Classification model of amino acid sequences prone to aggregation of therapeutic proteins
title_short Classification model of amino acid sequences prone to aggregation of therapeutic proteins
title_sort classification model of amino acid sequences prone to aggregation of therapeutic proteins
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4937009/
https://www.ncbi.nlm.nih.gov/pubmed/27388622
http://dx.doi.org/10.1186/s40203-016-0019-4
work_keys_str_mv AT marczakmonika classificationmodelofaminoacidsequencespronetoaggregationoftherapeuticproteins
AT okoniewskakrystyna classificationmodelofaminoacidsequencespronetoaggregationoftherapeuticproteins
AT grabowskitomasz classificationmodelofaminoacidsequencespronetoaggregationoftherapeuticproteins