Classification model of amino acid sequences prone to aggregation of therapeutic proteins
| Autor: | Monika Marczak, Tomasz Grabowski, Krystyna Okoniewska |
|---|---|
| Jazyk: | angličtina |
| Předmět: |
0301 basic medicine
Drug Aggregates animal structures In silico media_common.quotation_subject Biology Pharmacology Biological drugs 03 medical and health sciences 0302 clinical medicine Receptor Original Research media_common chemistry.chemical_classification Immunogenicity Proteins Receptor-mediated endocytosis Amino acid ADA 030104 developmental biology chemistry Automotive Engineering biology.protein Antibody 030215 immunology |
| Zdroj: | In Silico Pharmacology |
| ISSN: | 2193-9616 |
| DOI: | 10.1186/s40203-016-0019-4 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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