Freeze-drying of engineered proteins using protein modelling tools and experimental validation
The development of therapeutic proteins is a driving force in the current manufacture of biopharmaceuticals. Freeze drying is widely used in the fabrication of final dosage forms of therapeutic proteins. Using a series of A33 Fab mutants, this thesis aimed to correlate their physicochemical properti...
Main Author: | |
---|---|
Other Authors: | |
Published: |
University College London (University of London)
2017
|
Subjects: | |
Online Access: | https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.746503 |
id |
ndltd-bl.uk-oai-ethos.bl.uk-746503 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-bl.uk-oai-ethos.bl.uk-7465032019-03-05T15:16:56ZFreeze-drying of engineered proteins using protein modelling tools and experimental validationZhang, C.Dalby, Paul ; Brocchini, Steve2017The development of therapeutic proteins is a driving force in the current manufacture of biopharmaceuticals. Freeze drying is widely used in the fabrication of final dosage forms of therapeutic proteins. Using a series of A33 Fab mutants, this thesis aimed to correlate their physicochemical properties to the outcomes of freeze-drying. Preliminary studies employed a homogeneous freeze-drying process on 96-well plates. It was found that K65M and K133M surface mutations, the use of acetate buffer, low pH, increased ionic strength, and the use of NaCl, caused the most monomer loss; whereas S75K, C226S, and L50K mutations, high pH, and the use of Na2SO4 caused the least monomer loss. Several in-silico modelling tools were used to design mutants for studying the impact of protein conformational stability. Rosetta software, RMSF and B-factor analyses were used to evaluate the mutant candidates and restrict the mutations mainly located in the flexible regions. Unstable mutants were prepared as controls to validate the prediction accuracy. In freeze-drying, most of the stabilising mutants had 20% less monomer loss than C226S, while the destabilising ones had 14-46% more monomer loss. Tm and ΔΔG estimated the monomer loss in freeze-drying with low degree of accuracy. Compared to freeze-drying, a more distinct difference was observed in the aqueous phase as all the destabilising mutants aggregated more than 5 times faster than C226S and the stabilising mutants did. Tm correlated well with the aggregation in aqueous phase, indicating conformational stability was more important in aqueous phase than that in freeze-drying. In addition, excipients barely exerted influence on the stable mutants but provided sufficient protection for the unstable ones, which was reflected by their correlations to Tm values. The rank-order of excipient effects for individual mutants, relative to that of wild type, became less similar as the mutant ΔTm magnitude increased.660.6University College London (University of London)https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.746503http://discovery.ucl.ac.uk/1549425/Electronic Thesis or Dissertation |
collection |
NDLTD |
sources |
NDLTD |
topic |
660.6 |
spellingShingle |
660.6 Zhang, C. Freeze-drying of engineered proteins using protein modelling tools and experimental validation |
description |
The development of therapeutic proteins is a driving force in the current manufacture of biopharmaceuticals. Freeze drying is widely used in the fabrication of final dosage forms of therapeutic proteins. Using a series of A33 Fab mutants, this thesis aimed to correlate their physicochemical properties to the outcomes of freeze-drying. Preliminary studies employed a homogeneous freeze-drying process on 96-well plates. It was found that K65M and K133M surface mutations, the use of acetate buffer, low pH, increased ionic strength, and the use of NaCl, caused the most monomer loss; whereas S75K, C226S, and L50K mutations, high pH, and the use of Na2SO4 caused the least monomer loss. Several in-silico modelling tools were used to design mutants for studying the impact of protein conformational stability. Rosetta software, RMSF and B-factor analyses were used to evaluate the mutant candidates and restrict the mutations mainly located in the flexible regions. Unstable mutants were prepared as controls to validate the prediction accuracy. In freeze-drying, most of the stabilising mutants had 20% less monomer loss than C226S, while the destabilising ones had 14-46% more monomer loss. Tm and ΔΔG estimated the monomer loss in freeze-drying with low degree of accuracy. Compared to freeze-drying, a more distinct difference was observed in the aqueous phase as all the destabilising mutants aggregated more than 5 times faster than C226S and the stabilising mutants did. Tm correlated well with the aggregation in aqueous phase, indicating conformational stability was more important in aqueous phase than that in freeze-drying. In addition, excipients barely exerted influence on the stable mutants but provided sufficient protection for the unstable ones, which was reflected by their correlations to Tm values. The rank-order of excipient effects for individual mutants, relative to that of wild type, became less similar as the mutant ΔTm magnitude increased. |
author2 |
Dalby, Paul ; Brocchini, Steve |
author_facet |
Dalby, Paul ; Brocchini, Steve Zhang, C. |
author |
Zhang, C. |
author_sort |
Zhang, C. |
title |
Freeze-drying of engineered proteins using protein modelling tools and experimental validation |
title_short |
Freeze-drying of engineered proteins using protein modelling tools and experimental validation |
title_full |
Freeze-drying of engineered proteins using protein modelling tools and experimental validation |
title_fullStr |
Freeze-drying of engineered proteins using protein modelling tools and experimental validation |
title_full_unstemmed |
Freeze-drying of engineered proteins using protein modelling tools and experimental validation |
title_sort |
freeze-drying of engineered proteins using protein modelling tools and experimental validation |
publisher |
University College London (University of London) |
publishDate |
2017 |
url |
https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.746503 |
work_keys_str_mv |
AT zhangc freezedryingofengineeredproteinsusingproteinmodellingtoolsandexperimentalvalidation |
_version_ |
1718990979884646400 |