UCL logo

UCL Discovery

UCL home » Library Services » Electronic resources » UCL Discovery

Identification of Protein-Excipient Interaction Hotspots Using Computational Approaches

Barata, TS; Zhang, C; Dalby, PA; Brocchini, S; Zloh, M; (2016) Identification of Protein-Excipient Interaction Hotspots Using Computational Approaches. International Journal of Molecular Sciences , 17(6) (853) 10.3390/ijms17060853. Green open access

[img]
Preview
Text
Identification of Protein-Excipient Interaction Hotspots Using Computational Approaches.pdf - ["content_typename_Published version" not defined]

Download (12MB) | Preview

Abstract

Protein formulation development relies on the selection of excipients that inhibit protein–protein interactions preventing aggregation. Empirical strategies involve screening many excipient and buffer combinations using force degradation studies. Such methods do not readily provide information on intermolecular interactions responsible for the protective effects of excipients. This study describes a molecular docking approach to screen and rank interactions allowing for the identification of protein–excipient hotspots to aid in the selection of excipients to be experimentally screened. Previously published work with Drosophila Su(dx) was used to develop and validate the computational methodology, which was then used to determine the formulation hotspots for Fab A33. Commonly used excipients were examined and compared to the regions in Fab A33 prone to protein–protein interactions that could lead to aggregation. This approach could provide information on a molecular level about the protective interactions of excipients in protein formulations to aid the more rational development of future formulations.

Type: Article
Title: Identification of Protein-Excipient Interaction Hotspots Using Computational Approaches
Identifier: 10.3390/ijms17060853
Open access status: An open access version is available from UCL Discovery
DOI: 10.3390/ijms17060853
Additional information: © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
Keywords: Science & Technology, Life Sciences & Biomedicine, Physical Sciences, Biochemistry & Molecular Biology, Chemistry, Multidisciplinary, Chemistry, molecular docking, protein-excipient interactions, protein stability, molecular dynamics, Fab formulation, GENERIC EVOLUTIONARY METHOD, MOLECULAR DOCKING, SCORING FUNCTIONS, CONFORMATIONAL STABILITY, MONOCLONAL-ANTIBODIES, LIGAND DOCKING, AGGREGATION, FORMULATION, SOLUBILITY, PREDICTION
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > UCL School of Pharmacy
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > UCL School of Pharmacy > Pharmaceutics
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Biochemical Engineering
URI: http://discovery.ucl.ac.uk/id/eprint/1499758
Downloads since deposit
91Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item