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Lookup NU author(s): Micael Karlberg, Joao Victor de De Souza Cunha, Lanyu Fan, Arathi Kizhedath, Dr Agnieszka Bronowska, Professor Jarka Glassey
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.Monoclonal antibodies (mAbs) constitute a rapidly growing biopharmaceutical sector. However, their growth is impeded by high failure rates originating from failed clinical trials and developability issues in process development. There is, therefore, a growing need for better in silico tools to aid in risk assessment of mAb candidates to promote early-stage screening of potentially problematic mAb candidates. In this study, a quantitative structure–activity relationship (QSAR) modelling workflow was designed for the prediction of hydrophobic interaction chromatography (HIC) retention times of mAbs. Three novel descriptor sets derived from primary sequence, homology modelling, and atomistic molecular dynamics (MD) simulations were developed and assessed to determine the necessary level of structural resolution needed to accurately capture the relationship between mAb structures and HIC retention times. The results showed that descriptors derived from 3D structures obtained after MD simulations were the most suitable for HIC retention time prediction with a R2 = 0.63 in an external test set. It was found that when using homology modelling, the resulting 3D structures became biased towards the used structural template. Performing an MD simulation therefore proved to be a necessary post-processing step for the mAb structures in order to relax the structures and allow them to attain a more natural conformation. Based on the results, the proposed workflow in this paper could therefore potentially contribute to aid in risk assessment of mAb candidates in early development.
Author(s): Karlberg M, de Souza JV, Fan L, Kizhedath A, Bronowska AK, Glassey J
Publication type: Article
Publication status: Published
Journal: International Journal of Molecular Sciences
Year: 2020
Volume: 21
Issue: 21
Online publication date: 28/10/2020
Acceptance date: 27/10/2020
Date deposited: 04/12/2020
ISSN (print): 1661-6596
ISSN (electronic): 1422-0067
Publisher: MDPI AG
URL: https://doi.org/10.3390/ijms21218037
DOI: 10.3390/ijms21218037
PubMed id: 33126648
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