Toggle Main Menu Toggle Search

Open Access padlockePrints

Qsar implementation for hic retention time prediction of mabs using fab structure: A comparison between structural representations

Lookup NU author(s): Micael Karlberg, Joao Victor de De Souza Cunha, Lanyu Fan, Arathi Kizhedath, Dr Agnieszka Bronowska, Professor Jarka Glassey

Downloads


Licence

This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 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.


Publication metadata

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


Altmetrics

Altmetrics provided by Altmetric


Actions

Find at Newcastle University icon    Link to this publication


Share