Literature DB >> 29325924

Prediction of the Hydrogen Peroxide-Induced Methionine Oxidation Propensity in Monoclonal Antibodies.

Neeraj J Agrawal1, Andrew Dykstra2, Jane Yang2, Hai Yue2, Xichdao Nguyen2, Carl Kolvenbach2, Nicolas Angell2.   

Abstract

Methionine oxidation in therapeutic antibodies can impact the product's stability, clinical efficacy, and safety and hence it is desirable to address the methionine oxidation liability during antibody discovery and development phase. Although the current experimental approaches can identify the oxidation-labile methionine residues, their application is limited mostly to the development phase. We demonstrate an in silico method that can be used to predict oxidation-labile residues based solely on the antibody sequence and structure information. Since antibody sequence information is available in the discovery phase, the in silico method can be applied very early on to identify the oxidation-labile methionine residues and subsequently address the oxidation liability. We believe that the in silico method for methionine oxidation liability assessment can aid in antibody discovery and development phase to address the liability in a more rational way.
Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  biotechnology; in silico modeling; molecular modeling; monoclonal antibody; oxidation

Mesh:

Substances:

Year:  2018        PMID: 29325924     DOI: 10.1016/j.xphs.2018.01.002

Source DB:  PubMed          Journal:  J Pharm Sci        ISSN: 0022-3549            Impact factor:   3.534


  6 in total

1.  Effect of Chemical Oxidation on the Higher Order Structure, Stability, Aggregation, and Biological Function of Interferon Alpha-2a: Role of Local Structural Changes Detected by 2D NMR.

Authors:  Dinen D Shah; Surinder M Singh; Krishna M G Mallela
Journal:  Pharm Res       Date:  2018-10-15       Impact factor: 4.200

2.  A systematic review of recent trends in research on therapeutically significant L-asparaginase and acute lymphoblastic leukemia.

Authors:  Susan Aishwarya Suresh; Selvarajan Ethiraj; K N Rajnish
Journal:  Mol Biol Rep       Date:  2022-07-10       Impact factor: 2.742

3.  Modulation of amyloid fibrillation of bovine β-lactoglobulin by selective methionine oxidation.

Authors:  Sanhita Maity; Nayim Sepay; Sampa Pal; Subrata Sardar; Hasan Parvej; Swarnali Pal; Jishnu Chakraborty; Anirban Pradhan; Umesh Chandra Halder
Journal:  RSC Adv       Date:  2021-03-17       Impact factor: 3.361

4.  Prediction of methionine oxidation risk in monoclonal antibodies using a machine learning method.

Authors:  Kannan Sankar; Kam Hon Hoi; Yizhou Yin; Prasanna Ramachandran; Nisana Andersen; Amy Hilderbrand; Paul McDonald; Christoph Spiess; Qing Zhang
Journal:  MAbs       Date:  2018-09-25       Impact factor: 5.857

5.  Machine Learning Enables Accurate Prediction of Asparagine Deamidation Probability and Rate.

Authors:  Jared A Delmar; Jihong Wang; Seo Woo Choi; Jason A Martins; John P Mikhail
Journal:  Mol Ther Methods Clin Dev       Date:  2019-10-01       Impact factor: 6.698

Review 6.  In silico prediction of post-translational modifications in therapeutic antibodies.

Authors:  Shabdita Vatsa
Journal:  MAbs       Date:  2022 Jan-Dec       Impact factor: 5.857

  6 in total

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