Literature DB >> 31290058

Decreasing the immunogenicity of Erwinia chrysanthemi asparaginase via protein engineering: computational approach.

Maryam Yari1,2,3, Mahboobeh Eslami3, Mohammad Bagher Ghoshoon2,3,4, Navid Nezafat5,6, Younes Ghasemi7,8,9,10.   

Abstract

Immunogenicity of therapeutic proteins is one of the main challenges in disease treatment. L-Asparaginase is an important enzyme in cancer treatment which sometimes leads to undesirable side effects such as immunogenic or allergic responses. Here, to decrease Erwinase (Erwinia chrysanthemiL-Asparaginase) immunogenicity, which is the main drawback of the enzyme, firstly conformational B cell epitopes of Erwinase were predicted from three-dimensional structure by three different computational methods. A few residues were defined as candidates for reducing immunogenicity of the protein by point mutation. In addition to immunogenicity and hydrophobicity, stability and binding energy of mutants were also analyzed computationally. In order to evaluate the stability of the best mutant, molecular dynamics simulation was performed. Among mutants, H240A and Q239A presented significant reduction in immunogenicity. In contrast, the immunogenicity scores of D235A slightly decreased according to two servers. Binding affinity of substrate to the active site reduced significantly in K265A and E268A. The final results of molecular dynamics simulation indicated that H240A mutation has not changed the stability, flexibility, and the total structure of desired protein. Overall, point mutation can be used for reducing immunogenicity of therapeutic proteins, in this context, in silico approaches can be used to screen suitable mutants.

Entities:  

Keywords:  Asparaginase; B cell epitope; Bioinformatics; Immunogenicity; Therapeutic protein

Mesh:

Substances:

Year:  2019        PMID: 31290058     DOI: 10.1007/s11033-019-04921-5

Source DB:  PubMed          Journal:  Mol Biol Rep        ISSN: 0301-4851            Impact factor:   2.316


  14 in total

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Journal:  Protein Sci       Date:  1993-09       Impact factor: 6.725

Review 2.  The role of dynamic conformational ensembles in biomolecular recognition.

Authors:  David D Boehr; Ruth Nussinov; Peter E Wright
Journal:  Nat Chem Biol       Date:  2009-11       Impact factor: 15.040

3.  SDM: a server for predicting effects of mutations on protein stability.

Authors:  Arun Prasad Pandurangan; Bernardo Ochoa-Montaño; David B Ascher; Tom L Blundell
Journal:  Nucleic Acids Res       Date:  2017-07-03       Impact factor: 16.971

4.  Improved side-chain torsion potentials for the Amber ff99SB protein force field.

Authors:  Kresten Lindorff-Larsen; Stefano Piana; Kim Palmo; Paul Maragakis; John L Klepeis; Ron O Dror; David E Shaw
Journal:  Proteins       Date:  2010-06

5.  SDM--a server for predicting effects of mutations on protein stability and malfunction.

Authors:  Catherine L Worth; Robert Preissner; Tom L Blundell
Journal:  Nucleic Acids Res       Date:  2011-05-18       Impact factor: 16.971

Review 6.  Immunogenicity of Biotherapeutics: Causes and Association with Posttranslational Modifications.

Authors:  Anshu Kuriakose; Narendra Chirmule; Pradip Nair
Journal:  J Immunol Res       Date:  2016-06-29       Impact factor: 4.818

7.  Mechanisms of secondary structure breakers in soluble proteins.

Authors:  Kenichiro Imai; Shigeki Mitaku
Journal:  Biophysics (Nagoya-shi)       Date:  2005-10-19

Review 8.  Immunogenicity to Biotherapeutics - The Role of Anti-drug Immune Complexes.

Authors:  Murli Krishna; Steven G Nadler
Journal:  Front Immunol       Date:  2016-02-02       Impact factor: 7.561

Review 9.  An Introduction to B-Cell Epitope Mapping and In Silico Epitope Prediction.

Authors:  Lenka Potocnakova; Mangesh Bhide; Lucia Borszekova Pulzova
Journal:  J Immunol Res       Date:  2016-12-29       Impact factor: 4.818

Review 10.  Molecular dynamics simulations: advances and applications.

Authors:  Adam Hospital; Josep Ramon Goñi; Modesto Orozco; Josep L Gelpí
Journal:  Adv Appl Bioinform Chem       Date:  2015-11-19
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  1 in total

Review 1.  Microbial L-asparaginase as a promising enzyme for treatment of various cancers.

Authors:  Farshad Darvishi; Zohreh Jahanafrooz; Ahad Mokhtarzadeh
Journal:  Appl Microbiol Biotechnol       Date:  2022-07-25       Impact factor: 5.560

  1 in total

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