Computational-Driven Epitope Verification and Affinity Maturation of TLR4-Targeting Antibodies
Toll-like receptor (TLR) signaling plays a critical role in the induction and progression of autoimmune diseases such as rheumatoid arthritis, systemic lupus erythematous, experimental autoimmune encephalitis, type 1 diabetes mellitus and neurodegenerative diseases. Deciphering antigen recognition b...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-06-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/22/11/5989 |
| _version_ | 1797531741677682688 |
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| author | Bilal Ahmad Maria Batool Moon-Suk Kim Sangdun Choi |
| author_facet | Bilal Ahmad Maria Batool Moon-Suk Kim Sangdun Choi |
| author_sort | Bilal Ahmad |
| collection | DOAJ |
| description | Toll-like receptor (TLR) signaling plays a critical role in the induction and progression of autoimmune diseases such as rheumatoid arthritis, systemic lupus erythematous, experimental autoimmune encephalitis, type 1 diabetes mellitus and neurodegenerative diseases. Deciphering antigen recognition by antibodies provides insights and defines the mechanism of action into the progression of immune responses. Multiple strategies, including phage display and hybridoma technologies, have been used to enhance the affinity of antibodies for their respective epitopes. Here, we investigate the TLR4 antibody-binding epitope by computational-driven approach. We demonstrate that three important residues, i.e., Y328, N329, and K349 of TLR4 antibody binding epitope identified upon in silico mutagenesis, affect not only the interaction and binding affinity of antibody but also influence the structural integrity of TLR4. Furthermore, we predict a novel epitope at the TLR4-MD2 interface which can be targeted and explored for therapeutic antibodies and small molecules. This technique provides an in-depth insight into antibody–antigen interactions at the resolution and will be beneficial for the development of new monoclonal antibodies. Computational techniques, if coupled with experimental methods, will shorten the duration of rational design and development of antibody therapeutics. |
| first_indexed | 2024-03-10T10:48:01Z |
| format | Article |
| id | doaj.art-abd86c4a28ae42e6b7afc8138b5dcda6 |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-10T10:48:01Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-abd86c4a28ae42e6b7afc8138b5dcda62023-11-21T22:25:39ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672021-06-012211598910.3390/ijms22115989Computational-Driven Epitope Verification and Affinity Maturation of TLR4-Targeting AntibodiesBilal Ahmad0Maria Batool1Moon-Suk Kim2Sangdun Choi3Department of Molecular Science and Technology, Ajou University, Suwon 16499, KoreaDepartment of Molecular Science and Technology, Ajou University, Suwon 16499, KoreaDepartment of Molecular Science and Technology, Ajou University, Suwon 16499, KoreaDepartment of Molecular Science and Technology, Ajou University, Suwon 16499, KoreaToll-like receptor (TLR) signaling plays a critical role in the induction and progression of autoimmune diseases such as rheumatoid arthritis, systemic lupus erythematous, experimental autoimmune encephalitis, type 1 diabetes mellitus and neurodegenerative diseases. Deciphering antigen recognition by antibodies provides insights and defines the mechanism of action into the progression of immune responses. Multiple strategies, including phage display and hybridoma technologies, have been used to enhance the affinity of antibodies for their respective epitopes. Here, we investigate the TLR4 antibody-binding epitope by computational-driven approach. We demonstrate that three important residues, i.e., Y328, N329, and K349 of TLR4 antibody binding epitope identified upon in silico mutagenesis, affect not only the interaction and binding affinity of antibody but also influence the structural integrity of TLR4. Furthermore, we predict a novel epitope at the TLR4-MD2 interface which can be targeted and explored for therapeutic antibodies and small molecules. This technique provides an in-depth insight into antibody–antigen interactions at the resolution and will be beneficial for the development of new monoclonal antibodies. Computational techniques, if coupled with experimental methods, will shorten the duration of rational design and development of antibody therapeutics.https://www.mdpi.com/1422-0067/22/11/5989antibodyepitopemolecular dynamicsmutationtoll-like receptor |
| spellingShingle | Bilal Ahmad Maria Batool Moon-Suk Kim Sangdun Choi Computational-Driven Epitope Verification and Affinity Maturation of TLR4-Targeting Antibodies International Journal of Molecular Sciences antibody epitope molecular dynamics mutation toll-like receptor |
| title | Computational-Driven Epitope Verification and Affinity Maturation of TLR4-Targeting Antibodies |
| title_full | Computational-Driven Epitope Verification and Affinity Maturation of TLR4-Targeting Antibodies |
| title_fullStr | Computational-Driven Epitope Verification and Affinity Maturation of TLR4-Targeting Antibodies |
| title_full_unstemmed | Computational-Driven Epitope Verification and Affinity Maturation of TLR4-Targeting Antibodies |
| title_short | Computational-Driven Epitope Verification and Affinity Maturation of TLR4-Targeting Antibodies |
| title_sort | computational driven epitope verification and affinity maturation of tlr4 targeting antibodies |
| topic | antibody epitope molecular dynamics mutation toll-like receptor |
| url | https://www.mdpi.com/1422-0067/22/11/5989 |
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