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Development of a structure-based computational simulation to optimize the blocking efficacy of pro-antibodies

The on-target toxicity of monoclonal antibodies (Abs) is mainly due to the fact that Abs cannot distinguish target antigens (Ags) expressed in disease regions from those in normal tissues during systemic administration. In order to overcome this issue, we “copied” an autologous Ab hinge as an “Ab lo...

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Autores principales: Huang, Bo-Cheng, Lu, Yun-Chi, Liao, Jun-Min, Liu, Hui-Ju, Hong, Shih-Ting, Hsieh, Yuan-Chin, Chuang, Chih-Hung, Chen, Huei-Jen, Liao, Tzu-Yi, Ho, Kai-Wen, Wang, Yeng-Tseng, Cheng, Tian-Lu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society of Chemistry 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8293997/
https://www.ncbi.nlm.nih.gov/pubmed/34349949
http://dx.doi.org/10.1039/d1sc01748a
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author Huang, Bo-Cheng
Lu, Yun-Chi
Liao, Jun-Min
Liu, Hui-Ju
Hong, Shih-Ting
Hsieh, Yuan-Chin
Chuang, Chih-Hung
Chen, Huei-Jen
Liao, Tzu-Yi
Ho, Kai-Wen
Wang, Yeng-Tseng
Cheng, Tian-Lu
author_facet Huang, Bo-Cheng
Lu, Yun-Chi
Liao, Jun-Min
Liu, Hui-Ju
Hong, Shih-Ting
Hsieh, Yuan-Chin
Chuang, Chih-Hung
Chen, Huei-Jen
Liao, Tzu-Yi
Ho, Kai-Wen
Wang, Yeng-Tseng
Cheng, Tian-Lu
author_sort Huang, Bo-Cheng
collection PubMed
description The on-target toxicity of monoclonal antibodies (Abs) is mainly due to the fact that Abs cannot distinguish target antigens (Ags) expressed in disease regions from those in normal tissues during systemic administration. In order to overcome this issue, we “copied” an autologous Ab hinge as an “Ab lock” and “pasted” it on the binding site of the Ab by connecting a protease substrate and linker in between to generate a pro-Ab, which can be specifically activated in the disease region to enhance Ab selectivity and reduce side effects. Previously, we reported that 70% of pro-Abs can achieve more than 100-fold blocking ability compared to the parental Abs. However, 30% of pro-Abs do not have such efficient blocking ability. This is because the same Ab lock linker cannot be applied to every Ab due to the differences in the complementarity-determining region (CDR) loops. Here we designed a method which uses structure-based computational simulation (MSCS) to optimize the blocking ability of the Ab lock for all Ab drugs. MSCS can precisely adjust the amino acid composition of the linker between the Ab lock and Ab drug with the assistance of molecular simulation. We selected αPD-1, αIL-1β, αCTLA-4 and αTNFα Ab as models and attached the Ab lock with various linkers (L1 to L7) to form pro-Abs by MSCS, respectively. The resulting cover rates of the Ab lock with various linkers compared to the Ab drug were in the range 28.33–42.33%. The recombinant pro-Abs were generated by MSCS prediction in order to verify the application of molecular simulation for pro-Ab development. The binding kinetics effective concentrations (EC-50) for αPD-1 (200-250-fold), αIL-1β (152-186-fold), αCTLA-4 (68-150-fold) and αTNFα Ab (20-123-fold) were presented as the blocking ability of pro-Ab compared to the Ab drug. Further, there was a positive correlation between cover rate and blocking ability of all pro-Ab candidates. The results suggested that MSCS was able to predict the Ab lock linker most suitable for application to αPD-1, αIL-1β, αCTLA-4 and αTNFα Ab to form pro-Abs efficiently. The success of MSCS in optimizing the pro-Ab can aid the development of next-generation pro-Ab drugs to significantly improve Ab-based therapies and thus patients' quality of life.
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spelling pubmed-82939972021-08-03 Development of a structure-based computational simulation to optimize the blocking efficacy of pro-antibodies Huang, Bo-Cheng Lu, Yun-Chi Liao, Jun-Min Liu, Hui-Ju Hong, Shih-Ting Hsieh, Yuan-Chin Chuang, Chih-Hung Chen, Huei-Jen Liao, Tzu-Yi Ho, Kai-Wen Wang, Yeng-Tseng Cheng, Tian-Lu Chem Sci Chemistry The on-target toxicity of monoclonal antibodies (Abs) is mainly due to the fact that Abs cannot distinguish target antigens (Ags) expressed in disease regions from those in normal tissues during systemic administration. In order to overcome this issue, we “copied” an autologous Ab hinge as an “Ab lock” and “pasted” it on the binding site of the Ab by connecting a protease substrate and linker in between to generate a pro-Ab, which can be specifically activated in the disease region to enhance Ab selectivity and reduce side effects. Previously, we reported that 70% of pro-Abs can achieve more than 100-fold blocking ability compared to the parental Abs. However, 30% of pro-Abs do not have such efficient blocking ability. This is because the same Ab lock linker cannot be applied to every Ab due to the differences in the complementarity-determining region (CDR) loops. Here we designed a method which uses structure-based computational simulation (MSCS) to optimize the blocking ability of the Ab lock for all Ab drugs. MSCS can precisely adjust the amino acid composition of the linker between the Ab lock and Ab drug with the assistance of molecular simulation. We selected αPD-1, αIL-1β, αCTLA-4 and αTNFα Ab as models and attached the Ab lock with various linkers (L1 to L7) to form pro-Abs by MSCS, respectively. The resulting cover rates of the Ab lock with various linkers compared to the Ab drug were in the range 28.33–42.33%. The recombinant pro-Abs were generated by MSCS prediction in order to verify the application of molecular simulation for pro-Ab development. The binding kinetics effective concentrations (EC-50) for αPD-1 (200-250-fold), αIL-1β (152-186-fold), αCTLA-4 (68-150-fold) and αTNFα Ab (20-123-fold) were presented as the blocking ability of pro-Ab compared to the Ab drug. Further, there was a positive correlation between cover rate and blocking ability of all pro-Ab candidates. The results suggested that MSCS was able to predict the Ab lock linker most suitable for application to αPD-1, αIL-1β, αCTLA-4 and αTNFα Ab to form pro-Abs efficiently. The success of MSCS in optimizing the pro-Ab can aid the development of next-generation pro-Ab drugs to significantly improve Ab-based therapies and thus patients' quality of life. The Royal Society of Chemistry 2021-06-14 /pmc/articles/PMC8293997/ /pubmed/34349949 http://dx.doi.org/10.1039/d1sc01748a Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by-nc/3.0/
spellingShingle Chemistry
Huang, Bo-Cheng
Lu, Yun-Chi
Liao, Jun-Min
Liu, Hui-Ju
Hong, Shih-Ting
Hsieh, Yuan-Chin
Chuang, Chih-Hung
Chen, Huei-Jen
Liao, Tzu-Yi
Ho, Kai-Wen
Wang, Yeng-Tseng
Cheng, Tian-Lu
Development of a structure-based computational simulation to optimize the blocking efficacy of pro-antibodies
title Development of a structure-based computational simulation to optimize the blocking efficacy of pro-antibodies
title_full Development of a structure-based computational simulation to optimize the blocking efficacy of pro-antibodies
title_fullStr Development of a structure-based computational simulation to optimize the blocking efficacy of pro-antibodies
title_full_unstemmed Development of a structure-based computational simulation to optimize the blocking efficacy of pro-antibodies
title_short Development of a structure-based computational simulation to optimize the blocking efficacy of pro-antibodies
title_sort development of a structure-based computational simulation to optimize the blocking efficacy of pro-antibodies
topic Chemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8293997/
https://www.ncbi.nlm.nih.gov/pubmed/34349949
http://dx.doi.org/10.1039/d1sc01748a
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