Structure-guided engineering and molecular simulations to design a potent monoclonal antibody to target aP2 antigen for adaptive immune response instigation against type 2 diabetes
<h3>Introduction</h3><p dir="ltr">Diabetes mellitus (DM) is recognized as one of the oldest chronic diseases and has become a significant public health issue, necessitating innovative therapeutic strategies to enhance patient outcomes. Traditional treatments have provided...
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| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , |
| منشور في: |
2024
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| _version_ | 1864513543577010176 |
|---|---|
| author | Abbas Khan (5141000) |
| author2 | Muhammad Ammar Zahid (18123775) Anwar Mohammad (8383539) Abdelali Agouni (181926) |
| author2_role | author author author |
| author_facet | Abbas Khan (5141000) Muhammad Ammar Zahid (18123775) Anwar Mohammad (8383539) Abdelali Agouni (181926) |
| author_role | author |
| dc.creator.none.fl_str_mv | Abbas Khan (5141000) Muhammad Ammar Zahid (18123775) Anwar Mohammad (8383539) Abdelali Agouni (181926) |
| dc.date.none.fl_str_mv | 2024-03-08T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.3389/fimmu.2024.1357342 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Structure-guided_engineering_and_molecular_simulations_to_design_a_potent_monoclonal_antibody_to_target_aP2_antigen_for_adaptive_immune_response_instigation_against_type_2_diabetes/29651015 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biological sciences Bioinformatics and computational biology Biomedical and clinical sciences Immunology Medical biochemistry and metabolomics AP2 CA33 antibody structural engineering docking simulation free energy calculation |
| dc.title.none.fl_str_mv | Structure-guided engineering and molecular simulations to design a potent monoclonal antibody to target aP2 antigen for adaptive immune response instigation against type 2 diabetes |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <h3>Introduction</h3><p dir="ltr">Diabetes mellitus (DM) is recognized as one of the oldest chronic diseases and has become a significant public health issue, necessitating innovative therapeutic strategies to enhance patient outcomes. Traditional treatments have provided limited success, highlighting the need for novel approaches in managing this complex disease.</p><h3>Methods</h3><p dir="ltr">In our study, we employed graph signature-based methodologies in conjunction with molecular simulation and free energy calculations. The objective was to engineer the CA33 monoclonal antibody for effective targeting of the aP2 antigen, aiming to elicit a potent immune response. This approach involved screening a mutational landscape comprising 57 mutants to identify modifications that yield significant enhancements in binding efficacy and stability.</p><h3>Results</h3><p dir="ltr">Analysis of the mutational landscape revealed that only five substitutions resulted in noteworthy improvements. Among these, mutations T94M, A96E, A96Q, and T94W were identified through molecular docking experiments to exhibit higher docking scores compared to the wild-type. Further validation was provided by calculating the dissociation constant (KD), which showed a similar trend in favor of these mutations. Molecular simulation analyses highlighted T94M as the most stable complex, with reduced internal fluctuations upon binding. Principal components analysis (PCA) indicated that both the wild-type and T94M mutant displayed similar patterns of constrained and restricted motion across principal components. The free energy landscape analysis underscored a single metastable state for all complexes, indicating limited structural variability and potential for high therapeutic efficacy against aP2. Total binding free energy (TBE) calculations further supported the superior performance of the T94M mutation, with TBE values demonstrating the enhanced binding affinity of selected mutants over the wild-type.</p><h3>Discussion</h3><p dir="ltr">Our findings suggest that the T94M substitution, along with other identified mutations, significantly enhances the therapeutic potential of the CA33 antibody against DM by improving its binding affinity and stability. These results not only contribute to a deeper understanding of antibody-antigen interactions in the context of DM but also provide a valuable framework for the rational design of antibodies aimed at targeting this disease more effectively.</p><h2>Other Information</h2><p dir="ltr">Published in: Frontiers in Immunology<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3389/fimmu.2024.1357342" target="_blank">https://dx.doi.org/10.3389/fimmu.2024.1357342</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_f67268d6ad21a78454f68963bf048b76 |
| identifier_str_mv | 10.3389/fimmu.2024.1357342 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/29651015 |
| publishDate | 2024 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Structure-guided engineering and molecular simulations to design a potent monoclonal antibody to target aP2 antigen for adaptive immune response instigation against type 2 diabetesAbbas Khan (5141000)Muhammad Ammar Zahid (18123775)Anwar Mohammad (8383539)Abdelali Agouni (181926)Biological sciencesBioinformatics and computational biologyBiomedical and clinical sciencesImmunologyMedical biochemistry and metabolomicsAP2CA33antibodystructural engineeringdockingsimulationfree energy calculation<h3>Introduction</h3><p dir="ltr">Diabetes mellitus (DM) is recognized as one of the oldest chronic diseases and has become a significant public health issue, necessitating innovative therapeutic strategies to enhance patient outcomes. Traditional treatments have provided limited success, highlighting the need for novel approaches in managing this complex disease.</p><h3>Methods</h3><p dir="ltr">In our study, we employed graph signature-based methodologies in conjunction with molecular simulation and free energy calculations. The objective was to engineer the CA33 monoclonal antibody for effective targeting of the aP2 antigen, aiming to elicit a potent immune response. This approach involved screening a mutational landscape comprising 57 mutants to identify modifications that yield significant enhancements in binding efficacy and stability.</p><h3>Results</h3><p dir="ltr">Analysis of the mutational landscape revealed that only five substitutions resulted in noteworthy improvements. Among these, mutations T94M, A96E, A96Q, and T94W were identified through molecular docking experiments to exhibit higher docking scores compared to the wild-type. Further validation was provided by calculating the dissociation constant (KD), which showed a similar trend in favor of these mutations. Molecular simulation analyses highlighted T94M as the most stable complex, with reduced internal fluctuations upon binding. Principal components analysis (PCA) indicated that both the wild-type and T94M mutant displayed similar patterns of constrained and restricted motion across principal components. The free energy landscape analysis underscored a single metastable state for all complexes, indicating limited structural variability and potential for high therapeutic efficacy against aP2. Total binding free energy (TBE) calculations further supported the superior performance of the T94M mutation, with TBE values demonstrating the enhanced binding affinity of selected mutants over the wild-type.</p><h3>Discussion</h3><p dir="ltr">Our findings suggest that the T94M substitution, along with other identified mutations, significantly enhances the therapeutic potential of the CA33 antibody against DM by improving its binding affinity and stability. These results not only contribute to a deeper understanding of antibody-antigen interactions in the context of DM but also provide a valuable framework for the rational design of antibodies aimed at targeting this disease more effectively.</p><h2>Other Information</h2><p dir="ltr">Published in: Frontiers in Immunology<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3389/fimmu.2024.1357342" target="_blank">https://dx.doi.org/10.3389/fimmu.2024.1357342</a></p>2024-03-08T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.3389/fimmu.2024.1357342https://figshare.com/articles/journal_contribution/Structure-guided_engineering_and_molecular_simulations_to_design_a_potent_monoclonal_antibody_to_target_aP2_antigen_for_adaptive_immune_response_instigation_against_type_2_diabetes/29651015CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/296510152024-03-08T03:00:00Z |
| spellingShingle | Structure-guided engineering and molecular simulations to design a potent monoclonal antibody to target aP2 antigen for adaptive immune response instigation against type 2 diabetes Abbas Khan (5141000) Biological sciences Bioinformatics and computational biology Biomedical and clinical sciences Immunology Medical biochemistry and metabolomics AP2 CA33 antibody structural engineering docking simulation free energy calculation |
| status_str | publishedVersion |
| title | Structure-guided engineering and molecular simulations to design a potent monoclonal antibody to target aP2 antigen for adaptive immune response instigation against type 2 diabetes |
| title_full | Structure-guided engineering and molecular simulations to design a potent monoclonal antibody to target aP2 antigen for adaptive immune response instigation against type 2 diabetes |
| title_fullStr | Structure-guided engineering and molecular simulations to design a potent monoclonal antibody to target aP2 antigen for adaptive immune response instigation against type 2 diabetes |
| title_full_unstemmed | Structure-guided engineering and molecular simulations to design a potent monoclonal antibody to target aP2 antigen for adaptive immune response instigation against type 2 diabetes |
| title_short | Structure-guided engineering and molecular simulations to design a potent monoclonal antibody to target aP2 antigen for adaptive immune response instigation against type 2 diabetes |
| title_sort | Structure-guided engineering and molecular simulations to design a potent monoclonal antibody to target aP2 antigen for adaptive immune response instigation against type 2 diabetes |
| topic | Biological sciences Bioinformatics and computational biology Biomedical and clinical sciences Immunology Medical biochemistry and metabolomics AP2 CA33 antibody structural engineering docking simulation free energy calculation |