PyBindE: Development of a Simple Python MM-PBSA Implementation for Estimating Protein-Protein and Protein-Ligand Binding Energies

Detalhes bibliográficos
Autor(a) principal: Vitorino, João Nuno Marques
Data de Publicação: 2022
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10451/53791
Resumo: Tese de mestrado, Bioquímica (Bioquímica), Universidade de Lisboa, Faculdade de Ciências, 2022
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spelling PyBindE: Development of a Simple Python MM-PBSA Implementation for Estimating Protein-Protein and Protein-Ligand Binding EnergiesDinâmica MolecularMM-PBSAEletrostáticaAssociação ProteicaEnergias de AssociaçãoTeses de mestrado - 2022Departamento de Química e BioquímicaTese de mestrado, Bioquímica (Bioquímica), Universidade de Lisboa, Faculdade de Ciências, 2022Given the importance of proteins, the study of their interactions and binding affinities has been one of the most broadly populated fields of research for many years. Many approaches exist to calculate protein-protein and protein-ligand binding free energies, with single-trajectory MM-PBSA being a pop ular choice due to its more rigorous theoretical framework, when compared with methods, such as molec ular docking, while still possessing reasonable speed. MM-PBSA is particularly useful when the relative energy differences between system configurations are concerned, being able to provide insights about the forces involved in the binding process and their energetic contribution. In the present work, we describe a newly developed, DelPhi-based, single-trajectory MM-PBSA im plementation (PyBindE) written in Python, designed to be compatible with GROMOS force fields. A validation of this method was performed using a set of 37 HIV-1 protease-inhibitor complexes with experimentally-determined inhibition constants. These systems were also used as a validation set for g_mmpbsa, one widely used MM-PBSA implementation, originally validated using AMBER, thus com parisons with this method can be drawn. Molecular dynamics (MD) simulations of 150 ns were run in triplicate for every system, and MM-PBSA calculations were performed on the full trajectories, in 1500 snapshots per replicate. For 9 of the systems used for validation, the ligands of these systems con tained amine groups with pKa values ( 9) above physiological pH, and as such, different protonation scenarios for the ligands and the catalytic aspartate residues (Asp-25) were also explored. Furthermore, the impact of different values of the solute dielectric constant, on the correlation with experimental data, was studied for all different protonation cases. A practical application of PyBindE is also presented for the case of β-2 Microglobulin (β2M) D76N mutants, the causing-agents of a fatal form of amyloidosis. MM-PBSA was used to study the binding of 212 dimers derived from a Monte-Carlo Ensemble Docking protocol, determining the forces responsible for their binding and aggregation, and ranking the most stable binding modes. MM-PBSA calculations were run on 100 ns of MD trajectory for each dimer. Results of the comparison with g_mmpbsa are also analysed. Our validation results show an adequate correlation, 0.56, with experimental data when the correct ligand and catalytic aspartate residue protonations are employed, with a dielectric constant of 8. We found that underestimating the polar solvation contribution to the binding free energy resulted in an improvement of the correlations with our method, suggesting the need to optimize our parameterization and/or polar solvation calculation procedures. Regardless, our correlation results are higher than those reported for many standard MM-PBSA methods, with minimal parameter tweaking. The usefulness of PybindE was also highlighted in the calculation of binding free energies for β2M dimers. This method allowed the distinction of several binding modes from which different oligomerization patterns were then predicted. Overall, the results using PyBindE for the study of protein-protein binding affinities revealed a higher accuracy than g_mmpbsa, that often predicted positive binding energies suggesting unbinding events, which were not observed in the MD simulations.Machuqueiro, Miguel Ângelo dos SantosRepositório da Universidade de LisboaVitorino, João Nuno Marques2022-07-14T08:23:00Z202220222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10451/53791enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-08T16:59:56Zoai:repositorio.ul.pt:10451/53791Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:04:45.972397Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv PyBindE: Development of a Simple Python MM-PBSA Implementation for Estimating Protein-Protein and Protein-Ligand Binding Energies
title PyBindE: Development of a Simple Python MM-PBSA Implementation for Estimating Protein-Protein and Protein-Ligand Binding Energies
spellingShingle PyBindE: Development of a Simple Python MM-PBSA Implementation for Estimating Protein-Protein and Protein-Ligand Binding Energies
Vitorino, João Nuno Marques
Dinâmica Molecular
MM-PBSA
Eletrostática
Associação Proteica
Energias de Associação
Teses de mestrado - 2022
Departamento de Química e Bioquímica
title_short PyBindE: Development of a Simple Python MM-PBSA Implementation for Estimating Protein-Protein and Protein-Ligand Binding Energies
title_full PyBindE: Development of a Simple Python MM-PBSA Implementation for Estimating Protein-Protein and Protein-Ligand Binding Energies
title_fullStr PyBindE: Development of a Simple Python MM-PBSA Implementation for Estimating Protein-Protein and Protein-Ligand Binding Energies
title_full_unstemmed PyBindE: Development of a Simple Python MM-PBSA Implementation for Estimating Protein-Protein and Protein-Ligand Binding Energies
title_sort PyBindE: Development of a Simple Python MM-PBSA Implementation for Estimating Protein-Protein and Protein-Ligand Binding Energies
author Vitorino, João Nuno Marques
author_facet Vitorino, João Nuno Marques
author_role author
dc.contributor.none.fl_str_mv Machuqueiro, Miguel Ângelo dos Santos
Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Vitorino, João Nuno Marques
dc.subject.por.fl_str_mv Dinâmica Molecular
MM-PBSA
Eletrostática
Associação Proteica
Energias de Associação
Teses de mestrado - 2022
Departamento de Química e Bioquímica
topic Dinâmica Molecular
MM-PBSA
Eletrostática
Associação Proteica
Energias de Associação
Teses de mestrado - 2022
Departamento de Química e Bioquímica
description Tese de mestrado, Bioquímica (Bioquímica), Universidade de Lisboa, Faculdade de Ciências, 2022
publishDate 2022
dc.date.none.fl_str_mv 2022-07-14T08:23:00Z
2022
2022
2022-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10451/53791
url http://hdl.handle.net/10451/53791
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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