Fragment Dissolved molecular dynamics: A systematic and efficient method to locate binding sites.
Fragment-based drug discovery (FBDD) has been popular in the last decade, but some drawbacks, such as protein denaturation or ligand aggregation, have not yet clearly overcome in the framework of biomolecular simulations. In this work a systematic and semi-automatic method is presented as a novel pr...
| Autores: | , , , , , |
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| Tipo de documento: | artigo |
| Estado: | Versión aceptada para publicación |
| Data de publicação: | 2020 |
| País: | España |
| Recursos: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositório: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:2445/188360 |
| Acesso em linha: | https://hdl.handle.net/2445/188360 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Dinàmica molecular Disseny de medicaments Molecular dynamics Drug design |
| Resumo: | Fragment-based drug discovery (FBDD) has been popular in the last decade, but some drawbacks, such as protein denaturation or ligand aggregation, have not yet clearly overcome in the framework of biomolecular simulations. In this work a systematic and semi-automatic method is presented as a novel proposal, named fragment dissolved Molecular Dynamics (fdMD), to improve research in future FBDD projects. Our method employs simulation boxes of solvated small fragments, adding a repulsive Lennard-Jones potential term to avoid aggregation, which can be easily used to solvate the object of interest. This method has the advantage of solvating the target with a low number of ligands, thus preventing this way denaturation of the target, while simultaneously generating a database of ligand-solvated boxes that can be used with other targets. A number of scripts are made available to analyze the results and obtain the descriptors proposed as a means of trustfully discard spurious binding sites. To test our method, four sets of different complexity have been solvated with ligand boxes and four molecular dynamics runs of 200 ns length have been run for each system, which have been extended up to 1 μs when needed. The reported results point that the selected number of replicas are enough to identify the correct binding sites irrespective of the initial structure, even in the case of proteins having several close binding sites for the same ligand. Among the proposed descriptors, average MMGBSA and average KDEEP energies emerge as the most robust ones. |
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