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Extensive Sampling of Molecular Dynamics Simulations to Identify Reliable Protein Structures for Optimized Virtual Screening Studies: The Case of the hTRPM8 Channel
(1) Background: Virtual screening campaigns require target structures in which the pockets are properly arranged for binding. Without these, MD simulations can be used to relax the available target structures, optimizing the fine architecture of their binding sites. Among the generated frames, the b...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9317601/ https://www.ncbi.nlm.nih.gov/pubmed/35886905 http://dx.doi.org/10.3390/ijms23147558 |
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author | Gervasoni, Silvia Talarico, Carmine Manelfi, Candida Pedretti, Alessandro Vistoli, Giulio Beccari, Andrea R. |
author_facet | Gervasoni, Silvia Talarico, Carmine Manelfi, Candida Pedretti, Alessandro Vistoli, Giulio Beccari, Andrea R. |
author_sort | Gervasoni, Silvia |
collection | PubMed |
description | (1) Background: Virtual screening campaigns require target structures in which the pockets are properly arranged for binding. Without these, MD simulations can be used to relax the available target structures, optimizing the fine architecture of their binding sites. Among the generated frames, the best structures can be selected based on available experimental data. Without experimental templates, the MD trajectories can be filtered by energy-based criteria or sampled by systematic analyses. (2) Methods: A blind and methodical analysis was performed on the already reported MD run of the hTRPM8 tetrameric structures; a total of 50 frames underwent docking simulations by using a set of 1000 ligands including 20 known hTRPM8 modulators. Docking runs were performed by LiGen program and involved the frames as they are and after optimization by SCRWL4.0. For each frame, all four monomers were considered. Predictive models were developed by the EFO algorithm based on the sole primary LiGen scores. (3) Results: On average, the MD simulation progressively enhances the performance of the extracted frames, and the optimized structures perform better than the non-optimized frames (EF1% mean: 21.38 vs. 23.29). There is an overall correlation between performances and volumes of the explored pockets and the combination of the best performing frames allows to develop highly performing consensus models (EF1% = 49.83). (4) Conclusions: The systematic sampling of the entire MD run provides performances roughly comparable with those previously reached by using rationally selected frames. The proposed strategy appears to be helpful when the lack of experimental data does not allow an easy selection of the optimal structures for docking simulations. Overall, the reported docking results confirm the relevance of simulating all the monomers of an oligomer structure and emphasize the efficacy of the SCRWL4.0 method to optimize the protein structures for docking calculations. |
format | Online Article Text |
id | pubmed-9317601 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93176012022-07-27 Extensive Sampling of Molecular Dynamics Simulations to Identify Reliable Protein Structures for Optimized Virtual Screening Studies: The Case of the hTRPM8 Channel Gervasoni, Silvia Talarico, Carmine Manelfi, Candida Pedretti, Alessandro Vistoli, Giulio Beccari, Andrea R. Int J Mol Sci Article (1) Background: Virtual screening campaigns require target structures in which the pockets are properly arranged for binding. Without these, MD simulations can be used to relax the available target structures, optimizing the fine architecture of their binding sites. Among the generated frames, the best structures can be selected based on available experimental data. Without experimental templates, the MD trajectories can be filtered by energy-based criteria or sampled by systematic analyses. (2) Methods: A blind and methodical analysis was performed on the already reported MD run of the hTRPM8 tetrameric structures; a total of 50 frames underwent docking simulations by using a set of 1000 ligands including 20 known hTRPM8 modulators. Docking runs were performed by LiGen program and involved the frames as they are and after optimization by SCRWL4.0. For each frame, all four monomers were considered. Predictive models were developed by the EFO algorithm based on the sole primary LiGen scores. (3) Results: On average, the MD simulation progressively enhances the performance of the extracted frames, and the optimized structures perform better than the non-optimized frames (EF1% mean: 21.38 vs. 23.29). There is an overall correlation between performances and volumes of the explored pockets and the combination of the best performing frames allows to develop highly performing consensus models (EF1% = 49.83). (4) Conclusions: The systematic sampling of the entire MD run provides performances roughly comparable with those previously reached by using rationally selected frames. The proposed strategy appears to be helpful when the lack of experimental data does not allow an easy selection of the optimal structures for docking simulations. Overall, the reported docking results confirm the relevance of simulating all the monomers of an oligomer structure and emphasize the efficacy of the SCRWL4.0 method to optimize the protein structures for docking calculations. MDPI 2022-07-08 /pmc/articles/PMC9317601/ /pubmed/35886905 http://dx.doi.org/10.3390/ijms23147558 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Gervasoni, Silvia Talarico, Carmine Manelfi, Candida Pedretti, Alessandro Vistoli, Giulio Beccari, Andrea R. Extensive Sampling of Molecular Dynamics Simulations to Identify Reliable Protein Structures for Optimized Virtual Screening Studies: The Case of the hTRPM8 Channel |
title | Extensive Sampling of Molecular Dynamics Simulations to Identify Reliable Protein Structures for Optimized Virtual Screening Studies: The Case of the hTRPM8 Channel |
title_full | Extensive Sampling of Molecular Dynamics Simulations to Identify Reliable Protein Structures for Optimized Virtual Screening Studies: The Case of the hTRPM8 Channel |
title_fullStr | Extensive Sampling of Molecular Dynamics Simulations to Identify Reliable Protein Structures for Optimized Virtual Screening Studies: The Case of the hTRPM8 Channel |
title_full_unstemmed | Extensive Sampling of Molecular Dynamics Simulations to Identify Reliable Protein Structures for Optimized Virtual Screening Studies: The Case of the hTRPM8 Channel |
title_short | Extensive Sampling of Molecular Dynamics Simulations to Identify Reliable Protein Structures for Optimized Virtual Screening Studies: The Case of the hTRPM8 Channel |
title_sort | extensive sampling of molecular dynamics simulations to identify reliable protein structures for optimized virtual screening studies: the case of the htrpm8 channel |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9317601/ https://www.ncbi.nlm.nih.gov/pubmed/35886905 http://dx.doi.org/10.3390/ijms23147558 |
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