Divide-and-conquer approach to study protein tunnels in long molecular dynamics simulations
Nowadays, molecular dynamics (MD) simulations of proteins with hundreds of thousands of snapshots are commonly produced using modern GPUs. However, due to the abundance of data, analyzing transport tunnels present in the internal voids of these molecules, in all generated snapshots, has become chall...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-01-01
|
| Series: | MethodsX |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2215016122003429 |
| _version_ | 1797796447944441856 |
|---|---|
| author | Carlos Sequeiros-Borja Bartlomiej Surpeta Igor Marchlewski Jan Brezovsky |
| author_facet | Carlos Sequeiros-Borja Bartlomiej Surpeta Igor Marchlewski Jan Brezovsky |
| author_sort | Carlos Sequeiros-Borja |
| collection | DOAJ |
| description | Nowadays, molecular dynamics (MD) simulations of proteins with hundreds of thousands of snapshots are commonly produced using modern GPUs. However, due to the abundance of data, analyzing transport tunnels present in the internal voids of these molecules, in all generated snapshots, has become challenging. Here, we propose to combine the usage of CAVER3, the most popular tool for tunnel calculation, and the TransportTools Python3 library into a divide-and-conquer approach to speed up tunnel calculation and reduce the hardware resources required to analyze long MD simulations in detail. By slicing an MD trajectory into smaller pieces and performing a tunnel analysis on these pieces by CAVER3, the runtime and resources are considerably reduced. Next, the TransportTools library merges the smaller pieces and gives an overall view of the tunnel network for the complete trajectory without quality loss. |
| first_indexed | 2024-03-13T03:33:13Z |
| format | Article |
| id | doaj.art-3bfa4bbe69084400adb086a05cc32816 |
| institution | Directory Open Access Journal |
| issn | 2215-0161 |
| language | English |
| last_indexed | 2024-03-13T03:33:13Z |
| publishDate | 2023-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | MethodsX |
| spelling | doaj.art-3bfa4bbe69084400adb086a05cc328162023-06-24T05:16:50ZengElsevierMethodsX2215-01612023-01-0110101968Divide-and-conquer approach to study protein tunnels in long molecular dynamics simulationsCarlos Sequeiros-Borja0Bartlomiej Surpeta1Igor Marchlewski2Jan Brezovsky3International Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland; Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Poznan, PolandInternational Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland; Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Poznan, PolandInternational Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland; Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Poznan, PolandInternational Institute of Molecular and Cell Biology in Warsaw, Warsaw, Poland; Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Poznan, Poland; Corresponding authors: Dr. Jan Brezovsky, Adam Mickiewicz University, PolandNowadays, molecular dynamics (MD) simulations of proteins with hundreds of thousands of snapshots are commonly produced using modern GPUs. However, due to the abundance of data, analyzing transport tunnels present in the internal voids of these molecules, in all generated snapshots, has become challenging. Here, we propose to combine the usage of CAVER3, the most popular tool for tunnel calculation, and the TransportTools Python3 library into a divide-and-conquer approach to speed up tunnel calculation and reduce the hardware resources required to analyze long MD simulations in detail. By slicing an MD trajectory into smaller pieces and performing a tunnel analysis on these pieces by CAVER3, the runtime and resources are considerably reduced. Next, the TransportTools library merges the smaller pieces and gives an overall view of the tunnel network for the complete trajectory without quality loss.http://www.sciencedirect.com/science/article/pii/S2215016122003429Divide-and-conquer |
| spellingShingle | Carlos Sequeiros-Borja Bartlomiej Surpeta Igor Marchlewski Jan Brezovsky Divide-and-conquer approach to study protein tunnels in long molecular dynamics simulations MethodsX Divide-and-conquer |
| title | Divide-and-conquer approach to study protein tunnels in long molecular dynamics simulations |
| title_full | Divide-and-conquer approach to study protein tunnels in long molecular dynamics simulations |
| title_fullStr | Divide-and-conquer approach to study protein tunnels in long molecular dynamics simulations |
| title_full_unstemmed | Divide-and-conquer approach to study protein tunnels in long molecular dynamics simulations |
| title_short | Divide-and-conquer approach to study protein tunnels in long molecular dynamics simulations |
| title_sort | divide and conquer approach to study protein tunnels in long molecular dynamics simulations |
| topic | Divide-and-conquer |
| url | http://www.sciencedirect.com/science/article/pii/S2215016122003429 |
| work_keys_str_mv | AT carlossequeirosborja divideandconquerapproachtostudyproteintunnelsinlongmoleculardynamicssimulations AT bartlomiejsurpeta divideandconquerapproachtostudyproteintunnelsinlongmoleculardynamicssimulations AT igormarchlewski divideandconquerapproachtostudyproteintunnelsinlongmoleculardynamicssimulations AT janbrezovsky divideandconquerapproachtostudyproteintunnelsinlongmoleculardynamicssimulations |