An efficient low storage and memory treatment of gridded interaction fields for simulations of macromolecular association
Computer simulations of molecular systems often make use of regular rectangular grids with equidistant spacing to store information on their molecular interaction fields, e.g., electrostatic potential. These grids provide an easy way to store the data as they do not require any particular specificat...
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| Main Authors: | , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
July 27, 2016
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| In: |
Journal of chemical theory and computation
Year: 2016, Volume: 12, Issue: 9, Pages: 4563-4577 |
| ISSN: | 1549-9626 |
| DOI: | 10.1021/acs.jctc.6b00350 |
| Online Access: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1021/acs.jctc.6b00350
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| Author Notes: | Musa Ozboyaci, Michael Martinez, and Rebecca C. Wade |
| Summary: | Computer simulations of molecular systems often make use of regular rectangular grids with equidistant spacing to store information on their molecular interaction fields, e.g., electrostatic potential. These grids provide an easy way to store the data as they do not require any particular specification of the structure of the data. However, such grids may easily become large, and the storage and memory demands may become so high that calculations become infeasible. To overcome this problem, we show here how the data structure DT-Grid can be adapted and applied to efficiently represent macromolecular interaction grids by exploiting the nonuniformity of information on the grid; at the same time, this data structure ensures fast random data access. We demonstrate use of the DT-Grid data structure for potential of mean force and Brownian dynamics simulations of protein-surface binding and macromolecular association with the SDA software. We further demonstrate that the DT-Grid structure enables systems of large size, such as a viral capsid, and high resolution grids to be handled that are beyond current computational feasibility. |
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| Item Description: | Gesehen am 19.10.2020 |
| Physical Description: | Online Resource |
| ISSN: | 1549-9626 |
| DOI: | 10.1021/acs.jctc.6b00350 |