SDA 7: a modular and parallel implementation of the simulation of diffusional association software
The simulation of diffusional association (SDA) Brownian dynamics software package has been widely used in the study of biomacromolecular association. Initially developed to calculate bimolecular protein-protein association rate constants, it has since been extended to study electron transfer rates,...
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| Main Authors: | , , , , , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
29 June 2015
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| In: |
Journal of computational chemistry
Year: 2015, Volume: 36, Issue: 21, Pages: 1631-1645 |
| ISSN: | 1096-987X |
| DOI: | 10.1002/jcc.23971 |
| Online Access: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1002/jcc.23971 Verlag, lizenzpflichtig, Volltext: https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.23971 
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| Author Notes: | Michael Martinez, Neil J. Bruce, Julia Romanowska, Daria B. Kokh, Musa Ozboyaci, Xiaofeng Yu, Mehmet Ali Öztürk, Stefan Richter, and Rebecca C. Wade |
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| 520 | |a The simulation of diffusional association (SDA) Brownian dynamics software package has been widely used in the study of biomacromolecular association. Initially developed to calculate bimolecular protein-protein association rate constants, it has since been extended to study electron transfer rates, to predict the structures of biomacromolecular complexes, to investigate the adsorption of proteins to inorganic surfaces, and to simulate the dynamics of large systems containing many biomacromolecular solutes, allowing the study of concentration-dependent effects. These extensions have led to a number of divergent versions of the software. In this article, we report the development of the latest version of the software (SDA 7). This release was developed to consolidate the existing codes into a single framework, while improving the parallelization of the code to better exploit modern multicore shared memory computer architectures. It is built using a modular object-oriented programming scheme, to allow for easy maintenance and extension of the software, and includes new features, such as adding flexible solute representations. We discuss a number of application examples, which describe some of the methods available in the release, and provide benchmarking data to demonstrate the parallel performance. © 2015 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. | ||
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| 650 | 4 | |a parallelization | |
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| 650 | 4 | |a protein flexibility | |
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