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Antibodies 2018, 7(3), 21; https://doi.org/10.3390/antib7030021

Thinking outside the Laboratory: Analyses of Antibody Structure and Dynamics within Different Solvent Environments in Molecular Dynamics (MD) Simulations

1
Department of Chemical and Process Engineering, University of Strathclyde, Glasgow G1 1XJ, UK
2
Department of Physics, University of Strathclyde, Glasgow G4 0NG, UK
*
Author to whom correspondence should be addressed.
Received: 2 May 2018 / Revised: 11 June 2018 / Accepted: 20 June 2018 / Published: 24 June 2018
(This article belongs to the Collection Computational Antibody and Antigen Design)
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Abstract

Monoclonal antibodies (mAbs) have revolutionized the biomedical field, directly influencing therapeutics and diagnostics in the biopharmaceutical industry, while continuing advances in computational efficiency have enabled molecular dynamics (MD) simulations to provide atomistic insight into the structure and function of mAbs. Despite the success of MD tools, further optimizations are still required to enhance the computational efficiency of complex mAb simulations. This issue can be tackled by changing the way the solvent system is modelled to reduce the number of atoms to be tracked but must be done without compromising the accuracy of the simulations. In this work, the structure of the IgG2a antibody was analyzed in three solvent systems: explicit water and ions, implicit water and ions, and implicit water and explicit ions. Root-mean-square distance (RMSD), root-mean-square fluctuations (RMSF), and interchain angles were used to quantify structural changes. The explicit system provides the most atomistic detail but is ~6 times slower in its exploration of configurational space and required ~4 times more computational time on our supercomputer than the implicit simulations. Overall, the behavior of the implicit and explicit simulations is quantifiably similar, with the inclusion of explicit ions in the implicit simulation stabilizing the antibody to reproduce well the statistical fluctuations of the fully explicit system. Therefore, this approach holds promise to maximize the use of computational resources to explore antibody behavior. View Full-Text
Keywords: implicit solvent; explicit solvent; root-mean-square distance (RMSD); root-mean-square fluctuations (RMSF); antibody; molecular dynamics (MD) implicit solvent; explicit solvent; root-mean-square distance (RMSD); root-mean-square fluctuations (RMSF); antibody; molecular dynamics (MD)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Al Qaraghuli, M.M.; Kubiak-Ossowska, K.; Mulheran, P.A. Thinking outside the Laboratory: Analyses of Antibody Structure and Dynamics within Different Solvent Environments in Molecular Dynamics (MD) Simulations. Antibodies 2018, 7, 21.

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