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Review
. 2019 Jun 6;9(3):20180075.
doi: 10.1098/rsfs.2018.0075. Epub 2019 Apr 19.

SWINGER: a clustering algorithm for concurrent coupling of atomistic and supramolecular liquids

Affiliations
Review

SWINGER: a clustering algorithm for concurrent coupling of atomistic and supramolecular liquids

Julija Zavadlav et al. Interface Focus. .

Abstract

In this contribution, we review recent developments and applications of a dynamic clustering algorithm SWINGER tailored for the multiscale molecular simulations of biomolecular systems. The algorithm on-the-fly redistributes solvent molecules among supramolecular clusters. In particular, we focus on its applications in combination with the adaptive resolution scheme, which concurrently couples atomistic and coarse-grained molecular representations. We showcase the versatility of our multiscale approach on a few applications to biomolecular systems coupling atomistic and supramolecular water models such as the well-established MARTINI and dissipative particle dynamics models and provide an outlook for future work.

Keywords: adaptive resolution; molecular dynamics; supramolecular coupling.

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Conflict of interest statement

We declare we have no competing interests.

Figures

Figure 1.
Figure 1.
Schematic of the multiscale simulation set-up for the simulation of a protein in water where the resolution of the solvent is gradually changed from atomistic to SCG. For supramolecular mappings, the clusters need to be assembled, disassembled and reassembled on-the-fly to accommodate the molecular diffusion from the atomistic to SCG domains and vice versa. To this end, we developed the SWINGER algorithm that acts in the thin layer between the atomistic and hybrid domains. (Online version in colour.)
Figure 2.
Figure 2.
Original (a) and ‘reverse’ (b) implementation of AdResS multiscale simulation where an atomistic (AT) model is coupled to an SCG model. The coupling is shown for the special case where the resolution is changed only along one dimension. Only half of the simulation domain is displayed as the system is symmetric. In the original AdResS version, the weighting function w take limiting values of w = 1 and 0 in the AT and SCG domains, respectively. In the ‘reverse’ case, the definition of w is inverted, which permits the exclusion of the intermediate atomistic with bundles (ATwB) region. In both cases, the SWINGER algorithm is applied in a very small region at the edge of the AT domain. Different AdResS domains are shown disjoint only for clarity reasons. (Online version in colour.)
Figure 3.
Figure 3.
Flowchart of the SWINGER algorithm. (Online version in colour.)
Figure 4.
Figure 4.
Average bundling energy of a bundle UB (a) and tetrahedral order parameter Q4 and Q4 (b) with standard deviations along the direction of the resolution change (r is the distance from R0 in direction of the x-coordinate). The AdResS profile is computed separately for Γ (equation (2.10)) and Γ * functions, where Γ * = 1 for RB < ‖RR0‖ < RSCG. The value of Q4 = 1 corresponds to a perfect tetrahedral arrangement, whereas Q4 = 0 describes an ideal gas. The results are plotted for the AdResS simulation and reference all-atom SPC and bundled-SPC 1 [64] water models. Resolution region boundaries are denoted with the vertical dashed lines. Adapted from [70]. (Online version in colour.)
Figure 5.
Figure 5.
Subplot (a) shows the NDP (with standard deviation denoted by the error bars) around the CoM of the protein for water oxygen atoms and MARTINI SCG beads and the thermodynamic (TD) force that acts on CoM of supramolecular bundles in the HY region. In subplot (b), we show the radius of gyration Rg as a function of the simulation time and root-mean-square fluctuations RMSF of the backbone atoms with respect to the crystal structure. The configuration snapshots were prior to RMSD calculation superimposed on the initial crystal structure (1L2Y.pdb). The error bars of RMSF denote the standard deviation computed by block averaging. The multiscale results are compared to all-atom SPC, all-atom bundelled SPC 1 and 2 solvations. Adapted with permission from [71]. Copyright 2018 American Chemical Society. (Online version in colour.)
Figure 6.
Figure 6.
Distinct part of the Van Hove function Gd(r, t)/ρ (a) at times 0.0 and 0.5 ps for the oxygen–oxygen (OW-OW), oxygen–hydrogen (OW-HW), hydrogen–hydrogen (HW-HW), and DPD-DPD case. Self-part of the Van Hove function 4πr2 Gs(r, t) (b) for water oxygen (OW) atoms and DPD particles at times 0.5, 1.0, 2.0 and 5.0 ps. Adapted with permission from ref. [72]. Copyright 2017 American Institute of Physics (AIP) Publishing. (Online version in colour.)

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