3D animation as a tool for integrative modeling of dynamic molecular mechanisms

Abstract

As the scientific community accumulates diverse data describing how molecular mechanisms occur, creating and sharing visual models that integrate the richness of this information has become increasingly important to help us explore, refine, and communicate our hypotheses. Three-dimensional (3D) animation is a powerful tool to capture dynamic hypotheses that are otherwise difficult or impossible to visualize using traditional 2D illustration techniques. This perspective discusses the current and future roles that 3D animation can play in the research sphere.

Figure 1:. 3D animation as a tool for research.

(A) 3D animation can support the research process at multiple stages, highlighted in blue. (B) Animation was used to synthesize and communicate the ensemble of data collected by Kelly Lee’s group into a dynamic model of the mechanism of Chikungunya virus membrane fusion at the endosome. (C) In the same project, animation allowed for the exploration and discussion of alternative molecular trajectories connecting steps supported by structural data. (D) In a project carried in collaboration with Elizabeth Villa on the self-assembly and growth of jumbo phage nuclear shell, animation was instrumental to develop a dynamic molecular hypothesis from static structural data.

Figure 2:. Challenges and solutions to integrate dynamic data into animated models.

(A) Animated models have traditionally been based largely on structural data, thanks to both the amount of information available and their straightforward utilization for animation purposes. (B) Time-series of 3D coordinates obtained by simulation can be used to define the successive positions of molecules over time (left), as in this animation of the role of TRIM5α in HIV restriction (right). (C) The evolution of molecular distances can be informed by single-molecule FRET traces (left), as done in this animation of histone exchange by SWR1 chromatin remodeler, created in collaboration with Carl Wu and Taekjip Ha (right). (D) The relative pace of different steps of a process can be inferred from the relative distribution of particles of various conformational states in a cryo-EM dataset (left), as in this animation of protein G beta-5 folding by the TRiC/CCT chaperonin, created in collaboration with Peter Shen (right).

Figure 3:. Solutions to increase the transparency of animated models.

(A) Different strategies to provide greater transparency to animations through visual cues: cartoon-style rendering can be chosen to depict a process for which many aspects are still unclear, as for an animation of Microsporidia life cycle, created in collaboration with Gira Bhabha and Damian Ekiert (top); alternative hypotheses can be depicted in parallel (middle), and some of the data can be explicitly included (bottom), as for an animation of the jumbo phage life cycle, created in collaboration with Elizabeth Villa. (B) General organization of the user interface of a prototype tool for annotating 3D animations. Animators can add annotations, which describe the data that have informed different aspects of the model and appear on the left side of the screen, while the community can ask questions and leave comments, which appear on the right side. By clicking on one structure in the animation, the user highlights the associated annotations and comments. The distribution of comments, annotations and structures along the animation also appears at the bottom of the screen.

Figure 4:

A potential novel workflow for integrative and multiscale modeling of dynamic molecular mechanisms. Information derived from wet-lab experiments and physics-based simulations, gathered at various time and spatial scales, are converted into rules that are used for the design and simulation of agent-based models in animation software.