# Multiscale Visual Drilldown for the Analysis of Large Ensembles of Multi-Body Protein Complexes

## TL;DR

This paper introduces a multiscale visual drilldown method for systematically exploring large ensembles of multi-body protein complex configurations, aiding biochemists in identifying plausible structures efficiently.

## Contribution

It presents a novel interactive visualization approach that leverages hierarchical data structures and filtering operations, developed in collaboration with proteomic experts.

## Key findings

- Effective exploration of large protein configuration ensembles demonstrated in case studies
- Enhanced understanding of contact interfaces and amino acid interactions
- Facilitated identification of biologically relevant configurations

## Abstract

When studying multi-body protein complexes, biochemists use computational tools that can suggest hundreds or thousands of their possible spatial configurations. However, it is not feasible to experimentally verify more than only a very small subset of them. In this paper, we propose a novel multiscale visual drilldown approach that was designed in tight collaboration with proteomic experts, enabling a systematic exploration of the configuration space. Our approach takes advantage of the hierarchical structure of the data -- from the whole ensemble of protein complex configurations to the individual configurations, their contact interfaces, and the interacting amino acids. Our new solution is based on interactively linked 2D and 3D views for individual hierarchy levels and at each level, we offer a set of selection and filtering operations enabling the user to narrow down the number of configurations that need to be manually scrutinized. Furthermore, we offer a dedicated filter interface, which provides the users with an overview of the applied filtering operations and enables them to examine their impact on the explored ensemble. This way, we maintain the history of the exploration process and thus enable the user to return to an earlier point of the exploration. We demonstrate the effectiveness of our approach on two case studies conducted by collaborating proteomic experts.