# Spatial and Sequential Topological Analysis of Molecular Dynamics Simulations of IgG1 Fc Domains

## TL;DR

This paper introduces a new method to analyze antibody structures using topological data analysis, helping distinguish between different molecular forms.

## Contribution

The novel GCCD matrix integrates sequence data with topological analysis to differentiate antibody conformations.

## Key findings

- GCCD matrices successfully differentiate glycosylated and aglycosylated antibody conformations.
- The method captures multiscale spatial and sequential features not detectable by traditional analysis.

## Abstract

Monoclonal
antibodies are utilized in a wide range of
biomedical
applications. The NIST monoclonal antibody is a resource for developing
analysis methods for monoclonal antibody based biopharmaceutical platforms.
Techniques from topological data analysis quantify structural features
such as loops and tunnels which are not easily measured by classical
data analysis methods. In this paper, we introduce the Gaussian CROCKER
column differences (GCCD) matrix, which augments standard topological
data analysis summaries with biological sequence information. We use
GCCD matrices to successfully differentiate between glycosylated and
aglycosylated conformations from molecular dynamics simulations of
the NIST monoclonal antibody Fc domain. We are optimistic that other
researchers will be able to utilize GCCD matrices to quantify multiscale
spatial and sequential features.