Characterizing the 3D structure and dynamics of chromosomes and proteins in a common contact matrix framework

Abstract

Abstract:Any conformational ensemble of biopolymers, whether they are proteins or chromosomes, can be described using contact matrices derived from experimental or computational studies. One powerful approach to extract meaningful information from these contact matrices is to perform principal component analysis (PCA) on the covariance matrix of the contact data. Indeed, PCA on Hi-C chromosome contact matrices has revealed the spatial segregation of active and inactive chromatin. Separately, PCA on contact matrices from snapshots of protein conformations has characterized correlated fluctuations of protein domains. However, despite the similarities of these data and analyses, there has been little synergy between the PCA approaches and the comparison of resulting biological insights obtained for protein and chromosome structures. We note that, to date, different styles of analyses were applied exclusively to each biomolecule type: explicit contact correlation analysis (E-PCA) for proteins and implicit contact correlation (I-PCA) for chromosomes. In this work, we compare the results of applying both methods to both classes of biopolymers. While I-PCA reveals only average features of 3D chromosome structure, we find that applying E-PCA to an ensemble of chromosome structures from microscopy data reveals the dominant motion (concerted fluctuation) of the chromosome. Applying E-PCA to Hi-C data across the human blood cell lineage isolates the aspects of chromosome structure that most strongly differentiate cell types. Conversely, when we apply I-PCA to simulation snapshots of two protein complexes, the major component reports the consensus features of the structure, while the previously applied E-PCA characterizes correlated deviations from the mean structure.

Disorder Mediated Oligomerization of DISC1 Proteins Revealed by Coarse-Grained Molecular Dynamics Simulations

“…41,42 Contact-based measures, on the other hand, have the advantage of revealing a more detailed picture of disorder throughout the sequence as well as revealing dynamic and thermodynamic driving forces that shape energy landscapes of disordered proteins. 31,37,38 The distribution of radius of gyration clearly shows the presence of at least three major populations, with an average radius of gyrations of 3.5, 4.6, and 8.2 Å (Figure 2A). Analyzing frequency of contact formation in DISC1 ensemble we found a specific pattern of contacts within the N-and C-terminal domains while the central domain shows largely smeared contacts with the N-terminal domain (Figure 2B).…”

“…Examining the first few principal components reveals the interfacial hot spots which trigger most variable contact changes and are likely driving forces for slowest conformational transitions. 31,37,38…”