Probing and Perturbing Transcriptional Condensates with Multiscale Modeling and Deep Learning

PROJECT SUMMARY Biomolecular condensates are compartments that form within cells through the self-assembly of proteins, RNAs, etc. These condensates play a critical role in the functioning of cells as they help to concentrate biomolecules and facilitate biochemical reactions. Recent studies have shown that they are also essential for transcriptional regulation. However, there are still many unanswered questions about how these condensates form, interact with each other, and how they organize chromatin and regulate transcription. One of the challenges in addressing these questions is the lack of suitable experimental techniques for quantitatively studying the spatiotemporal complexity and heterogeneity of transcriptional condensates. We propose to characterize transcriptional condensates in the context of chromatin using in silico approaches. (i) By introducing many-body potentials represented using graph neural networks and novel parameterization schemes, we will introduce the next generation of residue-level coarse-grained (CG) models for proteins, RNAs, and DNAs. These models will outperform existing ones that often lack the accuracy needed for de novo predictions, enabling their application from generating testable hypotheses. (ii) Using CG models that balance computational efficiency and chemical accuracy, we will reconstruct in vivo chromatin organization at near-atomistic resolution with a multiscale approach. We will evaluate the stability of these near-atomistic models and the contribution of physicochemical interactions in stabilizing chromatin. In addition, we will quantify the role of transcriptional condensates in chromatin looping and accelerating transcription factor target search using reconstructed in vivo chromatin structures. (iii) We will also decode the molecular grammar of protein-protein interactions that dictate condensate stability using evolutionary sequence analysis and physical simulations. We will use this information to design small molecules for condensate modulation. Overall, the goal of our research is to provide critical evaluations of hypotheses on the role of transient, collective phenomena arising from weak, multivalent interactions in essential cellular processes and suggest novel therapeutic strategies for their modulation.