Molecular Modeling
TR&D1: Molecular modeling and simulations: Bridging molecular and cellular scales
TR&D1's overarching goal is to develop, implement, integrate and apply computational technology toward meeting the emerging needs for structure-based modeling of mesoscopic- and/or omics-scale dynamics, and to establish a platform that synergistically interfaces with the technologies developed in the other TR&Ds.
Vision
There is a growing need to understand molecular events at the mesoscopic time scale - microseconds-to-seconds, for systems containing 10s-to-100s of proteins/subunits, which current methods usually fail to represent with adequate structural and spatial complexity. We also have new challenges with 'omics'-scale data, which could be best tackled by advanced algorithms and high performance computing resources. Significant progress was made during the past funding period in the TR&D1 project, evidenced by 38 publications by TR&D1 members that acknowledged the P41 support. We developed and disseminated novel computational technology, and helped accelerate biomedical research driven by two DBPs. Many tools that we developed in the past decade, rooted in fundamental concepts of statistical mechanics, spectral graph theoretical methods and machine learning, can now be substantively advanced to meet emerging needs and challenges.

Time scales sampled by molecular (MD) and subcellular (MCell) simulations. The intermediate regime, mesoscale, is poorly sampled. Elastic network models aim at filling the gap between those scales.
Background and Motivation
The last decade has seen the creation of a remarkably inventive array of approaches for 4D modeling of biomolecular systems, using coarse-grained models and enhanced-sampling methods, as well as spatiotemporally realistic approaches at cellular scale. However, “mesoscale” systems such as large multi-protein complexes and subcellular structures, and “omics-scale” systems like chromatin have received significantly less attention. There is a growing need to develop computational technology for structure-based mesoscopic- and spatially resolved omics-scale modeling. Several methodologies already developed by TR&D1 investigators show great promise for meeting this need. These include the methods and tools based on elastic network models (ENMs) and implemented in the ProDy Application Programming Interface (API) developed for modeling supramolecular systems dynamics, and the Armatus software developed for identifying topological associated domains in chromosomes. Our research and development activities are driven by four Driving Biomedical Projects that focus on the complex interactions controlling neurotransmission and neurosignaling events (DBP1-3), and on constructing a spatial dynamic map of transcription and chromatin structure (DBP6). We are working together with all three other TR&Ds to meet the multiscale challenges of the investigated complex systems and processes.
Specific aims
- Advancing and implementing the methodology for treating the structure, dynamics and interactions of multimeric proteins and multiprotein assemblies
We extend the capabilities of our widely used ProDy API, to generate elastic network models (ENMs) of various levels of granularity for biomolecular complexes/assemblies in their subcellular environment, interacting with lipids, substrates, and ions. We take advantage of existing databases of structures and interactions, and the methods we developed during the past term such as coMD, weighted-ensemble(WE)-based HPC methods, in addition to our two-decade long experience on the development and use of ENMs for biomolecular systems dynamics.
- Extending the computing capabilities of TR&D1 to model chromosomal structure, dynamics and function
This aim is driven by DBP6.
We extend the capabilities of ProDy, and its underlying GNM theory and methods, to model the chromosomal structure and dynamics from pairwise contacts measured using chromosome conformation capture measurements (3C), and benchmark our model against data at the forefront of genomic sciences. We extend our existing software to add the capability to find functional spatial arrangements from imaging of pairs of genomic loci generated in collaboration with TR&D4. In particular, we develop techniques to identify co-localized transcription and bursty transcription events. We integrate the tools developed in the two subaims to provide a user-friendly platform for multiscale analysis of genome-scale structure/contact data.
- Further development of TR&D1 technology to ensure efficient integration of all software within TR&D1 and interoperability with those developed at TR&D2-4 and other resources
The goal is to promote the efficient usage of our tools by the broader community and to provide a platform that bridges between molecular and cellular simulations. We integrate and automate of ProDy modules methods and protocols, developed in TR&D1 aims 1 and 2, and implement the interfaces to enable interoperability with the software developed by TR&D1 members including Armatus59 for identifying topologically associated domains on the chromosomes. We ensure the interoperability of TR&D1 tools with, the major software MCell, BioNetGen and CellOrganizer, being developed in the respective TR&Ds 2 - 4 toward building a computational platform for integrated structural cell biology.