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.


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

  1. 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.


  2. 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.

  3. 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.

Molecular Modeling Research Highlights

Monoamine transporters: structure, intrinsic dynamics and allosteric regulation/strong><

T&RD1 investigators Mary Cheng and Ivet Bahar published an invited review article in Nature Structural & Molecular Biology, addressing recent progress in the elucidation of the structural dynamics of MATs and their conformational landscape and transitions, as well as allosteric regulation mechanisms. (Read more)

Trimerization of dopamine transporter triggered by AIM-100 binding

The Bahar (TR&D1) and Sorkin (DBP3) labs explored the trimerization of dopamine transporter (DAT) triggered by a furopyrimidine, AIM-100, using a combination of computational and biochemical methods, and single-molecule live-cell imaging assays. (Read more)

PINK1 Interacts with VCP/p97 and Activates PKA to Promote NSFL1C/p47 Phosphorylation and Dendritic Arborization in Neurons

Our findings highlight an important mechanism by which proteins genetically implicated in Parkinson’s disease (PD; PINK1) and frontotemporal dementia (FTD; VCP) interact to support the health and maintenance of neuronal arbors.(Read more)

New tool to predict pathogenicity of missense variants based on structural dynamics: RHAPSODY

We demonstrated that the analysis of a protein’s intrinsic dynamics can be successfully used to improve the prediction of the effect of point mutations on a protein functionality. This method employs ANM/GNM tools (Read more)


Multi-scale Hybrid Methodology

The hybrid methodology, coMD, that we have recently developed [1] has been recently extended to construct the energy landscape near the functional states of LeuT (Fig 1) [2]. This is the first energy landscape constructed for this NSS family member.  Read more


Insights into the cooperative dynamics of AMPAR

Comparative analysis of AMPAR and NMDAR dynamics reveals striking similiarities, opening the way to designing new modulators of allosteric interactions. Read more

New Release of the iGNM Database

We have updated our iGNM database. The updated iGNM 2.0 covers more than 95% of the structures in the Protein Data Bank. Read more

langmead2 200Sparse Graphical Models of Protein:Protein Interactions

DgSpi is a new method for learning and using graphical models that explicitly represent the amino acid basis for interaction specificity and extend earlier classification-oriented approaches to predict ΔG of binding.  Read more


Improved Sampling of Cell-Scale Models using the WE Strategy

The WE strategy for orchestrating a large set of parallel simulations has now been extended to spatially resolved cell-scale systems. The WESTPA implementation of WE has been used to control MCell simulations, including models built using a BioNetGen-CellOrganizer pipeline for situating complex biochemistry within spatially realistic cell models. Read more

Molecular Mechanism of Dopamine Transport by hDAT

Dopamine transporters (DATs) control neurotransmitter dopamine (DA) homeostasis by reuptake of excess DA, assisted by sodium and chloride ions. The recent resolution of DAT structure (dDAT) from Drosophila permits us for the first time to directly view the sequence of events involved in DA reuptake in human DAT (hDAT). Read more


Picture1 180Advancing Parallel Bio-simulations

A new non-Markovian analysis can eliminate bias in estimates of long-timescale behavior, such as the mean first-passage time for the dissociation of methane molecules in explicit solvent. Read more


stochasticModelingBing170Stochastic Modeling

Controlling ionizing radiation (IR)-induced cell death mitigates radiation damage. Examining tumor suppressor protein p53 network dynamics in response to IR damage found that the strength of p53 transcriptional activity and its coupling (or timing with respect) to mitochondrial pore opening are major determinants of cell fate.  Read more

GltPhGltPh Intracellular Gating

Our recent study highlights the role of the helical hairpin HP2 as an intracellular gate, in addition to its role as an extracellular gate.  Read more.

Figure1 SubstrateBinding LeuT 400 Gating events in LeuT

Unraveling the molecular mechanism of function of NSS family members has been a challenge due to the involvement of both local (EC or IC gate opening/closure) and global (between outward- and inward-facing) changes in structure. Read more

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