# TRD-VMD

> **NIH NIH P41** · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · 2021 · $439,230

## Abstract

Project Summary / Abstract
When combined with advanced software, the computer becomes a powerful instrument for the study of biomolecular complexes and living cells, providing researchers with graphical views and quantitative information at a level of
fidelity and accuracy limited only by the quality of available structural information. State-of-the-art biomolecular
and cellular simulations are demanding not only in terms of computations required for simulation, but also with
respect to the effort and computations required in building accurate models, preparing simulations, and analyzing
results. The size of structurally resolved biomolecular complexes continues to grow, threatening to overwhelm
existing software tools unless they are adapted to further exploit parallel computing technologies for key modeling,
analysis, and visualization tools. Simulations must incorporate information from multiple experimental imaging
modalities (e.g. X-ray crystallography, cryo-EM, cryo-ET, NMR) to enhance simulation accuracy and properly
reproduce conditions present in vivo. It is therefore critical that next-generation tools for model building, simulation preparation, analysis, and visualization support multi-modal simulation approaches, and interoperate with a
wide variety of research tools. The complexity involved in managing numerous and diverse simulation inputs and
methods poses a significant challenge for reproducibility, requiring research tools to better support the automation,
recording, and replay of complex simulation workflows both by the investigator using the software and by others.
The activities described in this TRD are aligned with these overarching themes, aiming to provide the research
community with new tools and software features that address challenges that arise in modeling, simulating, and
analyzing ever larger macromolecular and cellular complexes, incorporation of multi-modal structure data, and
interoperation with a broad range of other research software. The computational and visualization challenges
involved in these aims will be addressed through algorithmic innovations that leverage fine-grained parallel computing approaches on multi-core CPUs and GPUs, and larger scale parallel computing on clouds, clusters, and
supercomputers. The data size challenges that are expected to become more pervasive in the coming years will
be met through the use of advanced non-volatile memory systems, new file formats and compressed data structures with increasing emphasis on parallel filesystems. The use of high-quality video streaming will permit one to
perform modeling calculations at computer centers or advanced laboratories and avoid routine transfer of large
data to allow researchers to carry out their work anywhere on video-stream linked devices like laptops and will
facilitate remote collaboration among investigators.

## Key facts

- **NIH application ID:** 10163205
- **Project number:** 5P41GM104601-32
- **Recipient organization:** UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
- **Principal Investigator:** Klaus Schulten
- **Activity code:** P41 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $439,230
- **Award type:** 5
- **Project period:** 1997-08-01 → 2022-09-27

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10163205

## Citation

> US National Institutes of Health, RePORTER application 10163205, TRD-VMD (5P41GM104601-32). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10163205. Licensed CC0.

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