Data Management for Molecule Simulation : A Throughput-Oriented Approach

NIH Pandemic-Era Grants

Pandemic Era Grants

2021

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Principal Investigator: Yicheng  Tu
Organization: UNIVERSITY OF SOUTH FLORIDA
Fiscal Year: 2021
Award: $287,698
Funding agency: National Institute of General Medical Sciences

Project Summary
We will design and develop a molecular simulation data management system, we call P2DMS, to analyze large dis-
tributed molecular dynamics (MD) simulation data. The salient features of the system include: (1) a push-based local
query engine design that handles data in a batch processing manner and processes many queries at the same time;
(2) optimized MD analytics tools using modern many-core hardware such as GPUs; and (3) efficient management and
access to distributed data over wide area networks, which is quite common for large scale MD simulations. This will
be done by building a data analysis layer on top of state-of-the-art distributed big data management systems. The out-
come of this project will not only improve the efficiency of MD data processing, but also enable new knowledge discov-
ery that is currently regarded difficult or infeasible. In particular, we will integrate the P2DMS program into existing MD
simulation packages, and validate the new design with important real-world biological and MD methodological prob-
lems. In particular, we will (1) model the structure-function relationships of how the spike protein of SARS-CoV-2 inter-
acts with the human angiotensin converting enzyme 2 (ACE2) receptor; and (2) enhance the performance of a recently
developed parameter optimization software for active control of MD simulations.

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