PROJECT #16935 RESEARCH FOR CANCER
FOLDING PERFORMANCE PROFILE
PROJECT SUMMARY
These projects aim to simulate the dynamics of a large number of designed mini-proteins (< 50 residues), to establish the ability of molecular simulations to accurately predict thermodynamic and kinetic effects of designed mutations. We aim to develop a library of experimental and simulation data so we can compare the performance of different techniques for computational protein design, such as adaptive sampling. Prediction and design of mini-protein structure and dynamics is highly relevant to developing new biotherapeutics for a wide range of human diseases.
Project System
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16935 chignolin
PROJECT INFO
Manager(s): Prof. Vincent Voelz
Institution: Temple University
PROJECT WORK UNIT SUMMARY
Atoms: 17,368
Core: GRO_A8
Status: Beta
PROJECT FOLDING PPD AVERAGES BY GPU
PPDDB data as of Monday, 18 January 2021 21:35:23
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Rank Project |
Model Name Folding@Home Identifier |
Make Brand |
GPU Model |
PPD Average |
Points WU Average |
WUs Day Average |
WU Time Average |
|---|
PROJECT FOLDING PPD AVERAGES BY CPU BETA
PPDDB data as of Monday, 18 January 2021 21:35:23
|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|---|---|---|---|---|
| 1 | RYZEN 9 3950X 16-CORE | 32 | 21,809 | 697,888 | AMD |
| 2 | RYZEN 9 5950X 16-CORE | 32 | 11,908 | 381,056 | AMD |
| 3 | CORE I5-5200U CPU @ 2.20GHZ | 4 | 4,346 | 17,384 | Intel |
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