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

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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