PROJECT #18421 RESEARCH FOR CANCER
FOLDING PERFORMANCE PROFILE

PROJECT SUMMARY

Can molecular simulation be used for virtual affinity-maturation of de novo designed protein binders?  That’s the question this project aims to address.  The Bahl Lab at the Institute for Protein Innovation has had some amazing success using computational design to develop high-affinity mini-proteins that can inhibit protein targets by tightly binding to them.  In practice, the current approach requires the experimental screening of thousands of computational designs to discover a few tight binders, and similarly expensive experimental screens to optimize their binding (i.e. “affinity maturation”).  If we can make more accurate predictions of how sequence mutations affect binding affinity, we may be able to offload this expensive task to computers, boosting the efficiency of these efforts considerably.

In this project, we use relative free energy calculations to predict how single-point mutations of a computationally designed mini-protein alter the binding affinity to the periplasmic protease LapG, an important regulator of bacterial biofilm formation. These predictions will be compared to high-throughput experimental measurements of binding affinity provided by the Bahl lab.  An important end goal of this work is to develop new classes of inhibitors to make antibiotic therapies more successful.

PROJECT INFO

Manager(s): Prof. Vincent Voelz

Institution: Temple University

PROJECT WORK UNIT SUMMARY

Atoms: 80,500

Core: GRO_A8

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Friday, 03 December 2021 04:36:08

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PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Friday, 03 December 2021 04:36:08

Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make
1 RYZEN 9 5950X 16-CORE 32 33,666 1,077,312 AMD
2 RYZEN 9 3950X 16-CORE 32 18,414 589,248 AMD
3 CORE I9-7920X CPU @ 2.90GHZ 24 17,500 420,000 Intel
4 11TH GEN CORE I7-11700K @ 3.60GHZ 16 26,219 419,504 Intel
5 RYZEN 9 3900X 12-CORE 24 14,373 344,952 AMD
6 EPYC 7401P 24-CORE 48 6,450 309,600 AMD
7 11TH GEN CORE I9-11900K @ 3.50GHZ 16 18,000 288,000 Intel
8 CORE I5-10400 CPU @ 2.90GHZ 12 22,377 268,524 Intel
9 CORE I9-9900K CPU @ 3.60GHZ 16 15,886 254,176 Intel
10 CORE I9-9900 CPU @ 3.10GHZ 16 14,965 239,440 Intel
11 CORE I7-8700 CPU @ 3.20GHZ 12 19,829 237,948 Intel
12 RYZEN 7 5800X 8-CORE 16 12,910 206,560 AMD
13 RYZEN 5 3600 6-CORE 12 15,088 181,056 AMD
14 CORE I7-10700 CPU @ 2.90GHZ 16 9,542 152,672 Intel
15 RYZEN 7 2700X EIGHT-CORE 16 4,932 78,912 AMD