PROJECT #18417 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: 35,650

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 7 5800X 8-CORE 16 43,226 691,616 AMD
2 RYZEN 9 5950X 16-CORE 32 12,020 384,640 AMD
3 RYZEN 7 5700G 16 20,783 332,528 AMD
4 RYZEN 9 3950X 16-CORE 32 10,251 328,032 AMD
5 RYZEN 7 3800X 8-CORE 16 18,388 294,208 AMD
6 11TH GEN CORE I9-11900K @ 3.50GHZ 16 16,835 269,360 Intel
7 RYZEN 9 3900X 12-CORE 24 10,512 252,288 AMD
8 CORE I9-9900K CPU @ 3.60GHZ 16 13,482 215,712 Intel
9 RYZEN THREADRIPPER 2950X 16-CORE 32 6,656 212,992 AMD
10 CORE I7-8700 CPU @ 3.20GHZ 12 16,753 201,036 Intel
11 RYZEN 5 2600X SIX-CORE 12 15,266 183,192 AMD
12 XEON CPU E5-2690 V4 @ 2.60GHZ 28 6,474 181,272 Intel
13 CORE I9-9900 CPU @ 3.10GHZ 16 10,154 162,464 Intel
14 RYZEN 5 3600 6-CORE 12 11,468 137,616 AMD
15 11TH GEN CORE I5-11400 @ 2.60GHZ 12 9,035 108,420 Intel
16 RYZEN 5 2600 SIX-CORE 12 8,037 96,444 AMD
17 CORE I7-10750H CPU @ 2.60GHZ 12 6,996 83,952 Intel
18 RYZEN 5 1600 SIX-CORE 12 6,489 77,868 AMD
19 11TH GEN CORE I7-11370H @ 3.30GHZ 8 9,313 74,504 Intel
20 CORE I7-10510U CPU @ 1.80GHZ 8 6,947 55,576 Intel
21 CORE I7-3770 CPU @ 3.40GHZ 8 6,074 48,592 Intel