PROJECT #18416 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 9 5950X 16-CORE 32 22,155 708,960 AMD
2 RYZEN 7 5800X 8-CORE 16 41,604 665,664 AMD
3 RYZEN 7 5700G 16 25,013 400,208 AMD
4 11TH GEN CORE I7-11700K @ 3.60GHZ 16 21,581 345,296 Intel
5 RYZEN 9 3900X 12-CORE 24 14,328 343,872 AMD
6 CORE I9-7920X CPU @ 2.90GHZ 24 12,665 303,960 Intel
7 RYZEN 9 3950X 16-CORE 32 8,783 281,056 AMD
8 RYZEN 7 3800X 8-CORE 16 17,317 277,072 AMD
9 XEON CPU E5-2680 V3 @ 2.50GHZ 24 11,149 267,576 Intel
10 11TH GEN CORE I9-11900K @ 3.50GHZ 16 16,247 259,952 Intel
11 CORE I9-10850K CPU @ 3.60GHZ 20 12,475 249,500 Intel
12 RYZEN 5 5600X 6-CORE 12 20,010 240,120 AMD
13 RYZEN THREADRIPPER 2950X 16-CORE 32 7,333 234,656 AMD
14 EPYC 7401P 24-CORE 48 4,634 222,432 AMD
15 CORE I7-8700 CPU @ 3.20GHZ 12 16,919 203,028 Intel
16 CORE I9-9900K CPU @ 3.60GHZ 16 10,457 167,312 Intel
17 RYZEN 5 2600X SIX-CORE 12 13,175 158,100 AMD
18 RYZEN 5 3600 6-CORE 12 12,025 144,300 AMD
19 CORE I9-10900X CPU @ 3.70GHZ 20 7,161 143,220 Intel
20 11TH GEN CORE I9-11900F @ 2.50GHZ 16 6,522 104,352 Intel
21 RYZEN 5 2600 SIX-CORE 12 8,665 103,980 AMD
22 EPYC 7251 8-CORE 16 4,048 64,768 AMD
23 CORE I7-3770 CPU @ 3.40GHZ 8 6,021 48,168 Intel
24 CORE I5-8265U CPU @ 1.60GHZ 8 4,523 36,184 Intel
25 CORE I7 CPU 975 @ 3.33GHZ 8 2,304 18,432 Intel