PROJECT #18402 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: 24,700

Core: GRO_A8

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Sunday, 16 January 2022 11:42:01

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PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Sunday, 16 January 2022 11:42:01

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 29,452 942,464 AMD
2 RYZEN 9 3950X 16-CORE 32 28,602 915,264 AMD
3 RYZEN 7 5800X 8-CORE 16 43,669 698,704 AMD
4 RYZEN 7 3800X 8-CORE 16 23,590 377,440 AMD
5 CORE I9-10850K CPU @ 3.60GHZ 20 15,835 316,700 Intel
6 11TH GEN CORE I9-11900K @ 3.50GHZ 16 18,308 292,928 Intel
7 CORE I9-10900X CPU @ 3.70GHZ 20 13,804 276,080 Intel
8 EPYC 7401P 24-CORE 48 4,678 224,544 AMD
9 RYZEN 9 3900XT 12-CORE 24 9,109 218,616 AMD
10 RYZEN 5 2600X SIX-CORE 12 17,789 213,468 AMD
11 XEON CPU E5-2680 V3 @ 2.50GHZ 24 8,408 201,792 Intel
12 XEON CPU E5-2690 V4 @ 2.60GHZ 28 6,866 192,248 Intel
13 CORE I7-8700 CPU @ 3.20GHZ 12 15,283 183,396 Intel
14 CORE I5-9600K CPU @ 3.70GHZ 6 25,120 150,720 Intel
15 RYZEN 5 3600 6-CORE 12 11,860 142,320 AMD
16 11TH GEN CORE I9-11900F @ 2.50GHZ 16 7,728 123,648 Intel
17 CORE I7-9700K CPU @ 3.60GHZ 8 14,507 116,056 Intel
18 11TH GEN CORE I5-11400 @ 2.60GHZ 12 9,213 110,556 Intel
19 RYZEN 5 1600 SIX-CORE 12 7,837 94,044 AMD
20 CORE I7-4770K CPU @ 3.50GHZ 8 9,277 74,216 Intel
21 CORE I7-4770HQ CPU @ 2.20GHZ 8 7,631 61,048 Intel
22 XEON W-10855M CPU @ 2.80GHZ 12 4,657 55,884 Intel
23 CORE I5-10210U CPU @ 1.60GHZ 7 5,996 41,972 Intel
24 CORE I7 CPU 975 @ 3.33GHZ 8 2,291 18,328 Intel