PROJECT #18422 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.

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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 Monday, 23 May 2022 03:34:39

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PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Monday, 23 May 2022 03:34:39

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 26,805 857,760 AMD
2 12TH GEN CORE I7-12700K 20 38,317 766,340 Intel
3 RYZEN 9 5900X 12-CORE 24 20,595 494,280 AMD
4 RYZEN 7 5800X 8-CORE 16 28,481 455,696 AMD
5 RYZEN 9 3950X 16-CORE 32 13,682 437,824 AMD
6 RYZEN 9 3900 12-CORE 24 17,924 430,176 AMD
7 CORE I9-7920X CPU @ 2.90GHZ 24 17,442 418,608 Intel
8 12TH GEN CORE I7-12700 20 20,245 404,900 Intel
9 RYZEN 9 3900XT 12-CORE 24 15,344 368,256 AMD
10 XEON CPU E5-2690 V4 @ 2.60GHZ 28 12,063 337,764 Intel
11 RYZEN 9 3900X 12-CORE 24 13,699 328,776 AMD
12 RYZEN 5 5600X 6-CORE 12 25,606 307,272 AMD
13 RYZEN 7 3800X 8-CORE 16 18,692 299,072 AMD
14 XEON CPU E5-2680 V3 @ 2.50GHZ 24 10,279 246,696 Intel
15 CORE I7-8700 CPU @ 3.20GHZ 12 19,014 228,168 Intel
16 CORE I9-10900X CPU @ 3.70GHZ 20 11,326 226,520 Intel
17 CORE I9-9900 CPU @ 3.10GHZ 16 13,906 222,496 Intel
18 CORE I7-10700 CPU @ 2.90GHZ 16 13,556 216,896 Intel
19 RYZEN 7 3700X 8-CORE 16 11,884 190,144 AMD
20 RYZEN 5 3600 6-CORE 12 14,262 171,144 AMD
21 RYZEN 7 PRO 4750G 16 10,260 164,160 AMD
22 11TH GEN CORE I9-11900F @ 2.50GHZ 16 10,194 163,104 Intel
23 EPYC 7401P 24-CORE 48 3,188 153,024 AMD
24 CORE I5-10400 CPU @ 2.90GHZ 12 12,161 145,932 Intel
25 11TH GEN CORE I5-11400 @ 2.60GHZ 12 10,673 128,076 Intel
26 CORE I7-10700T CPU @ 2.00GHZ 16 7,677 122,832 Intel
27 CORE I9-8950HK CPU @ 2.90GHZ 12 9,803 117,636 Intel
28 RYZEN 5 1600 SIX-CORE 12 9,080 108,960 AMD
29 RYZEN 7 2700X EIGHT-CORE 16 5,615 89,840 AMD