PROJECT #18400 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 Tuesday, 28 September 2021 06:02:45

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PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Tuesday, 28 September 2021 06:02:45

Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make
1 RYZEN 9 3950X 16-CORE 32 35,146 1,124,672 AMD
2 RYZEN 7 5800X 8-CORE 16 30,101 481,616 AMD
3 RYZEN 9 5950X 16-CORE 32 13,646 436,672 AMD
4 RYZEN 7 3800X 8-CORE 16 21,559 344,944 AMD
5 CORE I9-10850K CPU @ 3.60GHZ 20 17,169 343,380 Intel
6 RYZEN 9 3900X 12-CORE 24 12,252 294,048 AMD
7 CORE I7-8700 CPU @ 3.20GHZ 12 19,719 236,628 Intel
8 XEON CPU E5-2690 V4 @ 2.60GHZ 28 7,037 197,036 Intel
9 RYZEN 7 2700X EIGHT-CORE 16 11,053 176,848 AMD
10 CORE I5-10400 CPU @ 2.90GHZ 12 12,277 147,324 Intel
11 RYZEN 9 3900XT 12-CORE 24 6,071 145,704 AMD
12 RYZEN 5 3600 6-CORE 12 10,614 127,368 AMD
13 RYZEN 5 2600 SIX-CORE 12 8,349 100,188 AMD
14 CORE I7-6700K CPU @ 4.00GHZ 8 11,013 88,104 Intel
15 CORE I7-8705G CPU @ 3.10GHZ 8 10,783 86,264 Intel
16 CORE I7-10750H CPU @ 2.60GHZ 12 4,367 52,404 Intel
17 CORE I5-7200U CPU @ 2.50GHZ 4 12,066 48,264 Intel