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.

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 Friday, 03 December 2021 04:36:07

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PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Friday, 03 December 2021 04:36:07

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 38,931 1,245,792 AMD
2 RYZEN 9 5900X 12-CORE 24 23,712 569,088 AMD
3 CORE I9-7920X CPU @ 2.90GHZ 24 18,161 435,864 Intel
4 RYZEN 7 5800X 8-CORE 16 27,024 432,384 AMD
5 RYZEN 9 3950X 16-CORE 32 13,162 421,184 AMD
6 RYZEN 7 3700X 8-CORE 16 19,139 306,224 AMD
7 RYZEN 5 5600X 6-CORE 12 22,093 265,116 AMD
8 CORE I7-8700 CPU @ 3.20GHZ 12 19,824 237,888 Intel
9 CORE I9-10900X CPU @ 3.70GHZ 20 11,326 226,520 Intel
10 CORE I5-10400 CPU @ 2.90GHZ 12 16,407 196,884 Intel
11 RYZEN 5 3600 6-CORE 12 14,052 168,624 AMD
12 11TH GEN CORE I9-11900F @ 2.50GHZ 16 10,194 163,104 Intel
13 RYZEN 5 1600 SIX-CORE 12 8,838 106,056 AMD
14 RYZEN 7 2700X EIGHT-CORE 16 5,615 89,840 AMD