PROJECT #18401 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: 64,500

Core: GRO_A8

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Monday, 27 September 2021 14:58:25

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PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Monday, 27 September 2021 14:58:25

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 31,071 994,272 AMD
2 RYZEN 7 5800X 8-CORE 16 32,311 516,976 AMD
3 RYZEN 9 5950X 16-CORE 32 14,204 454,528 AMD
4 XEON CPU E5-2680 V3 @ 2.50GHZ 24 15,203 364,872 Intel
5 CORE I9-10850K CPU @ 3.60GHZ 20 14,916 298,320 Intel
6 CORE I9-10900X CPU @ 3.70GHZ 20 13,958 279,160 Intel
7 XEON CPU E5-2690 V4 @ 2.60GHZ 28 9,062 253,736 Intel
8 RYZEN 7 3700X 8-CORE 16 14,952 239,232 AMD
9 RYZEN 9 5900X 12-CORE 24 9,475 227,400 AMD