PROJECT #16907 RESEARCH FOR CANCER
FOLDING PERFORMANCE PROFILE

PROJECT SUMMARY

Recently, cyclic peptides have gained increasing interests due to their potential applications in the “undruggable” target space of intracellular protein-protein interactions that are difficult to target using small molecules. Although the size and complexity of most cyclic peptides often fail to meet Lipinski’s Rule of Five (1) for predicting drug-likeness, there are known examples of natural products such as cyclosporin A (CsA) that can cross cell membrane by passive diffusion. However, its mutant, CsE has one order of magnitude lower permeability, even though it differs only in one backbone methylation. Early studies (2, 3) give insights into studying the conformational behaviors of CsA and CsE from kinetic aspect to understand the siginificant difference. Thus, in this study, we will perform all-atom MD simulations to study the conformational behaviors of CsA and its varivants in solvents and crossing membrane.  We hope with the kinetic information obtained from our MD simulation, we could investigate and rationalize the differences in permeability of CsA and its variants as well as other cyclic peptide families from kinetic aspects.

References:

(1) Lipinski, C. A. (2000). Drug-like properties and the causes of poor solubility and poor permeability. Journal of Pharmacological and Toxicological Methods.

(2) Witek, J., Keller, B. G., Blatter, M., Meissner, A., Wagner, T., & Riniker, S. (2016). Kinetic Models of Cyclosporin A in Polar and Apolar Environments Reveal Multiple Congruent Conformational States. Journal of Chemical Information and Modeling.

(3) Ahlbach, C. L., Lexa, K. W., Bockus, A. T., Chen, V., Crews, P., Jacobson, M. P., & Lokey, R. S. (2015). Beyond cyclosporine A: Conformation-dependent passive membrane permeabilities of cyclic peptide natural products. Future Medicinal Chemistry.

PROJECT INFO

Manager(s): Si Zhang

Institution: Temple University

Project URL: http://voelzlab.org

PROJECT WORK UNIT SUMMARY

Atoms: 6,800

Core: OPENMM_21

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Friday, 03 December 2021 04:36:11

Rank
Project
Model Name
Folding@Home Identifier
Make
Brand
GPU
Model
PPD
Average
Points WU
Average
WUs Day
Average
WU Time
Average
1 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 1,261,066 124,035 10.17 2 hrs 22 mins
2 GeForce RTX 3080 10GB / 20GB
GA102 [GeForce RTX 3080 10GB / 20GB]
Nvidia GA102 1,152,110 119,074 9.68 2 hrs 29 mins
3 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 1,064,650 116,330 9.15 3 hrs 37 mins
4 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 919,002 111,316 8.26 3 hrs 54 mins
5 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 834,886 107,642 7.76 3 hrs 6 mins
6 GeForce RTX 2080 SUPER Mobile / Max-Q
TU104M [GeForce RTX 2080 SUPER Mobile / Max-Q]
Nvidia TU104M 789,216 105,188 7.50 3 hrs 12 mins
7 Tesla T4
TU104GL [Tesla T4] 8141
Nvidia TU104GL 756,928 104,285 7.26 3 hrs 18 mins
8 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 740,258 98,152 7.54 3 hrs 11 mins
9 GeForce GTX 1070 Ti
GP104 [GeForce GTX 1070 Ti] 8186
Nvidia GP104 688,732 101,148 6.81 4 hrs 31 mins
10 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 676,070 99,889 6.77 4 hrs 33 mins
11 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 666,861 99,837 6.68 4 hrs 36 mins
12 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 632,080 98,239 6.43 4 hrs 44 mins
13 Radeon RX Vega 56/64
Vega 10 XL/XT [Radeon RX Vega 56/64]
AMD Vega 10 XL/XT 552,308 92,906 5.94 4 hrs 2 mins
14 P106-100
GP106 [P106-100]
Nvidia GP106 435,360 86,669 5.02 5 hrs 47 mins
15 GeForce GTX 980
GM204 [GeForce GTX 980] 4612
Nvidia GM204 366,547 81,879 4.48 5 hrs 22 mins
16 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 363,335 81,470 4.46 5 hrs 23 mins
17 Radeon RX 470/480/570/580/590
Ellesmere XT [Radeon RX 470/480/570/580/590]
AMD Ellesmere XT 339,499 79,980 4.24 6 hrs 39 mins
18 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 292,773 76,214 3.84 6 hrs 15 mins
19 P106-090
GP106 [P106-090]
Nvidia GP106 215,624 68,680 3.14 8 hrs 39 mins
20 Radeon R9 200/300 Series
Hawaii [Radeon R9 200/300 Series]
AMD Hawaii 213,246 67,138 3.18 8 hrs 33 mins
21 Radeon R9 M295X
Amethyst XT [Radeon R9 M295X]
AMD Amethyst XT 156,948 58,987 2.66 9 hrs 1 mins
22 Polaris11
Baffin [Polaris11]
AMD Baffin 113,136 55,341 2.04 12 hrs 44 mins
23 GeForce GTX 750 Ti
GM107 [GeForce GTX 750 Ti] 1389
Nvidia GM107 84,917 50,485 1.68 14 hrs 16 mins
24 Radeon HD 7800
Pitcairn [Radeon HD 7800]
AMD Pitcairn 83,144 49,981 1.66 14 hrs 26 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Friday, 03 December 2021 04:36:11

Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make