PROJECT #19012 RESEARCH FOR CANNABINOID
FOLDING PERFORMANCE PROFILE

PROJECT SUMMARY

Cannabinoid Receptors Cannabinoid receptors (CBs) are part of the endocannabinoid signaling system, which help to maintain homeostasis in neuron signaling to control pain, obesity, and other neurological disorders.

Therefore, synthetic cannabinoids (SCs) were designed and tested to target CBs as potential therapeutical selective drugs.

Initially, SCs were designed by modulating the scaffolds of known phytocannabinoids.

However, chemically diverse synthetic cannabinoids (Novel Psychoactive Substance (NPS)) were
discovered rapidly, which have a high affinity towards CBs and significantly modulate the receptor activities.

These molecules were started to get sold in the market as abusive drugs under different brand names (e.g., K2, spice) and caused thousands of hospitalizations of patients across the US due to more adverse effects, including impairment of fine motor skills and increased blood pressure, tachycardia.

It is hypothesized that β-arrestin biased downstream signaling of these NPSs causes more adversarial effects compared to classical cannabinoids.

However, how these classical and non-classical cannabinoids affect receptor conformational dynamics distinctly,
has not been mechanistically studied.

In this project, we compare the unbinding mechanism and kinetics of a non-classical cannabinoid, MDMB-Fubinaca, and a classical cannabinoid, HU-210, using biased and unbiased simulation..

PROJECT INFO

Manager(s): Soumajit Dutta

Institution: University of Illinois Urbana-Champaign

Project URL: shuklagroup.org/

PROJECT WORK UNIT SUMMARY

Atoms: 90,246

Core: OPENMM_22

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Monday, 27 June 2022 11:45:16

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 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 6,802,078 263,024 25.86 1 hrs 56 mins
2 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 6,445,113 258,230 24.96 1 hrs 58 mins
3 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 4,922,447 234,774 20.97 1 hrs 9 mins
4 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 4,538,532 229,707 19.76 1 hrs 13 mins
5 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 4,505,143 229,613 19.62 1 hrs 13 mins
6 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 4,124,974 222,837 18.51 1 hrs 18 mins
7 GeForce RTX 3070 Lite Hash Rate
GA104 [GeForce RTX 3070 Lite Hash Rate]
Nvidia GA104 4,057,035 219,411 18.49 1 hrs 18 mins
8 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 3,552,461 208,572 17.03 1 hrs 25 mins
9 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 2,769,023 175,851 15.75 2 hrs 31 mins
10 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 1,986,167 175,493 11.32 2 hrs 7 mins
11 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 1,900,474 171,898 11.06 2 hrs 10 mins
12 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 1,834,961 170,565 10.76 2 hrs 14 mins
13 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 1,702,310 165,932 10.26 2 hrs 20 mins
14 GeForce RTX 2070 SUPER Mobile / Max-Q
TU104M [GeForce RTX 2070 SUPER Mobile / Max-Q]
Nvidia TU104M 1,483,060 159,464 9.30 3 hrs 35 mins
15 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,336,975 153,450 8.71 3 hrs 45 mins
16 Geforce RTX 3050
GA106 [Geforce RTX 3050]
Nvidia GA106 1,305,797 151,417 8.62 3 hrs 47 mins
17 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 924,232 134,026 6.90 3 hrs 29 mins
18 Tesla M40
GM200GL [Tesla M40] 6844
Nvidia GM200GL 920,746 136,352 6.75 4 hrs 33 mins
19 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 869,563 132,841 6.55 4 hrs 40 mins
20 P104-100
GP104 [P104-100]
Nvidia GP104 767,043 128,406 5.97 4 hrs 1 mins
21 GeForce GTX 980
GM204 [GeForce GTX 980] 4612
Nvidia GM204 615,593 119,080 5.17 5 hrs 39 mins
22 GeForce GTX 980 Ti
GM200 [GeForce GTX 980 Ti] 5632
Nvidia GM200 487,258 118,149 4.12 6 hrs 49 mins
23 Quadro M4000
GM204GL [Quadro M4000]
Nvidia GM204GL 209,767 90,117 2.33 10 hrs 19 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Monday, 27 June 2022 11:45:16

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