PPDDB data as of Sunday, 29 November 2020 11:22:33
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.
(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.
Manager(s): Si Zhang
Institution: Temple University
Project URL: http://voelzlab.org
|GeForce RTX 2080 Ti||Nvidia||TU102||1,261,066||124,035||10.17||2 hrs 22 mins|
|GeForce RTX 3080 10GB / 20GB||Nvidia||GA102||1,152,110||119,074||9.68||2 hrs 29 mins|
|GeForce RTX 2080 Super||Nvidia||TU104||1,064,650||116,330||9.15||3 hrs 37 mins|
|GeForce RTX 2060 Super||Nvidia||TU106||919,002||111,316||8.26||3 hrs 54 mins|
|GeForce RTX 2080 Ti Rev. A||Nvidia||TU102||834,886||107,642||7.76||3 hrs 6 mins|
|GeForce RTX 2080 SUPER Mobile / Max-Q||Nvidia||TU104M||789,216||105,188||7.50||3 hrs 12 mins|
|Tesla T4||Nvidia||TU104GL||756,928||104,285||7.26||3 hrs 18 mins|
|GeForce RTX 2070 SUPER||Nvidia||TU104||740,258||98,152||7.54||3 hrs 11 mins|
|GeForce GTX 1070 Ti||Nvidia||GP104||688,732||101,148||6.81||4 hrs 31 mins|
|GeForce GTX 1080||Nvidia||GP104||676,070||99,889||6.77||4 hrs 33 mins|
|GeForce RTX 2060||Nvidia||TU104||666,861||99,837||6.68||4 hrs 36 mins|
|GeForce RTX 2060||Nvidia||TU106||632,080||98,239||6.43||4 hrs 44 mins|
|Radeon RX Vega 56/64||AMD||Vega 10 XL/XT||552,308||92,906||5.94||4 hrs 2 mins|
|P106-100||Nvidia||GP106||435,360||86,669||5.02||5 hrs 47 mins|
|GeForce GTX 980||Nvidia||GM204||366,547||81,879||4.48||5 hrs 22 mins|
|GeForce GTX 1060 6GB||Nvidia||GP106||363,335||81,470||4.46||5 hrs 23 mins|
|Radeon RX 470/480/570/580/590||AMD||Ellesmere XT||339,499||79,980||4.24||6 hrs 39 mins|
|GeForce GTX 970||Nvidia||GM204||292,773||76,214||3.84||6 hrs 15 mins|
|P106-090||Nvidia||GP106||215,624||68,680||3.14||8 hrs 39 mins|
|Radeon R9 200/300 Series||AMD||Hawaii||213,246||67,138||3.18||8 hrs 33 mins|
|Radeon R9 M295X||AMD||Amethyst XT||156,948||58,987||2.66||9 hrs 1 mins|
|Polaris11||AMD||Baffin||113,136||55,341||2.04||12 hrs 44 mins|
|GeForce GTX 750 Ti||Nvidia||GM107||84,917||50,485||1.68||14 hrs 16 mins|
|Radeon HD 7800||AMD||Pitcairn||83,144||49,981||1.66||14 hrs 26 mins|
AVG PPD per 1 LP
Legal Information: This sites use is for entertainment purposes only and comes with no guarantees or warranties in its use or related to any data displayed, collected or calcuated. This site is not affilated with folding@home or any folding team or GPU company in any official capacity and is an enthusiast creation in support of folding@home and the users / teams folding data for the greater good.
Please Note: By using this site, and / or our chrome extension you understand that you may be periodically providing information such as your IP, stats regarding use of our site, and folding@home GPU model, Work Unit ID and PPD estimate data when using our chrome extention to the site developer for site optimization and PPD related data displayed on the site.
If you do not wish to contribute data to the GPU PPD database please uninstall our plugin and discontinue use of this site immediately.