Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.

Prediction of P-glycoprotein inhibitors with machine learning classification models and 3D-RISM-KH theory based solvation energy descriptors

Autor: Hinge, Vijaya Kumar, Roy, Dipankar, Kovalenko, Andriy

Publikováno v: Journal of Computer-Aided Molecular Design. 33:965-971

Development of novel in silico methods for questing novel PgP inhibitors is crucial for the reversal of multi-drug resistance in cancer therapy. Here, we report machine learning based binary classification schemes to identify the PgP inhibitors from

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::447ebceb9dede4c4757032e871dc2cbb
https://doi.org/10.1007/s10822-019-00253-5

Activity Coefficient of Triton X100 and Brij S20 in the Infinitely Diluted Micellar Pseudophase of the Binary Micelle Triton X100–Brij S20 in the Water Phase at the Temperature Interval T = (283.15–318.15) K

Autor: Ana Pilipović, Mihalj Poša

Publikováno v: Journal of Chemical & Engineering Data. 65:106-119

Activity coefficients of the infinitely diluted micellar pseudophase are equal to parameters of the second-order Margules function: ln φi∞ = aij and ln φj∞ = aji. The excess chemical potential of t...

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::bfc5163415e0af1aac832893afed58c4
https://doi.org/10.1021/acs.jced.9b00797

Density-functional-theory approach to the Hamiltonian adaptive resolution simulation method

Autor: Ravi C. Dutta, Raffaello Potestio, Mauricio Sevilla, Kurt Kremer, Robinson Cortes-Huerto, Luis A. Baptista, Maziar Heidari

Publikováno v: Journal of Physics: Condensed Matter

In the Hamiltonian adaptive resolution simulation method (H–AdResS) it is possible to simulate coexisting atomistic (AT) and ideal gas representations of a physical system that belong to different subdomains within the simulation box. The Hamiltoni

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d82c0f03b81af0ffd246ed06aa73e49
https://iopscience.iop.org/article/10.1088/1361-648X/abed1d

Accurate prediction of hydration free energies and solvation structures using molecular density functional theory with a simple bridge functional

Autor: Luc Belloni, Sohvi Luukkonen, Guillaume Jeanmairet, Daniel Borgis

Publikováno v: Journal of Chemical Physics
Journal of Chemical Physics, American Institute of Physics, 2021, 155 (2), pp.024117. ⟨10.1063/5.0057506⟩
Journal of Chemical Physics, 2021, 155 (2), pp.024117. ⟨10.1063/5.0057506⟩

International audience; This paper assesses the ability of molecular density functional theory to predict efficiently and accurately the hydration free energies of molecular solutes and the surrounding microscopic water structure. A wide range of sol

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8a7d2dd32aafc97a5bfad8f7e83d084c
https://hal.archives-ouvertes.fr/hal-03414656