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Items: 1 to 20 of 115

1.

Octanol-water partition coefficient measurements for the SAMPL6 blind prediction challenge.

Işık M, Levorse D, Mobley DL, Rhodes T, Chodera JD.

J Comput Aided Mol Des. 2019 Dec 19. doi: 10.1007/s10822-019-00271-3. [Epub ahead of print]

PMID:
31858363
2.

Prediction of the n-octanol/water partition coefficients in the SAMPL6 blind challenge from MST continuum solvation calculations.

Zamora WJ, Pinheiro S, German K, Ràfols C, Curutchet C, Luque FJ.

J Comput Aided Mol Des. 2019 Nov 27. doi: 10.1007/s10822-019-00262-4. [Epub ahead of print]

PMID:
31776809
3.

Prediction of octanol-water partition coefficients for the SAMPL6-[Formula: see text] molecules using molecular dynamics simulations with OPLS-AA, AMBER and CHARMM force fields.

Fan S, Iorga BI, Beckstein O.

J Comput Aided Mol Des. 2020 Jan 20. doi: 10.1007/s10822-019-00267-z. [Epub ahead of print]

PMID:
31960254
4.

Error occurred: cannot get document summary

PMID:
31981015

5.

LogP prediction performance with the SMD solvation model and the M06 density functional family for SAMPL6 blind prediction challenge molecules.

Guan D, Lui R, Matthews S.

J Comput Aided Mol Des. 2020 Jan 14. doi: 10.1007/s10822-020-00278-1. [Epub ahead of print]

PMID:
31939103
6.

1-Octanol/Water Partition Coefficients of n-Alkanes from Molecular Simulations of Absolute Solvation Free Energies.

Garrido NM, Queimada AJ, Jorge M, Macedo EA, Economou IG.

J Chem Theory Comput. 2009 Sep 8;5(9):2436-46. doi: 10.1021/ct900214y.

7.

A blind SAMPL6 challenge: insight into the octanol-water partition coefficients of drug-like molecules via a DFT approach.

Arslan E, Findik BK, Aviyente V.

J Comput Aided Mol Des. 2020 Jan 14. doi: 10.1007/s10822-020-00284-3. [Epub ahead of print]

PMID:
31939104
8.

Use of molecular dynamics fingerprints (MDFPs) in SAMPL6 octanol-water log P blind challenge.

Wang S, Riniker S.

J Comput Aided Mol Des. 2019 Nov 19. doi: 10.1007/s10822-019-00252-6. [Epub ahead of print]

PMID:
31745704
9.

SAMPL6 blind predictions of water-octanol partition coefficients using nonequilibrium alchemical approaches.

Procacci P, Guarnieri G.

J Comput Aided Mol Des. 2019 Oct 17. doi: 10.1007/s10822-019-00233-9. [Epub ahead of print]

PMID:
31624982
10.

pKa measurements for the SAMPL6 prediction challenge for a set of kinase inhibitor-like fragments.

Işık M, Levorse D, Rustenburg AS, Ndukwe IE, Wang H, Wang X, Reibarkh M, Martin GE, Makarov AA, Mobley DL, Rhodes T, Chodera JD.

J Comput Aided Mol Des. 2018 Oct;32(10):1117-1138. doi: 10.1007/s10822-018-0168-0. Epub 2018 Nov 7.

11.

Measuring experimental cyclohexane-water distribution coefficients for the SAMPL5 challenge.

Rustenburg AS, Dancer J, Lin B, Feng JA, Ortwine DF, Mobley DL, Chodera JD.

J Comput Aided Mol Des. 2016 Nov;30(11):945-958. doi: 10.1007/s10822-016-9971-7. Epub 2016 Oct 7.

12.

Comparison of two simulation methods to compute solvation free energies and partition coefficients.

Yang L, Ahmed A, Sandler SI.

J Comput Chem. 2013 Feb 5;34(4):284-93. doi: 10.1002/jcc.23127. Epub 2012 Oct 29.

PMID:
23109246
13.

Direct calculation of 1-octanol-water partition coefficients from adaptive biasing force molecular dynamics simulations.

Bhatnagar N, Kamath G, Chelst I, Potoff JJ.

J Chem Phys. 2012 Jul 7;137(1):014502. doi: 10.1063/1.4730040.

PMID:
22779660
14.

Calculating the Partition Coefficients of Organic Solvents in Octanol/Water and Octanol/Air.

Nedyalkova MA, Madurga S, Tobiszewski M, Simeonov V.

J Chem Inf Model. 2019 May 28;59(5):2257-2263. doi: 10.1021/acs.jcim.9b00212. Epub 2019 May 7.

PMID:
31042037
15.

SAMPL6 Octanol-water partition coefficients from alchemical free energy calculations with MBIS atomic charges.

Riquelme M, Vöhringer-Martinez E.

J Comput Aided Mol Des. 2020 Jan 20. doi: 10.1007/s10822-020-00281-6. [Epub ahead of print]

PMID:
31960251
16.

Octanol-Water Partition Coefficient from 3D-RISM-KH Molecular Theory of Solvation with Partial Molar Volume Correction.

Huang W, Blinov N, Kovalenko A.

J Phys Chem B. 2015 Apr 30;119(17):5588-97. doi: 10.1021/acs.jpcb.5b01291. Epub 2015 Apr 15.

PMID:
25844645
17.

A comparison of molecular representations for lipophilicity quantitative structure-property relationships with results from the SAMPL6 logP Prediction Challenge.

Lui R, Guan D, Matthews S.

J Comput Aided Mol Des. 2020 Jan 13. doi: 10.1007/s10822-020-00279-0. [Epub ahead of print]

PMID:
31933037
18.

SAMPL5: 3D-RISM partition coefficient calculations with partial molar volume corrections and solute conformational sampling.

Luchko T, Blinov N, Limon GC, Joyce KP, Kovalenko A.

J Comput Aided Mol Des. 2016 Nov;30(11):1115-1127. doi: 10.1007/s10822-016-9947-7. Epub 2016 Sep 1.

PMID:
27585474
19.

Predicting partition coefficients of drug-like molecules in the SAMPL6 challenge with Drude polarizable force fields.

Ding Y, Xu Y, Qian C, Chen J, Zhu J, Huang H, Shi Y, Huang J.

J Comput Aided Mol Des. 2020 Jan 20. doi: 10.1007/s10822-020-00282-5. [Epub ahead of print]

PMID:
31960252
20.

Prediction of Partition Coefficients of Environmental Toxins Using Computational Chemistry Methods.

van der Spoel D, Manzetti S, Zhang H, Klamt A.

ACS Omega. 2019 Aug 12;4(9):13772-13781. doi: 10.1021/acsomega.9b01277. eCollection 2019 Aug 27.

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