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Items: 1 to 20 of 111

1.

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.

2.

Blind prediction of cyclohexane-water distribution coefficients from the SAMPL5 challenge.

Bannan CC, Burley KH, Chiu M, Shirts MR, Gilson MK, Mobley DL.

J Comput Aided Mol Des. 2016 Nov;30(11):927-944. doi: 10.1007/s10822-016-9954-8. Epub 2016 Sep 27.

3.

Extended solvent-contact model approach to blind SAMPL5 prediction challenge for the distribution coefficients of drug-like molecules.

Chung KC, Park H.

J Comput Aided Mol Des. 2016 Nov;30(11):1019-1033. doi: 10.1007/s10822-016-9928-x. Epub 2016 Jul 23.

PMID:
27448686
4.

Prediction of cyclohexane-water distribution coefficients with COSMO-RS on the SAMPL5 data set.

Klamt A, Eckert F, Reinisch J, Wichmann K.

J Comput Aided Mol Des. 2016 Nov;30(11):959-967. doi: 10.1007/s10822-016-9927-y. Epub 2016 Jul 26.

PMID:
27460058
5.

Predicting cyclohexane/water distribution coefficients for the SAMPL5 challenge using MOSCED and the SMD solvation model.

Diaz-Rodriguez S, Bozada SM, Phifer JR, Paluch AS.

J Comput Aided Mol Des. 2016 Nov;30(11):1007-1017. doi: 10.1007/s10822-016-9945-9. Epub 2016 Aug 26.

PMID:
27565796
6.

Partition coefficients for the SAMPL5 challenge using transfer free energies.

Jones MR, Brooks BR, Wilson AK.

J Comput Aided Mol Des. 2016 Nov;30(11):1129-1138. doi: 10.1007/s10822-016-9964-6. Epub 2016 Sep 19.

PMID:
27646287
7.

Prediction of cyclohexane-water distribution coefficients for the SAMPL5 data set using molecular dynamics simulations with the OPLS-AA force field.

Kenney IM, Beckstein O, Iorga BI.

J Comput Aided Mol Des. 2016 Nov;30(11):1045-1058. doi: 10.1007/s10822-016-9949-5. Epub 2016 Aug 31.

PMID:
27581968
8.

Prediction of cyclohexane-water distribution coefficient for SAMPL5 drug-like compounds with the QMPFF3 and ARROW polarizable force fields.

Kamath G, Kurnikov I, Fain B, Leontyev I, Illarionov A, Butin O, Olevanov M, Pereyaslavets L.

J Comput Aided Mol Des. 2016 Nov;30(11):977-988. doi: 10.1007/s10822-016-9958-4. Epub 2016 Sep 1.

PMID:
27585472
9.

The SAMPL5 challenge for embedded-cluster integral equation theory: solvation free energies, aqueous pK a, and cyclohexane-water log D.

Tielker N, Tomazic D, Heil J, Kloss T, Ehrhart S, Güssregen S, Schmidt KF, Kast SM.

J Comput Aided Mol Des. 2016 Nov;30(11):1035-1044. doi: 10.1007/s10822-016-9939-7. Epub 2016 Aug 23.

PMID:
27554666
10.

All-atom/coarse-grained hybrid predictions of distribution coefficients in SAMPL5.

Genheden S, Essex JW.

J Comput Aided Mol Des. 2016 Nov;30(11):969-976. doi: 10.1007/s10822-016-9926-z. Epub 2016 Jul 26.

11.

Calculating distribution coefficients based on multi-scale free energy simulations: an evaluation of MM and QM/MM explicit solvent simulations of water-cyclohexane transfer in the SAMPL5 challenge.

König G, Pickard FC 4th, Huang J, Simmonett AC, Tofoleanu F, Lee J, Dral PO, Prasad S, Jones M, Shao Y, Thiel W, Brooks BR.

J Comput Aided Mol Des. 2016 Nov;30(11):989-1006. doi: 10.1007/s10822-016-9936-x. Epub 2016 Aug 30.

PMID:
27577746
12.

Blind prediction of distribution in the SAMPL5 challenge with QM based protomer and pK a corrections.

Pickard FC 4th, König G, Tofoleanu F, Lee J, Simmonett AC, Shao Y, Ponder JW, Brooks BR.

J Comput Aided Mol Des. 2016 Nov;30(11):1087-1100. doi: 10.1007/s10822-016-9955-7. Epub 2016 Sep 19.

PMID:
27646286
13.

Calculation of distribution coefficients in the SAMPL5 challenge from atomic solvation parameters and surface areas.

Santos-Martins D, Fernandes PA, Ramos MJ.

J Comput Aided Mol Des. 2016 Nov;30(11):1079-1086. doi: 10.1007/s10822-016-9951-y. Epub 2016 Sep 1.

PMID:
27585473
14.

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
15.

Adapting the semi-explicit assembly solvation model for estimating water-cyclohexane partitioning with the SAMPL5 molecules.

Brini E, Paranahewage SS, Fennell CJ, Dill KA.

J Comput Aided Mol Des. 2016 Nov;30(11):1067-1077. doi: 10.1007/s10822-016-9961-9. Epub 2016 Sep 8.

16.

Predicting water-to-cyclohexane partitioning of the SAMPL5 molecules using dielectric balancing of force fields.

Paranahewage SS, Gierhart CS, Fennell CJ.

J Comput Aided Mol Des. 2016 Nov;30(11):1059-1065. doi: 10.1007/s10822-016-9950-z. Epub 2016 Aug 29.

17.

Blinded predictions of distribution coefficients in the SAMPL5 challenge.

Bosisio S, Mey AS, Michel J.

J Comput Aided Mol Des. 2016 Nov;30(11):1101-1114. doi: 10.1007/s10822-016-9969-1. Epub 2016 Sep 27.

18.

Setup and validation of shake-flask procedures for the determination of partition coefficients (logD) from low drug amounts.

Andrés A, Rosés M, Ràfols C, Bosch E, Espinosa S, Segarra V, Huerta JM.

Eur J Pharm Sci. 2015 Aug 30;76:181-91. doi: 10.1016/j.ejps.2015.05.008. Epub 2015 May 9. Review.

PMID:
25968358
19.

On the probability of finding a water molecule in a nonpolar cavity.

Wolfenden R, Radzicka A.

Science. 1994 Aug 12;265(5174):936-7.

PMID:
8052849
20.

Temperature and solvent effects in the solubility of some pharmaceutical compounds: Measurements and modeling.

Mota FL, Carneiro AP, Queimada AJ, Pinho SP, Macedo EA.

Eur J Pharm Sci. 2009 Jun 28;37(3-4):499-507. doi: 10.1016/j.ejps.2009.04.009. Epub 2009 May 3.

PMID:
19406228

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