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

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          Abstract

          Alchemical transformation of solutes using classical fixed-charge force fields is a popular strategy for assessing the free energy of transfer in different environments. Accurate estimations of transfer between phases with significantly different polarities can be difficult because of the static nature of the force fields. Here, we report on an application of such calculations in the SAMPL5 experiment that also involves an effort in balancing solute and solvent interactions via their expected static dielectric constants. This strategy performs well with respect to predictive accuracy and correlation with unknown experimental values. We follow this by performing a series of retrospective investigations which highlight the potential importance of proper balancing in these systems, and we use a null hypothesis analysis to explore potential biases in the comparisons with experiment. The collective findings indicate that considerations of force field compatibility through dielectric behavior is a potential strategy for future improvements in transfer processes between disparate environments.

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          The online version of this article (doi:10.1007/s10822-016-9950-z) contains supplementary material, which is available to authorized users.

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          Most cited references20

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          Epik: a software program for pK( a ) prediction and protonation state generation for drug-like molecules.

          Epik is a computer program for predicting pK(a) values for drug-like molecules. Epik can use this capability in combination with technology for tautomerization to adjust the protonation state of small drug-like molecules to automatically generate one or more of the most probable forms for use in further molecular modeling studies. Many medicinal chemicals can exchange protons with their environment, resulting in various ionization and tautomeric states, collectively known as protonation states. The protonation state of a drug can affect its solubility and membrane permeability. In modeling, the protonation state of a ligand will also affect which conformations are predicted for the molecule, as well as predictions for binding modes and ligand affinities based upon protein-ligand interactions. Despite the importance of the protonation state, many databases of candidate molecules used in drug development do not store reliable information on the most probable protonation states. Epik is sufficiently rapid and accurate to process large databases of drug-like molecules to provide this information. Several new technologies are employed. Extensions to the well-established Hammett and Taft approaches are used for pK(a) prediction, namely, mesomer standardization, charge cancellation, and charge spreading to make the predicted results reflect the nature of the molecule itself rather just for the particular Lewis structure used on input. In addition, a new iterative technology for generating, ranking and culling the generated protonation states is employed.
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            Prediction of Absolute Solvation Free Energies using Molecular Dynamics Free Energy Perturbation and the OPLS Force Field.

            The accurate prediction of protein-ligand binding free energies is a primary objective in computer-aided drug design. The solvation free energy of a small molecule provides a surrogate to the desolvation of the ligand in the thermodynamic process of protein-ligand binding. Here, we use explicit solvent molecular dynamics free energy perturbation to predict the absolute solvation free energies of a set of 239 small molecules, spanning diverse chemical functional groups commonly found in drugs and drug-like molecules. We also compare the performance of absolute solvation free energies obtained using the OPLS_2005 force field with two other commonly used small molecule force fields-general AMBER force field (GAFF) with AM1-BCC charges and CHARMm-MSI with CHelpG charges. Using the OPLS_2005 force field, we obtain high correlation with experimental solvation free energies (R(2) = 0.94) and low average unsigned errors for a majority of the functional groups compared to AM1-BCC/GAFF or CHelpG/CHARMm-MSI. However, OPLS_2005 has errors of over 1.3 kcal/mol for certain classes of polar compounds. We show that predictions on these compound classes can be improved by using a semiempirical charge assignment method with an implicit bond charge correction.
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              Fast, efficient generation of high-quality atomic charges. AM1-BCC model: I. Method

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                Author and article information

                Contributors
                christopher.fennell@okstate.edu
                Journal
                J Comput Aided Mol Des
                J. Comput. Aided Mol. Des
                Journal of Computer-Aided Molecular Design
                Springer International Publishing (Cham )
                0920-654X
                1573-4951
                29 August 2016
                29 August 2016
                2016
                : 30
                : 11
                : 1059-1065
                Affiliations
                [1 ]Department of Chemistry, Oklahoma State University, Stillwater, OK 74078 USA
                [2 ]Department of Chemical Engineering, Oklahoma State University, Stillwater, OK 74078 USA
                Article
                9950
                10.1007/s10822-016-9950-z
                5206264
                27573982
                fb5576aa-b897-4b5c-b1dd-4e4c57d4268d
                © The Author(s) 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 21 June 2016
                : 21 August 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;
                Award ID: GM063592
                Categories
                Article
                Custom metadata
                © Springer International Publishing Switzerland 2016

                Biomedical engineering
                sampl,force field,solvation free energy,dielectric constant,distribution coefficient

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