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New Solvation Model Has Wide Applicability
Supercomputing
Institute researchers in the Chemistry Department have completed a universal
solvation model that may be useful for a wide variety of processes in organic, biological,
medicinal, and environmental chemistry. For example, the new model can be used to
predict the partitioning of potential drug molecules between the blood and the central
nervous system, thereby contributing to computer-aided drug design. In addition,
insights gained in the creation of this model are being used to create a new solvation
model for organometallic catalysis of polyethylene production. The new model, called
Solvation Model 5.4 (SM5.4) builds on several years of effort funded by the National
Science Foundation, National Institute of Standards and Technology, Eastman Kodak
Company, and the U.S. Army.
The SM5.4 model has two key physical elements: (i) a quantum mechanical self-consistent
treatment of electrostatic mutual polarization of the solvent and solute based on
class IV partial atomic charges, and (ii) a dual-range, solute-geometry dependent
treatment of first-solvation-shell effects such as cavity creation, dispersion, solvent
structural rearrangements, hydrogen bonding, and the hydrophobic effect. The model
is semiempirical and was parameterized using 1,939 free energies of solvation for
over 200 solutes in water and 90 organic solvents plus 26 chloroform/water partition
coefficients. The mean unsigned error is less than 0.5 kilocalories per mole across
a wide range of solute and solvent functionality.
A typical application in organic chemistry would be the prediction of solvation effects
on the free energies of activation for chemical reactions. The model has already
been applied successfully to several biological problems, including the partitioning
of nucleic acid bases between water and organic media simulating lipophilic biophases,
the electrostatic polarization of dipeptides by surrounding aqueous solvent, and
the solution-phase conformational energies of sugars. The SM5.4 model will soon be
made generally available in the popular AMSOL computer program, version 6.0.
Structures of 1-methylcytosine and 5-bromo-1-methylcytosine,
which are, respectively, a natural and an unnatural nucleic acid base. The SM5.4
model predicts that the direct effect of the circled bromine atom as compared to
the hydrogen in the other structure promotes partitioning into chloroform over water
by 1.0 log unit, and the bromine atom changes the contribution of the other two circled
groups by 0.4 log units in the same direction. The contributions from the rest of
the molecules total only 0.2 log units, for a predicted total substituent effect
of 1.6 log units. Such predictions can be very useful for designing molecules to
have desirable properties for medicinal chemistry.
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5-bromo-1-methylcytosine
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1-methylcytosine
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The principal investigators for the development of the SM5.4 model were Christopher
J. Cramer and Donald G. Truhlar of the Chemistry Department. The other researchers
involved in this effort were former AHPCRC postdoctoral associate Candee C. Chambers
(now on the faculty of Mercyhurst College, Erie, Pennsylvania), graduate students
David Giesen and Gregory J. Hawkins, and former Minnesota Supercomputing Institute
undergraduate intern Michael (Zhen) Gu. The Class IV charge model was developed by
former postdoctoral associate Joey Storer (now with Dow Chemical Co.) along with
Giesen, Cramer, and Truhlar. New researchers working on further related projects
include Drs. Tianhui (Tony) Zhu and Jiabo Li along with graduate student Jianhua
Xing. Further work also involves industrial partners Oxford Molecular Inc. and Semichem
Inc.
Further information on this project is available in several UMSI Research Reports,
namely 96/214, 97/18, 97/19, and 97/21. These reports are listed on pages 10 and
11 of this bulletin and are available by completing the form on page 15. The interested
reader is also referred to the AMSOL home page:
http://amsol.chem.umn.edu/~amsol/
The quantum chemical prediction of material and chemical properties by scientific
computation on advanced computer architectures is a key digital technology, and this
work is an example of several projects in this area being conducted at the Supercomputing
Institute.
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