To improve computational modeling in biology, we need to deepen our understanding of water and improve our models of solvation. Explicit water models are computationally expensive and implicit water models miss much of the physics, so computer simulations of biomolecules often don't predict experiments as well as they could. We propose here a new approach to solvation that aims to be as accurate as explicit models and as fast as implicit models. We have three aims: (1) To develop 3D analytical and integral-equation approaches to compute structures and energetics of water, (2) To compare explicit with implicit solvation simulations to learn the nature of water structuring in solvation shells, and (3) To develop a Semi-Explicit method for solvation, which is faster than explicit, and more physical than implicit. Our approach is based more on the local statistical mechanics of each water molecule, rather than on continuum approximations (implicit), or brute force stochastic simulations. Our preliminary results give us optimism that this approach is working. Our model gives the density of water vs. temperature as accurately as TIP4P-Ew but 6 orders of magnitude faster. The preliminary phase diagram of water looks good. Our solvation model is capturing the free energies of solvation of neutrals and polar solutes about as accurately as explicit, and is about as fast to compute as GB. Our recent results in the blind SAMPL computational solvation modeling event are highly encouraging.

Public Health Relevance

The foundation of biological processes starts at the molecular level, and one of our key tools for understanding microscopic systems is computational modeling. Computer simulations of biomolecules often don't predict experiments as well as they could, and one of the primary reasons is limitations in the modeling of ever present water. We propose to develop new approaches for treating water that aim to deepen our understanding and lift the limitations of models for solvation.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM063592-12
Application #
8325067
Study Section
Macromolecular Structure and Function D Study Section (MSFD)
Program Officer
Preusch, Peter C
Project Start
2001-09-01
Project End
2014-08-31
Budget Start
2012-09-01
Budget End
2013-08-31
Support Year
12
Fiscal Year
2012
Total Cost
$273,415
Indirect Cost
$86,542
Name
State University New York Stony Brook
Department
Chemistry
Type
Schools of Arts and Sciences
DUNS #
804878247
City
Stony Brook
State
NY
Country
United States
Zip Code
11794
Urbic, Tomaz (2014) Ions increase strength of hydrogen bond in water. Chem Phys Lett 610-611:159-162
Gujt, Jure; Bešter-Roga?, Marija; Hribar-Lee, Barbara (2014) An Investigation of Ion-Pairing of Alkali Metal Halides in Aqueous Solutions Using the Electrical Conductivity and the Monte Carlo Computer Simulation Methods. J Mol Liq 190:34-41
Lukši?, Miha; Fennell, Christopher J; Dill, Ken A (2014) Using interpolation for fast and accurate calculation of ion-ion interactions. J Phys Chem B 118:8017-25
Rocklin, Gabriel J; Mobley, David L; Dill, Ken A (2013) Calculating the sensitivity and robustness of binding free energy calculations to force field parameters. J Chem Theory Comput 9:3072-3083
Fennell, Christopher J; Kehoe, Charlie; Dill, Ken A (2010) Oil/water transfer is partly driven by molecular shape, not just size. J Am Chem Soc 132:234-40
Fennell, Christopher J; Bizjak, Alan; Vlachy, Vojko et al. (2009) Ion pairing in molecular simulations of aqueous alkali halide solutions. J Phys Chem B 113:6782-91
Mobley, David L; Bayly, Christopher I; Cooper, Matthew D et al. (2009) Predictions of hydration free energies from all-atom molecular dynamics simulations. J Phys Chem B 113:4533-7
Mobley, David L; Bayly, Christopher I; Cooper, Matthew D et al. (2009) Small molecule hydration free energies in explicit solvent: An extensive test of fixed-charge atomistic simulations. J Chem Theory Comput 5:350-358
Hribar-Lee, Barbara; Vlachy, Vojko; Dill, Ken A (2009) Modeling Hofmeister Effects. Acta Chim Slov 56:196-202
Mobley, David L; Barber 2nd, Alan E; Fennell, Christopher J et al. (2008) Charge asymmetries in hydration of polar solutes. J Phys Chem B 112:2405-14

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