In order to simulate the interactions of molecules, an accurate method of representing these interactions must be available. Ab initio calculations are able to do this, but these calculations are restricted to relatively small systems. The simulation of larger systems requires a simpler, less computationally intensive method such as molecular mechanics (MM). The force fields employed in MM and MD calculations are a much simpler representation of the potential energy of the system compared to ab initio methods. Fortunately, these force fields have been shown to accurately model many types of systems. Because solvation effects are very important in many biological processes, e.g. catalysis and binding, it is also necessary to model these systems in the condensed phase with the ability to accurately calculate the energetics of desolvation. In recent years, free energy perturbation (FEP) calculations have reproduced experimental values for the free energy of solvation of a variety of molecules, including those with polar and hydrophobic groups. The ability to correlate calculated results to experimental data allows the calibration of the potential functions which are employed. With accurate potential functions, these methods can be used in a predictive manner for molecules whose solvation energies are not accessible experimentally. Cornell et al. have recently re-parameterized the AMBER force field. I am interested in using this new force field to study molecules whose solvation free energies have not been determined experimentally. The nucleic acid bases are one such class of molecules. It is important to be able to accurately model these molecules because the formation of duplex or triplex nucleic acids depends on the energetics of desolvating the bases. The free energies of solvation of 9-methyladenine and 1-methylthymine have been derived from solubilities reported by Clark et al. These free energies have also been calculated by several methods: FEP with the old AMBER 4.0 force field; AMSOL, a recently developed semi-empirical model that includes solvation parameters; and FEP with the OPLS parameter set. The results obtained from the three models and parameter sets are very different. These differences bring into question the accuracy of the models, especially in light of the excellent agreement with experimental data for these models for other classes of polar and hydrophobic molecules. I plan to test the new force field by calculating the solvation free energies of adenine and thymine, and use it in a predictive manner by calculating the energies for guanine and cytosine. For this project I use the Computer Graphics Laboratory facilities in the following ways: MidasPlus to examine the geometry of all structures at the beginning and ending points of the perturbation calculations. In addition, I use the image generation tools when preparing posters and publications.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biotechnology Resource Grants (P41)
Project #
5P41RR001081-19
Application #
5222456
Study Section
Project Start
Project End
Budget Start
Budget End
Support Year
19
Fiscal Year
1996
Total Cost
Indirect Cost
Kozak, John J; Gray, Harry B; Garza-López, Roberto A (2018) Relaxation of structural constraints during Amicyanin unfolding. J Inorg Biochem 179:135-145
Alamo, Lorenzo; Pinto, Antonio; Sulbarán, Guidenn et al. (2018) Lessons from a tarantula: new insights into myosin interacting-heads motif evolution and its implications on disease. Biophys Rev 10:1465-1477
Viswanath, Shruthi; Chemmama, Ilan E; Cimermancic, Peter et al. (2017) Assessing Exhaustiveness of Stochastic Sampling for Integrative Modeling of Macromolecular Structures. Biophys J 113:2344-2353
Chu, Shidong; Zhou, Guangyan; Gochin, Miriam (2017) Evaluation of ligand-based NMR screening methods to characterize small molecule binding to HIV-1 glycoprotein-41. Org Biomol Chem 15:5210-5219
Portioli, Corinne; Bovi, Michele; Benati, Donatella et al. (2017) Novel functionalization strategies of polymeric nanoparticles as carriers for brain medications. J Biomed Mater Res A 105:847-858
Alamo, Lorenzo; Koubassova, Natalia; Pinto, Antonio et al. (2017) Lessons from a tarantula: new insights into muscle thick filament and myosin interacting-heads motif structure and function. Biophys Rev 9:461-480
Nguyen, Hai Dang; Yadav, Tribhuwan; Giri, Sumanprava et al. (2017) Functions of Replication Protein A as a Sensor of R Loops and a Regulator of RNaseH1. Mol Cell 65:832-847.e4
Sofiyev, Vladimir; Kaur, Hardeep; Snyder, Beth A et al. (2017) Enhanced potency of bivalent small molecule gp41 inhibitors. Bioorg Med Chem 25:408-420
Nekouzadeh, Ali; Rudy, Yoram (2016) Conformational changes of an ion-channel during gating and emerging electrophysiologic properties: Application of a computational approach to cardiac Kv7.1. Prog Biophys Mol Biol 120:18-27
Towse, Clare-Louise; Vymetal, Jiri; Vondrasek, Jiri et al. (2016) Insights into Unfolded Proteins from the Intrinsic ?/? Propensities of the AAXAA Host-Guest Series. Biophys J 110:348-361

Showing the most recent 10 out of 508 publications