| dc.identifier.uri | http://hdl.handle.net/11401/77138 | |
| dc.description.sponsorship | This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree. | en_US |
| dc.format | Monograph | |
| dc.format.medium | Electronic Resource | en_US |
| dc.language.iso | en_US | |
| dc.publisher | The Graduate School, Stony Brook University: Stony Brook, NY. | |
| dc.type | Dissertation | |
| dcterms.abstract | Generalized Born solvent model offers inexpensive approach for solvation energy calculation as compared to explicit solvent and Poisson-Boltzmann (PB) method. Thanks to its speed, GB models have been widely used in molecular dynamics (MD) simulations. However the speed comes with tradeoffs. Literatures have pointed out the weaknesses of GB models in inaccurately calculating solvation energy that leads to helical bias in protein simulation or unstable DNA/RNA duplex in nucleic acid simulation. Here we introduced the reparameterization of the recently developed GB-Neck model to improve its accuracy. Compared to other pairwise GB models (e.g. GB-OBC and GB-Neck) the new GB models have better agreement to very accurate (but slow) PB method in terms of reproducing solvation energies for a variety of systems from protein to nucleic acid. For the protein, secondary structure preferences are in much better agreement with explicit solvent simulations. We also obtain near-quantitative reproduction of experimental structure and thermal stability profiles for several model peptides. Moreover the model is able to reproduce the folding of microsecond to millisecond time scale folding of a series of larger proteins. For the nucleic acid, simulations maintain stable trajectories for various DNA and RNA duplexes through MD simulations and also correctly fold DNA/RNA hairpin from extended conformation. | |
| dcterms.available | 2017-09-20T16:52:04Z | |
| dcterms.contributor | Simmerling, Carlos | en_US |
| dcterms.contributor | Rizzo, Robert | en_US |
| dcterms.contributor | Tonge, Peter | en_US |
| dcterms.contributor | Seeliger, Markus. | en_US |
| dcterms.creator | Nguyen, Hai Minh | |
| dcterms.dateAccepted | 2017-09-20T16:52:04Z | |
| dcterms.dateSubmitted | 2017-09-20T16:52:04Z | |
| dcterms.description | Department of Chemistry. | en_US |
| dcterms.extent | 240 pg. | en_US |
| dcterms.format | Application/PDF | en_US |
| dcterms.format | Monograph | |
| dcterms.identifier | http://hdl.handle.net/11401/77138 | |
| dcterms.issued | 2014-12-01 | |
| dcterms.language | en_US | |
| dcterms.provenance | Made available in DSpace on 2017-09-20T16:52:04Z (GMT). No. of bitstreams: 1
Nguyen_grad.sunysb_0771E_11965.pdf: 25495173 bytes, checksum: 743337218382e8e21d4c08e0a074f5ea (MD5)
Previous issue date: 1 | en |
| dcterms.publisher | The Graduate School, Stony Brook University: Stony Brook, NY. | |
| dcterms.subject | Chemistry | |
| dcterms.title | Improved Generalized Born Solvent Model Parameters for Protein and Nucleic Acid Simulations | |
| dcterms.type | Dissertation | |
