Incorporating the dynamic nature of molecules improves performance of structure-based function prediction methods
Abstract/Contents
- Abstract
- Structural Genomics consortia aim to determine the structure of proteins with novel folds. In order to interpret their biological significance, it is critical to annotate the functions of these structures. Most structures are solved by X-ray crystallography experiments and represent static snapshots of the molecules. Structure-based function prediction methods do not perform well when the snapshots fail to display the relevant functional conformations. We show that coupling structure-based function prediction methods to molecular dynamics simulations considerably improves their performance in locating calcium binding sites. Our approach can be easily extended to other functions of interest. In particular, we generated short- to medium- scale molecular simulation trajectories (1ns -- 10ns) using GROMACS, a software suite developed for creating molecular dynamics simulations. Gromos 43a5, Gromos 53a6, AMBER '96, AMBER '99SB, AMBER '03, and OPLS-AA force fields were used to generate trajectories for 11 pairs of PDB structures, HOLO and APO form for the presence of calcium ions in the structures (22 structrures in total). Extracting structures at various time points over the course of the simulations we created structural ensembles which inform about the dynamic nature of each of the simulation systems. Using FEATURE, a machine learning algorithm that evaluates the presence of enriched physico-chemical properties around a site of interest, we analyzed the structural ensembles for the presence of calcium binding sites. We devised a clustering algorithm which allowed for definitive determination of the similarity of the local environments around the points identified by FEATURE as potential calcium binding site centers in different structural ensembles for each of the 22 PDB structures. Our results indicate that short scale simulations with 2 or 3 different force fields generate sufficient structural diversity to allow for improved identification of calcium binding sites. Furthermore, inclusion of calcium ions in the simulation systems does not significantly improve the performance of FEATURE. This result highlights the need for improved force fields, such that the dynamic nature of calcium binding sites can be accurately reproduced.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Copyright date | 2011 |
| Publication date | 2010, c2011; 2010 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Glazer, Dariya Sergiuivna |
|---|---|
| Associated with | Stanford University, Department of Genetics |
| Primary advisor | Altman, Russ |
| Thesis advisor | Altman, Russ |
| Thesis advisor | Cherry, Joe H, 1934- |
| Thesis advisor | Levitt, Michael, 1947- |
| Thesis advisor | Sherlock, Gavin |
| Advisor | Cherry, Joe H, 1934- |
| Advisor | Levitt, Michael, 1947- |
| Advisor | Sherlock, Gavin |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Dariya S. Glazer. |
|---|---|
| Note | Submitted to the Department of Genetics. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2011. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2011 by Dariya Sergiuivna Glazer
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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