Towards a deeper understanding of molecular mechanics
Abstract/Contents
- Abstract
- The advent of atomistic molecular dynamics simulations held the promise of a complete understanding of biomolecular dynamics. However, this goal has remained elusive, as increased computational power has brought with it larger systems to simulate and an overwhelming number of observables to analyze. In this work, I describe how recent advancements in Markov state modeling have helped overcome this dimensionality problem and enabled the characterization of complex phenomena, such as the folding-upon-binding processes of intrinsically disordered peptides. But is it possible to produce even more insightful models? To this end, I present a method that exploits Markov state models to infer statistically causal drivers of protein dynamics. Finally, I discuss a neural network alternative to Markov models, which yields physically interpretable insights and has the potential to replace expensive atomistic simulations.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2018; ©2018 |
| Publication date | 2018; 2018 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Hernández, Carlos Xavier |
|---|---|
| Degree supervisor | Pande, Vijay |
| Thesis advisor | Pande, Vijay |
| Thesis advisor | Das, Rhiju |
| Thesis advisor | Markland, Thomas E |
| Degree committee member | Das, Rhiju |
| Degree committee member | Markland, Thomas E |
| Associated with | Stanford University, Biophysics Program. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Carlos Xavier Hernández. |
|---|---|
| Note | Submitted to the Biophysics Program. |
| Thesis | Thesis Ph.D. Stanford University 2018. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2018 by Carlos Xavier Hernandez
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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