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I. Quantal effects in biochemical cooperativity and a proposed mechanism for the differentiation of calcium signaling in synaptic plasticity. II. Evolutionary algorithms for the optimization of methods in computational chemistry

Citation

Ford, William Chastang (2012) I. Quantal effects in biochemical cooperativity and a proposed mechanism for the differentiation of calcium signaling in synaptic plasticity. II. Evolutionary algorithms for the optimization of methods in computational chemistry. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/Z9HH6H1Z. http://resolver.caltech.edu/CaltechTHESIS:05302012-122930768

Abstract

In Part 1 of this thesis, we propose that biochemical cooperativity is a fundamentally non-ideal process. We show quantal effects underlying biochemical cooperativity and highlight apparent ergodic breaking at small volumes. The apparent ergodic breaking manifests itself in a divergence of deterministic and stochastic models. We further predict that this divergence of deterministic and stochastic results is a failure of the deterministic methods rather than an issue of stochastic simulations.

Ergodic breaking at small volumes may allow these molecular complexes to function as switches to a greater degree than has previously been shown. We propose that this ergodic breaking is a phenomenon that the synapse might exploit to differentiate Ca2+ signaling that would lead to either the strengthening or weakening of a synapse. Techniques such as lattice-based statistics and rule-based modeling are tools that allow us to directly confront this non-ideality. A natural next step to understanding the chemical physics that underlies these processes is to consider in silico specifically atomistic simulation methods that might augment our modeling efforts.

In the second part of this thesis, we use evolutionary algorithms to optimize in silico methods that might be used to describe biochemical processes at the subcellular and molecular levels. While we have applied evolutionary algorithms to several methods, this thesis will focus on the optimization of charge equilibration methods. Accurate charges are essential to understanding the electrostatic interactions that are involved in ligand binding, as frequently discussed in the first part of this thesis.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:Quantal, Chemical Reaction Dynamics, Stochastic Chemical Reaction Networks, Rule-based Modeling, QEq
Degree Grantor:California Institute of Technology
Division:Engineering and Applied Science
Major Option:Computation and Neural Systems
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Hoffmann, Michael R. (co-advisor)
  • Goddard, William A., III (co-advisor)
Thesis Committee:
  • Gray, Harry B. (chair)
  • Elowitz, Michael B.
  • Abrol, Ravinder
  • Goddard, William A., III
  • Hoffmann, Michael R.
Defense Date:27 September 2011
Record Number:CaltechTHESIS:05302012-122930768
Persistent URL:http://resolver.caltech.edu/CaltechTHESIS:05302012-122930768
DOI:10.7907/Z9HH6H1Z
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:7096
Collection:CaltechTHESIS
Deposited By: William Ford
Deposited On:20 Sep 2016 16:40
Last Modified:11 Apr 2017 23:26

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