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Record W2567500392

Quantifying and Enhancing the Statistical Convergence of Equilibrium and Non-equilibrium Properties in Molecular Simulations of Proteins, Peptides, and Amino Acid Side Chain Analogs Embedded in Lipid Bilayers

2014· dissertation· en· W2567500392 on OpenAlexfundno aff
Chris Neale

Bibliographic record

VenueTSpace (University of Toronto) · 2014
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Structure and Dynamics
Canadian institutionsnot available
FundersCoral Reef Conservation ProgramNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchHospital for Sick ChildrenUniversity of TorontoFonds Québécois de la Recherche sur la Nature et les TechnologiesCanada Research ChairsGovernment of OntarioCompute Canada
KeywordsSide chainConvergence (economics)Molecular dynamicsLipid bilayerChemistryChain (unit)Amino acidStatistical physicsBiological systemBiochemistryComputational chemistryOrganic chemistryPhysicsMembraneBiologyPolymer
DOInot available

Abstract

fetched live from OpenAlex

Atomistic molecular simulations provide high-resolution structural and dynamic characterizations of small molecules, peptides, and proteins interacting with biological membranes. Here I use new methods and massively repeated computer simulations to critically examine the statistical convergence of equilibrium and non-equilibrium properties in molecular simulations of three types of solute in hydrated phospholipid bilayers: amino acid side-chain analogs, the intrinsically disordered antimicrobial peptide indolicidin, and the bacterial magnesium channel CorA. This thesis is as much a journey to discover what one can learn from simulations by quantifying their sampling errors as it is a quest for convergence using massive computational resources and enhanced sampling techniques. I first evaluate the convergence of the standard binding free energy for the reversible bilayer insertion of amino acid side-chain analogs and indolicidin. I identify rare and abrupt transitions in bilayer structure resulting from slow reorganization of intermolecular ionic interactions, which constitute hidden sampling barriers that limit the rate of convergence of equilibrium properties and result in systematic sampling errors. Next, I introduce three new generalized ensemble sampling algorithms and show that they dramatically enhance the efficiency of quantifying free energy profiles for solute insertion across a lipid bilayer. I employ one of these methods with a novel analysis tool to accurately predict the amount of additional simulation time required to attain converged estimates of equilibrium properties – something that has never before been accomplished. Finally, I examine the functional hydration of a hydrophobic gate by comparing hundreds of simulations in which the regulatory sites of the CorA magnesium channel are either fully occupied or empty. In the absence of regulatory ions, water penetrates more readily into a 1.5-nm-long channel constriction that is dehydrated in all available crystal structures. These wetting transitions involve more water, and the resulting hydration is more stable, when regulatory ions are absent. Furthermore, this hydration reduces the free energy barrier to the conduction of magnesium. While many of the ensemble-averaged values presented in this thesis have converged, intra-ensemble comparisons indicate incomplete convergence of the constituent simulations. Because my microsecond-scale constituent simulations are long by contemporary standards, I conclude that the difficulty of attaining convergence for bilayer-embedded solutes is drastically underestimated in the literature.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.242
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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