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Record W6912924879 · doi:10.5281/zenodo.8055067

Investigating the Aryl Hydrocarbon Receptor Agonist/Antagonist Conformational Switch using Well-Tempered Metadynamics Simulations input and output files

2023· article· en· W6912924879 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Structure and Dynamics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMetadynamicsMolecular dynamicsTopology (electrical circuits)Coordinate systemArylMicrosecond

Abstract

fetched live from OpenAlex

The MD simulation data for the research article: - Investigating the Aryl Hydrocarbon Receptor Agonist/Antagonist Conformational Switch using Well-Tempered Metadynamics Simulations Standard_md_files-GAFF.zip: The Standard_md folder comprises the initial conformations and prepared system files for both apo proteins and ligand-protein complexes. It also includes all topology files and coordinate files (.prmtop & .rst7) required for each system. Amber_md_input.zip: The Amber_input folder encompasses a comprehensive set of input files for the Amber to run molecular dynamics (MD) simulations. This includes the following stages: minimization (min_fix.in), heating (heat_fix.in), equilibration (equ1.in to equ5.in), and production (MD1.in to MD20.in) simulations, allowing for up to 1000 ns of MD simulations for both apo proteins and ligand-protein complexes. The package also contains the MD job run script and tleap script for preparing solvated system. Gromac_plumed_input.zip: The Gromac_plumed_input package provides a suite of input files specifically designed for Gromacs simulations coupled with Plumed. It includes essential input files for various steps, such as minimization(minimization.mdp), NVT (constant number of particles, volume, and temperature) equilibration, NPT (constant number of particles, pressure, and temperature) equilibration (equilibration.mdp &equilibration_2.mdp), and production simulations (dynamic.mdp), extending up to 600 ns. Each step has the corresponding tpr file, while the Plumed simulations utilize the plumed.dat file as the input for conducting well-tempered metadynamics (WTE-metad) simulations to 1 microsecond. Also, it contains gromacs topology and coordinate files (.gro & .top) for each system. GAFF2_input.zip: The GAFF2_input file contains the initial conformations and prepared system files for both ligand-protein complexes after ligands are parametrized via GAFF2. It also includes all topology files and coordinate files (.prmtop & .rst7) required for each system. CGenFF_input.zip: CGenFF_input folder encompasses the initial conformations and prepared system files for both ligand-protein complexes after ligands are parametrized via CGenFF. It also includes all topology files and coordinate files (.top & .gro) required for each system and files need to run the simulations. GROMACS input parameters.zip: It has input files to run minimization(minimization.mdp), NVT (constant number of particles, volume, and temperature) equilibration, NPT (constant number of particles, pressure, and temperature) equilibration (equilibration.mdp &equilibration_2.mdp), and production simulations (dynamic.mdp), extending up to 1000 ns.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.175
Threshold uncertainty score0.584

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1750.030

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 head0.027
GPT teacher head0.251
Teacher spread0.224 · 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
Published2023
Admission routes1
Has abstractyes

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