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Record W2094754077 · doi:10.1063/1.2213980

A theoretical analysis on hydration thermodynamics of proteins

2006· article· en· W2094754077 on OpenAlexaff
Takashi Imai, Yuichi Harano, Masahiro Kinoshita, Andriy Kovalenko, Fumio Hirata

Bibliographic record

VenueThe Journal of Chemical Physics · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsNational Institute for NanotechnologyUniversity of Alberta
FundersJapan Society for the Promotion of Science
KeywordsSolvationThermodynamicsIsochoric processChemistryEntropy (arrow of time)MoleculeInteraction energyChemical physicsPhysics

Abstract

fetched live from OpenAlex

The hydration free energy (HFE) of several proteins modeled using the all-atom force field is calculated by employing the three-dimensional reference interaction site model theory, a recently developed integral equation theory of molecular solvation. The HFE is decomposed into the energetic and entropic components under the isochoric condition. The former comprises the protein-water interaction energy and the water reorganization energy arising from the structural changes induced in water. Each component is further decomposed into the nonelectrostatic and electrostatic contributions. It is found that the HFE is governed by the nonelectrostatic hydration entropy and the electrostatic hydration energy. The nonelectrostatic hydration entropy is almost exclusively ascribed to the translational entropy loss of water upon the protein insertion. It asymptotically becomes proportional to the excluded volume (EV) for water molecules as the protein size increases. The hydration energy is determined by the protein-water interaction energy which is half compensated by the water reorganization energy. These energy terms are approximately proportional to the water-accessible surface area (ASA). The energetic and entropic contributions are balanced with each other and the HFE has no apparent linear relation with the EV and ASA.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.260

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.233
Teacher spread0.228 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations153
Published2006
Admission routes1
Has abstractyes

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