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Record W1968512735 · doi:10.1139/v01-199

2000 John C. Polanyi Award LectureMother Nature and the molecular Big Bang

2002· article· en· W1968512735 on OpenAlexvenueno aff
RJ Dwayne Miller

Bibliographic record

VenueCanadian Journal of Chemistry · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Structure and Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Degrees of freedom (physics and chemistry)ChemistryMaxima and minimaDissipative systemMesoscopic physicsStatistical physicsChemical physicsBiomoleculeRelaxation (psychology)Biological systemComputational chemistryPhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

Biological molecules are mesoscopic systems that bridge the quantum and classical worlds. At the single molecule level, there are often more than 1 × 104 degrees of freedom that are involved in protein-mediated processes. These molecules are sufficiently large that the bath coordinate convolved to the reaction at an active site is defined by the surrounding protein tertiary structure. In this context, the very interatomic forces that determine the active protein structures create a strongly associated system. Thus, the bath fluctuations leading to reactive crossings involve highly hindered motions within a myriad of local minima that would act to cast the reaction dynamics into the high viscosity limit appropriate to glasses. However, the time scales observed for biological events are orders of magnitude too fast to meet this anticipated categorization. In this context, the apparent deterministic nature of biological processes represents an enormous challenge to our understanding of chemical processes. Somehow Nature has discovered a molecular scaffolding that enables minute amounts of energy to be efficiently channeled to perform biological functions without becoming entrapped in local minima. Clearly, energy derived from chemical processes is highly directed in biological systems. To understand this problem, we must first understand how energy is redistributed among the different degrees of freedom and fully characterize the protein relaxation processes along representative reaction coordinates in relation to these dissipative processes. This paper discusses the development of new nonlinear spectroscopic methods that have enabled interferometric sensitivity to protein motions on femtosecond time scales appropriate to the very fastest motions (i.e., bond breaking or the molecular "Big Bang") out to the slowest relaxation steps. This work has led to the Collective Mode Coupling Model as an explanation of the required reduced dimensionality in biological systems. Within this model, the largest coupling coefficients of the reaction coordinate are to the damped inertial collective modes of the protein defined by the strongly correlated secondary structures. These modes act to guide the reaction along the correct seam(s) in an otherwise highly complex potential energy surface. The mechanism by which biological molecules have been able to harness chemical energy over meso-length scales represents the first step towards higher levels of organization. The new insight afforded by the collective mode mechanism may prove important in understanding this larger issue of scaling in biological systems.Key words: biodynamics, energy transduction, ultrafast spectroscopy, nonlinear spectroscopy, primary processes in biology.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.244
Threshold uncertainty score0.815

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.2440.138

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 head0.003
GPT teacher head0.177
Teacher spread0.174 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations31
Published2002
Admission routes1
Has abstractyes

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Same venueCanadian Journal of ChemistrySame topicProtein Structure and DynamicsFrench-language works237,207