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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 × 10 4 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 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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.390

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 head0.003
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 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

Citations31
Published2002
Admission routes1
Has abstractyes

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