pith. machine review for the scientific record. sign in

arxiv: 2604.18604 · v1 · submitted 2026-04-09 · ⚛️ physics.bio-ph · quant-ph

Recognition: unknown

Engineering quantum optical responses of microtubules through tryptophan-network simulations and ultraviolet spectroscopy

Authors on Pith no claims yet

Pith reviewed 2026-05-10 16:46 UTC · model grok-4.3

classification ⚛️ physics.bio-ph quant-ph
keywords microtubulestryptophanquantum yieldexcitonic couplingultraviolet spectroscopyfluorescencemolecular dynamicsoptical tuning
0
0 comments X

The pith

Microtubule quantum yield can be tuned by chemically altering its tryptophan network.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper combines molecular-dynamics simulations of microtubule assemblies with an excitonic radiative-coupling model to predict changes in radiative rates and quantum yield from perturbations to the tryptophan sites. Experiments measure absorbance and fluorescence of tubulin dimers and stabilized microtubules, showing that polymerization increases quantum yield at 280 nm while added tryptophan quenches it at both 280 nm and 295 nm. This evidence indicates that the optical properties are chemically addressable, motivating the use of microtubules in engineered photonic applications.

Core claim

Simulations quantify how positional and orientational fluctuations in the tryptophan network reshape radiative rates and quantum yield, predicting that removing a specific site, adding an extra tryptophan, or using mixed fractions modulates emission. Experiments on porcine tubulin and taxol-stabilized microtubules support these trends by demonstrating enhanced quantum yield upon polymerization at 280 nm and quenching by added L-tryptophan at both wavelengths.

What carries the argument

Excitonic radiative-coupling model applied to molecular-dynamics-derived microtubule-like assemblies, which accounts for fluctuations controlling radiative rates and quantum yield.

If this is right

  • Removing or adding tryptophan at specific positions changes the predicted emission properties.
  • Polymerization of tubulin enhances microtubule quantum yield at 280 nm excitation.
  • Addition of L-tryptophan quenches fluorescence at 280 nm and 295 nm.
  • These results provide design rules for chemically tuning microtubule photonics.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Similar chemical tuning strategies could be applied to other aromatic-rich protein assemblies for optical control.
  • Natural cellular processes that modify tryptophan environments might influence microtubule optical behavior in vivo.
  • Testing these modifications in live cells could reveal whether such tuning has biological functions beyond structural roles.

Load-bearing premise

The excitonic radiative-coupling model, populated with molecular-dynamics structures, sufficiently represents the positional and orientational fluctuations that govern radiative rates in real microtubules.

What would settle it

A measurement of microtubule quantum yield after targeted mutation or chemical blocking of a predicted key tryptophan site that shows no modulation as forecasted by the simulations.

read the original abstract

Microtubules host dense ultraviolet-absorbing aromatic networks, suggesting an opportunity to engineer their optical response for biotechnology. Here we assess the feasibility of tuning microtubule fluorescence by combining an excitonic radiative-coupling model with molecular-dynamics-derived microtubule-like assemblies and steady-state absorbance and fluorescence measurements in microplate geometries. Simulations quantify how positional and orientational fluctuations reshape radiative rates and quantum yield, and predict how perturbing the tryptophan network by removing a specific site, adding an extra tryptophan at candidate binding pockets, or using mixed modification fractions can modulate emission. Experiments on porcine tubulin dimers and taxol-stabilized microtubules support these trends: polymerization enhances microtubule quantum yield at 280 nm and yields bounded changes at 295 nm due to scattering, while added L-tryptophan reproducibly quenches microtubules at both wavelengths. Together, theory and experiment provide evidence for chemically addressable tuning of microtubule quantum yield and motivate design rules for engineered microtubule photonics.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

3 major / 2 minor

Summary. The manuscript combines molecular-dynamics-derived microtubule-like assemblies with an excitonic radiative-coupling model to quantify how positional and orientational fluctuations reshape tryptophan-network radiative rates and quantum yields. Simulations predict modulation of emission via specific network perturbations (site removal, pocket addition, or mixed modification fractions). Steady-state UV absorbance and fluorescence experiments on porcine tubulin dimers and taxol-stabilized microtubules are reported to support the trends: polymerization increases quantum yield at 280 nm while added L-tryptophan quenches emission at both 280 and 295 nm. The work concludes that theory and experiment together provide evidence for chemically addressable tuning of microtubule quantum yield and motivate design rules for engineered microtubule photonics.

Significance. If the model correctly captures real fluctuations and the experimental trends confirm the specific predicted modulations, the work would establish a foundation for using chemical edits to the tryptophan network to engineer microtubule optical responses, with potential applications in biotechnology and photonics. The integration of MD-derived structures with an excitonic model is a methodological strength, and the provision of concrete design rules from simulation is valuable if the validation holds.

major comments (3)
  1. [Abstract and experimental results] Abstract and experimental results section: Simulations predict modulation from targeted perturbations (removal of a specific Trp site, addition at candidate pockets, mixed fractions), yet experiments test only polymerization and free L-Trp addition. These do not implement or measure the specific network edits whose effects are simulated, leaving the combined evidence for chemically addressable tuning indirect and one step removed from the claimed design rules.
  2. [Results] Results section: No quantitative error bars, fit statistics, or detailed controls for scattering are provided in the reported quantum-yield values, particularly at 295 nm where scattering is noted to produce bounded changes. This leaves the strength of experimental support for the trends preliminary and weakens the claim that experiments confirm the simulated modulations.
  3. [Model description] Model description: The excitonic radiative-coupling model is parameterized and its outputs are compared directly to experiment; clarification is required on whether key rates or yields are derived independently from the MD assemblies or adjusted to match data, to evaluate the risk that validation is partly circular.
minor comments (2)
  1. [Figures and tables] Add explicit statistical measures (e.g., standard deviations or p-values) to all quantitative fluorescence and quantum-yield data in figures and tables.
  2. [Methods] Clarify the precise definition of 'microtubule-like assemblies' used in the MD simulations and how their structural parameters map to real tubulin lattices.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for the constructive and detailed comments on our manuscript. We address each major comment point by point below and have made revisions to improve clarity, rigor, and the presentation of our results where appropriate.

read point-by-point responses
  1. Referee: [Abstract and experimental results] Abstract and experimental results section: Simulations predict modulation from targeted perturbations (removal of a specific Trp site, addition at candidate pockets, or mixed modification fractions), yet experiments test only polymerization and free L-Trp addition. These do not implement or measure the specific network edits whose effects are simulated, leaving the combined evidence for chemically addressable tuning indirect and one step removed from the claimed design rules.

    Authors: We agree that the experimental perturbations tested (polymerization of tubulin into microtubules and addition of free L-tryptophan) do not directly replicate the specific network edits simulated, such as removal of a particular Trp site or addition at candidate pockets. The experiments instead probe how changes to the tryptophan network environment and introduction of additional tryptophan affect quantum yield, yielding trends that align with the directions predicted by the simulations. We have revised the abstract, results, and discussion sections to more accurately describe the experiments as providing supporting evidence for the feasibility of chemically addressable tuning, rather than direct validation of each individual simulated design rule. This clarification acknowledges the indirect nature of the combined evidence while retaining the value of the simulation-derived design rules. revision: partial

  2. Referee: [Results] Results section: No quantitative error bars, fit statistics, or detailed controls for scattering are provided in the reported quantum-yield values, particularly at 295 nm where scattering is noted to produce bounded changes. This leaves the strength of experimental support for the trends preliminary and weakens the claim that experiments confirm the simulated modulations.

    Authors: The referee is correct that the original manuscript lacked quantitative error bars, fit statistics, and detailed scattering controls for the quantum-yield measurements. We have revised the results and methods sections to incorporate error bars derived from replicate experiments, statistical details on the linear fits used for quantum-yield determination, and expanded controls for scattering at 295 nm. These include concentration-dependent measurements, path-length variations, and comparisons against scattering standards to better bound the scattering contribution. These additions provide a more quantitative and robust basis for the experimental trends. revision: yes

  3. Referee: [Model description] Model description: The excitonic radiative-coupling model is parameterized and its outputs are compared directly to experiment; clarification is required on whether key rates or yields are derived independently from the MD assemblies or adjusted to match data, to evaluate the risk that validation is partly circular.

    Authors: The parameters of the excitonic radiative-coupling model, including transition dipole moments, site energies, and coupling terms, are computed independently from the MD-derived microtubule-like assemblies using standard quantum-chemical methods for tryptophan without any post-hoc adjustment to match experimental data. The resulting radiative rates and quantum yields are calculated from these MD-based inputs and subsequently compared to the experimental measurements. We have added a dedicated paragraph in the model description section, along with a supplementary table listing all key parameters and their independent sources, to make this independence explicit and address any concern about circular validation. revision: yes

Circularity Check

0 steps flagged

No circularity: simulations and experiments remain independent.

full rationale

The derivation proceeds from MD-generated microtubule-like assemblies fed into an excitonic radiative-coupling model to compute radiative rates and quantum yields for both unperturbed and perturbed Trp networks. These are theoretical outputs. Separate steady-state absorbance/fluorescence measurements on porcine tubulin and taxol-stabilized microtubules test only polymerization and free L-Trp addition, which the paper states support general trends but do not implement the specific site-removal or pocket-addition edits. No equations, parameters, or self-citations are shown to make the simulated predictions equivalent to the experimental inputs by construction. The two strands are therefore additive rather than self-referential.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Based solely on the abstract; no explicit free parameters, axioms, or invented entities are stated.

pith-pipeline@v0.9.0 · 5457 in / 1104 out tokens · 63751 ms · 2026-05-10T16:46:06.702069+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

35 extracted references · 26 canonical work pages

  1. [1]

    Desai, T

    A. Desai, T. J. Mitchison, Microtubule polymerization dynamics.Annual Review of Cell and Developmental Biology13(1), 83–117 (1997), doi:10.1146/annurev.cellbio.13.1.83

  2. [2]

    Akhmanova, M

    A. Akhmanova, M. O. Steinmetz, Control of microtubule organization and dynamics: two ends in the limelight.Nature Reviews Molecular Cell Biology16(12), 711–726 (2015), doi: 10.1038/nrm4084

  3. [3]

    M. T. Kelliher, H. A. J. Saunders, J. Wildonger, Microtubule control of functional architecture in neurons.Current Opinion in Neurobiology57, 39–45 (2019), doi:10.1016/j.conb.2019.01.003

  4. [4]

    Guedes-Dias, E

    P. Guedes-Dias, E. L. F. Holzbaur, Axonal transport: Driving synaptic function.Science 366(6462), eaaw9997 (2019), doi:10.1126/science.aaw9997

  5. [5]

    M. K. Iwanski, L. C. Kapitein, Cellular cartography: Towards an atlas of the neuronal mi- crotubule cytoskeleton.Frontiers in Cell and Developmental Biology11, 1052245 (2023), doi:10.3389/fcell.2023.1052245

  6. [6]

    S. F. van Beuningen, C. C. Hoogenraad, Neuronal polarity: remodeling microtubule organiza- tion.Current Opinion in Neurobiology39, 1–7 (2016), doi:10.1016/j.conb.2016.02.011

  7. [7]

    Nogales, S

    E. Nogales, S. G. Wolf, K. H. Downing, Erratum: Structure of the𝛼𝛽tubulin dimer by electron crystallography.Nature393(6681), 191–191 (1998), doi:10.1038/34465

  8. [8]

    Akter,et al., Localized Control of the Swarming of Kinesin-Driven Microtubules Using Light.ACS omega9(36), 37748–37753 (2024)

    M. Akter,et al., Localized Control of the Swarming of Kinesin-Driven Microtubules Using Light.ACS omega9(36), 37748–37753 (2024)

  9. [9]

    K. A. Steinbrink, S. Tripathy, Y. Aboelkassem, Biological nanomachines: Controlling kinesin- microtubule interaction in a microchannel using electric field.Biophysical Journal123(3), 127a (2024)

  10. [10]

    Ishii,et al., Kinesin motors driven microtubule swarming triggered by UV light.Polymer Journal54(12), 1501–1507 (2022)

    S. Ishii,et al., Kinesin motors driven microtubule swarming triggered by UV light.Polymer Journal54(12), 1501–1507 (2022). 26

  11. [11]

    G. D. Bachand, E. D. Spoerke, M. J. Stevens, Microtubule-based nanomaterials: Exploiting nature’s dynamic biopolymers.Biotechnology and Bioengineering112(6), 1065–1073 (2015)

  12. [12]

    J. L. Malcos, W. O. Hancock, Engineering tubulin: microtubule functionalization approaches for nanoscale device applications.Applied Microbiology and Biotechnology90(1), 1–10 (2011)

  13. [13]

    T. J. A. Craddock, D. Friesen, J. Mane, S. Hameroff, J. A. Tuszynski, The feasibility of coherent energy transfer in microtubules.Journal of the Royal Society Interface11(100), 20140677 (2014), doi:10.1098/rsif.2014.0677

  14. [14]

    Przybylska, A

    G. Celardo, M. Angeli, T. Craddock, P. Kurian, On the existence of superradiant excitonic states in microtubules.New Journal of Physics21(2), 023005 (2019), doi:10.1088/1367-2630/ aaf839

  15. [15]

    Kurian, T

    P. Kurian, T. Obisesan, T. J. Craddock, Oxidative species-induced excitonic transport in tubulin aromatic networks: Potential implications for neurodegenerative disease.Journal of Photo- chemistry and Photobiology B: Biology175, 109–124 (2017), doi:10.1016/j.jphotobiol.2017. 08.033

  16. [16]

    A. P. Kalra,et al., Electronic energy migration in microtubules.ACS Central Science9(3), 352–361 (2023), doi:10.1021/acscentsci.2c01114

  17. [17]

    Babcock,et al., Ultraviolet superradiance from mega-networks of tryptophan in biological architectures.The Journal of Physical Chemistry B(2024), doi:10.1021/acs.jpcb.3c07936

    N. Babcock,et al., Ultraviolet superradiance from mega-networks of tryptophan in biological architectures.The Journal of Physical Chemistry B(2024), doi:10.1021/acs.jpcb.3c07936

  18. [18]

    Patwa, N

    H. Patwa, N. S. Babcock, P. Kurian, Quantum-enhanced photoprotection in neuroprotein ar- chitectures emerges from collective light-matter interactions.Frontiers in Physics12, 1387271 (2024), doi:10.3389/fphy.2024.1387271

  19. [19]

    Reiter, F

    S. Reiter, F. L. Kiss, J. Hauer, R. de Vivie-Riedle, Thermal site energy fluctuations in photo- system I: new insights from MD/QM/MM calculations.Chemical Science14(12), 3117–3131 (2023), doi:10.1039/d2sc06160k. 27

  20. [20]

    L. Marchese,et al., The uptake and metabolism of amino acids, and their unique role in the biology of pathogenic trypanosomatids.Pathogens7(2), 36 (2018), doi:10.3390/ pathogens7020036

  21. [21]

    J. R. Lakowicz,Principles of Fluorescence Spectroscopy(Springer, New York), 3 ed. (2006), doi:10.1007/978-0-387-46312-4

  22. [22]

    R. H. Dicke, Coherence in Spontaneous Radiation Processes.Physical Review93(1), 99–110 (1954), doi:10.1103/PhysRev.93.99

  23. [23]

    P. R. Callis, [7] 1La and 1Lb transitions of tryptophan: Applications of theory and experimental observations to fluorescence of proteins.Methods in enzymology278, 113–150 (1997), doi: 10.1016/S0076-6879(97)78009-1

  24. [24]

    Waterhouse,et al., SWISS-MODEL: homology modelling of protein structures and com- plexes.Nucleic Acids Research46(W1), W296–W303 (2018), doi:10.1093/nar/gky427

    A. Waterhouse,et al., SWISS-MODEL: homology modelling of protein structures and com- plexes.Nucleic Acids Research46(W1), W296–W303 (2018), doi:10.1093/nar/gky427

  25. [25]

    Anandakrishnan, B

    R. Anandakrishnan, B. Aguilar, A. V. Onufriev, H++ 3.0: automating pK prediction and the preparation of biomolecular structures for atomistic molecular modeling and simulations. Nucleic Acids Research40(W1), W537–W541 (2012), doi:10.1093/nar/gks375

  26. [26]

    M. H. M. Olsson, C. R. Søndergaard, M. Rostkowski, J. H. Jensen, PROPKA3: Consistent Treatment of Internal and Surface Residues in Empirical pKa Predictions.Journal of Chemical Theory and Computation7(2), 525–537 (2011), doi:10.1021/ct100578z

  27. [27]

    D. A. Case,et al., The Amber biomolecular simulation programs.Journal of Computational Chemistry26(16), 1668–1688 (2005), doi:10.1002/jcc.20290

  28. [28]

    J. A. Maier,et al., ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB.Journal of Chemical Theory and Computation11(8), 3696–3713 (2015), doi:10.1021/acs.jctc.5b00255

  29. [29]

    D. R. Roe, T. E. Cheatham, PTRAJ and CPPTRAJ: Software for Processing and Analysis of Molecular Dynamics Trajectory Data.Journal of Chemical Theory and Computation9(7), 3084–3095 (2013), doi:10.1021/ct400341p. 28

  30. [30]

    S. A. Yousefzadeh, M. Jarah, G. H. Riazi, Tryptophan improves memory independent of its role as a serotonin precursor: potential involvement of microtubule proteins.Journal of Molecular Neuroscience70, 559–567 (2020), doi:10.1007/s12031-019-01457-y

  31. [31]

    W. L. DeLano, PyMOL: An Open-Source Molecular Graphics Tool.CCP4 Newsletter on Protein Crystallography40, 82–92 (2002)

  32. [32]

    Gaskin, C

    F. Gaskin, C. R. Cantor, M. L. Shelanski, Turbidimetric studies of the in vitro assembly and disassembly of porcine neurotubules.Journal of Molecular Biology89(4), 737–755 (1974), doi:10.1016/0022-2836(74)90048-5

  33. [33]

    C. F. Bohren, D. R. Huffman,Absorption and Scattering of Light by Small Particles(Wiley, New York) (1983)

  34. [34]

    H. C. van de Hulst,Light Scattering by Small Particles(Wiley, New York) (1957), reprinted by Dover (ISBN 9780486642284)

  35. [35]

    Baseline

    G. L. Schuster, O. Dubovik, B. N. Holben, Angstrom exponent and bimodal aerosol size distributions.Journal of Geophysical Research: Atmospheres111(D7), D07207 (2006), doi: 10.1029/2005JD006328. Supplementary materials Supplementary Text Fig. S1 Tables S1 to S10 Data S1 Code S1 29 Supplementary Materials for Engineering quantum optical responses of microtu...