Studying Protein kinases PKCζ and PKMζ with the Resonant Recognition Model. Implications for the study of Memory Mechanisms

Authors

  • Dra. Suria Valdés García Facultad "Diez de Octubre", Universidad de Ciencias Médicas de La Habana
  • DrC. José Luis Hernández Cáceres Facultad de Ciencias Médicas "Diez de Octubre"

Abstract

PKMζ is a brain-specific protein kinase that has been suggested as playing a key role in memory consolidation mechanisms. It is identical to catalytic portion of another protein kinase, PKCζ. Lacking the regulatory end, PKMζ is several times more active than PKCζ. However, knowledge about PKMζ mechanisms in memory consolidation is patchy, and sometimes contradictory. The resonant recognition model (RRM) might shed some light in understanding PKMζ role on memory consolidation. This is the first attempt in literature to apply the RRM to the study of PKMζ and PKCζ. We obtained that PKMζ presents a spectral peak at the resonant recognition frequency of fRRM= 0.063 (likely, corresponding to the infrared frequency of 3190 nm) and another peak at fRRM =0.211(950 nm in the near infrared). Peak at fRRM= 0.063 is also shared by PKCζ, and the peak at fRRM =0.211 is similar to the one recently reported in literature for regulatory proteins. We hypothesize that irradiating with a weak light infrared source at these frequencies would modify long term potentiation results. Finally, a scheme for resonant interactions in PKMζ and PKCζ is proposed.

Palabras claves: long term potentiation, protein kinases, resonant recognition model, bioinformatics.

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Author Biographies

Dra. Suria Valdés García, Facultad "Diez de Octubre", Universidad de Ciencias Médicas de La Habana

Dra en Ciencias Biológicas

DrC. José Luis Hernández Cáceres, Facultad de Ciencias Médicas "Diez de Octubre"

Doctor en Ciencias Biológicas

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Published

2017-10-20

How to Cite

1.
Valdés García DS, Hernández Cáceres DJL. Studying Protein kinases PKCζ and PKMζ with the Resonant Recognition Model. Implications for the study of Memory Mechanisms. RCIM [Internet]. 2017 Oct. 20 [cited 2025 Jul. 7];9(2). Available from: https://revinformatica.sld.cu/index.php/rcim/article/view/216

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