Experimental detection of long-distance interactions between biomolecules through collective spectral properties of oscillating electric dipoles: a numerical study

3 CPT - E7 Systèmes dynamiques : théories et applications
CPT - Centre de Physique Théorique - UMR 7332
Abstract : The present work reports about the dynamics of a collection of randomly distributed, and randomly oriented, oscillators in 3D space, coupled by an interaction potential falling as $1/r^3$, where r stands for the inter-particle distance. This model schematically represents a collection of identical biomolecules, coherently vibrating at some common frequency, coupled with a $1/r^3$ potential stemming from the electrodynamic interaction between oscillating dipoles. The oscillating dipole moment of each molecule being a direct consequence of its coherent (collective) vibration. By changing the average distance among the molecules, neat and substantial changes in the power spectrum of the time variation of a collective observable are found. As the average intermolecular distance can be varied by changing the concentration of the solvated molecules, and as the collective variable investigated is proportional to the projection of the total dipole moment of the model biomolecules on a coordinate plane, we have found a prospective experimental strategy of spectroscopic kind to check whether the mentioned intermolecular electrodynamic interactions can be strong enough to be detectable, and thus to be of possible relevance to biology.
Type de document :
Pré-publication, Document de travail
22 pages, 5 figures. 2018
Domaine :

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https://hal.archives-ouvertes.fr/hal-01776531
Contributeur : Matteo Gori <>
Soumis le : mardi 24 avril 2018 - 16:02:27
Dernière modification le : jeudi 10 mai 2018 - 02:13:59

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• HAL Id : hal-01776531, version 1
• ARXIV : 1711.07547

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Simona Olmi, Matteo Gori, Irene Donato, Marco Pettini. Experimental detection of long-distance interactions between biomolecules through collective spectral properties of oscillating electric dipoles: a numerical study. 22 pages, 5 figures. 2018. 〈hal-01776531〉

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