Electrodynamic forces driving DNA-protein interactions at large distances

In the present paper we address the general problem of selective electrodynamic interactions between DNA and protein, which is motivated by decades of theoretical study and our very recent experimental findings providing a first evidence for their activation. Inspired by the Davydov and Holstein&#x2212;Fr&#x00F6;hlich models describing electron motion along biomolecules, and using a model Hamiltonian written in second quantization, the time-dependent variational principle is used to derive the dynamical equations of the system. We demonstrate the efficacy of this second-quantized model for a well-documented biochemical system consisting of a restriction enzyme, <i>Eco</i>RI, which binds selectively to a palindromic six-base-pair target within a DNA oligonucleotide sequence to catalyze a DNA double-strand cleavage. The time-domain Fourier spectra of the electron currents numerically computed for the DNA fragment and for the <i>Eco</i>RI enzyme, respectively, exhibit a cross-correlation spectrum with a sharp co-resonance peak. When the target DNA recognition sequence is randomized, this sharp co-resonance peak is replaced with a broad and noisy spectrum. Such a sequence-dependent charge transfer phenomenology is suggestive of a potentially rich variety of selective electrodynamic interactions influencing the coordinated activity of DNA substrates, enzymes, transcription factors, ligands, and other proteins under realistic biochemical conditions characterized by electron&#x2212;phonon excitations.

Institutions

Publication Details

Journal
Frontiers of Physics
Published
2025-01-01
DOI
https://doi.org/10.15302/frontphys.2025.061200
Primary Topic
Magnetic and Electromagnetic Effects
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Electrodynamic forces driving DNA-protein interactions at large distances

Frontiers of Physics
Magnetic and Electromagnetic Effects
article

Electrodynamic forces driving DNA-protein interactions at large distances

article en

Abstract

In the present paper we address the general problem of selective electrodynamic interactions between DNA and protein, which is motivated by decades of theoretical study and our very recent experimental findings providing a first evidence for their activation. Inspired by the Davydov and Holstein&#x2212;Fr&#x00F6;hlich models describing electron motion along biomolecules, and using a model Hamiltonian written in second quantization, the time-dependent variational principle is used to derive the dynamical equations of the system. We demonstrate the efficacy of this second-quantized model for a well-documented biochemical system consisting of a restriction enzyme, <i>Eco</i>RI, which binds selectively to a palindromic six-base-pair target within a DNA oligonucleotide sequence to catalyze a DNA double-strand cleavage. The time-domain Fourier spectra of the electron currents numerically computed for the DNA fragment and for the <i>Eco</i>RI enzyme, respectively, exhibit a cross-correlation spectrum with a sharp co-resonance peak. When the target DNA recognition sequence is randomized, this sharp co-resonance peak is replaced with a broad and noisy spectrum. Such a sequence-dependent charge transfer phenomenology is suggestive of a potentially rich variety of selective electrodynamic interactions influencing the coordinated activity of DNA substrates, enzymes, transcription factors, ligands, and other proteins under realistic biochemical conditions characterized by electron&#x2212;phonon excitations.

Frontiers of PhysicsVol. 20(6)
University of Siena (IT), Università di Camerino (IT), Centre National de la Recherche Scientifique (FR), Université de Toulon (FR), Istituto Nazionale di Fisica Nucleare, Sezione di Firenze (IT), BioMed X Institute (DE), Centre de Physique Théorique (FR), Istituto Nazionale di Fisica Nucleare, Sezione di Perugia (IT)
Openalex Percentile: Top 85%
Magnetic and Electromagnetic Effects
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.