On the comparison of models and experiments in the study of DNA open states: the problem of degrees of freedom

TL;DR

This paper examines the importance of correctly matching experimental data with mechanical DNA models, highlighting errors caused by mismatched open state types and threshold coordinates, and proposes a solution to improve model accuracy.

Contribution

It introduces the concept of an effective total threshold coordinate for DNA strand separation, improving the interpretation of experimental data in mechanical models.

Findings

Correct interpretation of experimental data can eliminate discrepancies with theory.

Mismatch in open state types leads to critical errors in modeling.

Introducing an effective threshold coordinate improves model-experiment consistency.

Abstract

Simple mechanical models of DNA play an important role in studying the dynamics of its open states. The main requirement when developing a DNA model is the correct selection of its effective potentials and parameters based on experimental data. At the same time, various experiments allow us to "see" different types of DNA open states. Consideration of this feature is one of the most important conditions in the development, optimization, and parameterization of any mechanical model. Violation of this condition, i.e., the comparison of incomparable characteristics, leads to critical errors. The present investigation is devoted to the problem of degrees of freedom of DNA bases taken into account in mechanical models. Using the Peyrard-Bishop-Dauxois model as an example, two types of errors in interpreting experimental data when compared with the model are examined. The first one is a mismatch between the open state types in the model and experiment. The second one is an incorrect specification of the "threshold coordinate" of the open state. The concept of the effective total threshold coordinate of the radial separation of DNA strands for registration of opening is introduced. It is shown that correct interpretation of experimental data can actually eliminate discrepancies with theory.