title: Multiscale Theories and Methods for Describing Biological Clocks and Nonequilibrium Protein Dynamics
Creators: name: Rojas, Pedro Pablo
Publisher: name: KOBRA Universität Kassel
Year: 2025
Subjects: subject: biological clocks
subject: reservoir computing
subject: metastable proteins
subject: wavelet transform
subject: molecular dynamics
subject: protein dynamics
subject: reaction diffusion systems
classificationCode: 530
subject: 530
classificationCode: Biologische Uhr
subject: Biologische Uhr
classificationCode: Maschinelles Lernen
subject: Maschinelles Lernen
classificationCode: Wavelet-Transformation
subject: Wavelet-Transformation

description: <p>Life is intricately organized in both space and time across multiple scales. Complex organisms, such as animals, have evolved to predict and capitalize on periodic environmental changes. To accomplish this task, they employ elaborate and yet not fully understood mechanisms that coordinate diverse spatial and temporal scales, in order to ensure the maintenance of operational ranges in physiological variables.</p>
<p>The circadian clock, the driving force behind daily rhythms in physiology and behaviour, emerges from an complex array of processes occurring across various scales. This array of processes includes proteins cycling with a $\sim$24 hour period, neurons that exhibit both electrical coupling within milliseconds and chemical coupling over longer time scales, as well as networks of neurons displaying multiple intermediate rhythms.</p>
<p>This present thesis delves into theories and methods aimed at elucidating aspects of the multiscale dynamics and organization within the circadian clock and non-equilibrium proteins.</p>
<p>We first addressed the challenge of analysing experimental electrophysiology recordings to uncover aspects of the internal network organization of the circadian clock. We developed methods rooted on the wavelet transform for detecting and analysing events in multiple scales, along with their timing patterns. We tested the methods on experimental long term recordings, which yielded the time description of the activity and a collection of dynamical types that can serve for future modelling. Moreover, we present a method for inferring dynamical networks in multivariate time series data. In this method, the time series is projected into a high dimensional recurrent neural network termed the subReservoir Computer. This process generate embeddings of the dynamical system and encodes the original connections in the output layer. </p>
<p>We then addressed problems concerning generation, synchronization and entrainment of oscillations in the circadian clock at both the intracellular and extracellular network scales. Our developed model generalizes existing biochemical models, incorporating intracellular diffusion and the spatial distribution of transcription and translation sites. This modification proves that intracellular negative feedback loops can initiate oscillations when the sources of the molecules are spatially separated.In addition, we propose a model for the synchronization and entrainment of circadian oscillators, that demonstrates that entrainment achieved through plasticity-like adaptation involving two distinct time scales yields improves entrainment properties.</p>
<p>Finally, we investigated the dynamics of the spike protein of the SARS-CoV-2 virus under several electric field intensities. Our findings reveal that the spike protein undergoes irreversible conformational changes at significantly lower intensities than previously observed in other proteins. We attribute this phenomenon to the metastable state of its prefusion conformation. The alterations in secondary and tertiary structures lead to impaired binding with the ACE2 receptor, thereby opening new avenues for research in the realm of nonequilibrium dynamics of metastable proteins.</p>