Sorgenfrei, F. A. | Search bioRxiv

bioRxiv2020

Optimal time frequency analysis for biological data - pyBOAT

Methods for the quantification of rhythmic biological signals have been essential for the discovery of function and design of biological oscillators. Advances in live measurements have allowed recordings of unprecedented resolution revealing a new world of complex heterogeneous oscillations with multiple noisy non-stationary features. However, our understanding of the underlying mechanisms regulating these oscillations has been lagging behind, partially due to the lack of simple tools to reliably quantify these complex non-stationary features. With this challenge in mind, we have developed pyBOAT, a Python-based fully automatic stand-alone software that integrates multiple steps of non-stationary oscillatory time series analysis into an easy-to-use graphical user interface. pyBOAT implements continuous wavelet analysis which is specifically designed to reveal time-dependent features. In this work we illustrate the advantages of our tool by analyzing complex non-stationary time-series profiles. Our approach integrates data-visualization, optimized sinc-filter detrending, amplitude envelope removal and a subsequent continuous-wavelet based time-frequency analysis. Finally, using analytical considerations and numerical simulations we discuss unexpected pitfalls in commonly used smoothing and detrending operations.

systems biology↗

bioRxiv2020

Evolution of an interaction between disordered proteins resulted in increased heterogeneity of the binding transition state

Intrinsically disordered protein (IDP) domains often have multiple binding partners. Little is known regarding molecular changes in the binding mechanism when a new interaction evolves from low to high affinity. Here we compared the degree of native contacts in the transition state of the interaction of two IDP domains, low-affinity ancestral and high-affinity human NCBD and CID. We found that the coupled binding and folding mechanism of the domains is overall similar, but with a higher degree of native hydrophobic contact formation in the transition state of the ancestral complex while more heterogenous transient interactions, including electrostatic, and an increased disorder characterize the human complex. From an evolutionary perspective, adaptation to new binding partners for IDPs may benefit from this ability to exploit multiple alternative transient interactions while retaining the overall pathway.

biophysics↗