Daily Digest | February 24, 2023

De novo design of luciferases using deep learning | Nature

De novo enzyme design has sought to introduce active sites and substrate-binding pockets that are predicted to catalyse a reaction of interest into geometrically compatible native scaffolds, but has been limited by a lack of suitable protein structures and the complexity of native protein sequence–structure relationships. Here researchers describe a deep-learning-based ‘family-wide hallucination’ approach that generates large numbers of idealized protein structures containing diverse pocket shapes and designed sequences that encode them. They use these scaffolds to design artificial luciferases that selectively catalyse the oxidative chemiluminescence of the synthetic luciferin substrates diphenylterazine and 2-deoxycoelenterazine.

Research paper

 

ComMap: A software to perform large-scale structure-based mapping for cross-linking mass spectrometry | Bioinformatics

Chemical cross-linking combined with mass spectrometry (CXMS) is now a well-established method for profiling existing protein-protein interactions (PPIs) with partially known structures. ComMap (protein complex structure mapping) is a software designed to perform large-scale structure-based mapping by integrating CXMS data with existing structures. It allows complete the distance calculation of PPIs with existing structures in batch within minutes and provides scores for different PPI-structure pairs of testable hypothetical structural dynamism via a global view.

Research paper

 

Sex-dimorphic and age-dependent organization of 24-hour gene expression rhythms in humans | Science

Rhythmic circadian changes in gene expression have been well documented in model organisms, but data are limited from primates and particularly humans. Researchers developed an algorithm that allowed them to assign a circadian phase to each individual in a set of about 900 human donors. This approach allowed them to detect circadian changes in gene expression in samples from 46 tissues. Women showed higher rhythmicity of transcripts, especially in liver and the adrenal gland. The results also confirmed that rhythmicity was generally damped in older individuals.

Research paper

 

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