Publications by authors named "T K Antal"

An in silico redesign of the secondary quinone electron acceptor (Q) binding pocket of the D1 protein of Photosystem II (PSII) suggested that mutations of the F265 residue would affect atrazine binding. Chlamydomonas reinhardtii mutants F265T and F265S were produced to obtain atrazine-hypersensitive strains for biosensor applications, and the mutants were indeed found to be more atrazine-sensitive than the reference strain IL. Fluorescence and thermoluminescence data agree with a weak driving force and confirm slow electron transfer but cannot exclude an additional effect on protonation of the secondary quinone.

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Article Synopsis
  • Plastocyanin is a small protein that helps transfer electrons by forming temporary complexes with cytochrome and photosystem 1, making traditional structure determination difficult.
  • Due to its transient nature, researchers have turned to AI, particularly AlphaFold 3, to predict the structures of these short-lived complexes.
  • The study found that the structure predicted by AlphaFold 3 closely matched experimental data from cryo-EM and molecular dynamics, whereas it differed from the orientation suggested by previously available NMR data.
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Extreme mutation rates in microbes and cancer cells can result in error-induced extinction (EEX), where every descendant cell eventually acquires a lethal mutation. In this work, we investigate critical birth-death processes with n distinct types as a birth-death model of EEX in a growing population. Each type-i cell divides independently or mutates at the same rate.

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Neural Cellular Automata (NCA) are a powerful combination of machine learning and mechanistic modelling. We train NCA to learn complex dynamics from time series of images and Partial Differential Equation (PDE) trajectories. Our method is designed to identify underlying local rules that govern large scale dynamic emergent behaviours.

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Stochastic models of sequential mutation acquisition are widely used to quantify cancer and bacterial evolution. Across manifold scenarios, recurrent research questions are: how many cells are there with n alterations, and how long will it take for these cells to appear. For exponentially growing populations, these questions have been tackled only in special cases so far.

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