In this review, we discuss the successes and challenges of the atomistic modeling of photoreceptors. Throughout our presentation, we integrate explanations of the primary methodological approaches, ranging from quantum mechanical descriptions to classical enhanced sampling methods, all while providing illustrative examples of their practical application to specific systems. To enhance the effectiveness of our analysis, our primary focus has been directed towards the examination of applications across three distinct photoreceptors. These include an example of Blue Light-Using Flavin (BLUF) domains, a bacteriophytochrome, and the orange carotenoid protein (OCP) employed by cyanobacteria for photoprotection. Particular emphasis will be placed on the pivotal role played by the protein matrix in fine-tuning the initial photochemical event within the embedded chromophore. Furthermore, we will investigate how this localized perturbation initiates a cascade of events propagating from the binding pocket throughout the entire protein structure, thanks to the intricate network of interactions between the chromophore and the protein.
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http://dx.doi.org/10.1016/j.jmb.2023.168358 | DOI Listing |
Comput Struct Biotechnol J
December 2024
NovaMechanics Ltd, Nicosia 1070, Cyprus.
The CompSafeNano project, a Research and Innovation Staff Exchange (RISE) project funded under the European Union's Horizon 2020 program, aims to advance the safety and innovation potential of nanomaterials (NMs) by integrating cutting-edge nanoinformatics, computational modelling, and predictive toxicology to enable design of safer NMs at the earliest stage of materials development. The project leverages Safe-by-Design (SbD) principles to ensure the development of inherently safer NMs, enhancing both regulatory compliance and international collaboration. By building on established nanoinformatics frameworks, such as those developed in the H2020-funded projects NanoSolveIT and NanoCommons, CompSafeNano addresses critical challenges in nanosafety through development and integration of innovative methodologies, including advanced models, approaches including machine learning (ML) and artificial intelligence (AI)-driven predictive models and 1st-principles computational modelling of NMs properties, interactions and effects on living systems.
View Article and Find Full Text PDFNPJ Comput Mater
January 2025
Computational Atomic-scale Materials Design (CAMD), Department of Physics, Technical University of Denmark, Kgs. Lyngby, Denmark.
We conduct a systematic investigation of the role of Hubbard U corrections in electronic structure calculations of two-dimensional (2D) materials containing 3 transition metals. Specifically, we use density functional theory (DFT) with the PBE and PBE+U approximations to calculate the crystal structure, band gaps, and magnetic parameters of 638 monolayers. Based on a comprehensive comparison to experiments we first establish that the inclusion of the U correction worsens the accuracy for the lattice constants.
View Article and Find Full Text PDFJ Phys Chem B
January 2025
Engineering Research Center of Membrane and Water Treatment of MOE, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, P. R. China.
Polyamide (PA) membranes are widely utilized in desalination and water treatment applications, yet the mechanisms underlying water transport within these amorphous polymer materials remain insufficiently understood. To gain more insight into these problems on a microscopic scale, we employ molecular dynamics (MD) simulations to analyze the relationship between the structural properties and the water permeation behavior of PA membranes. Two distinct atomistic models of PA membranes are developed by controlling their degrees of cross-linking (DC).
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
Department of Chemistry, Faculty of Science, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada.
Tau is a microtubule (MT)-associated protein that binds to and stabilizes the MTs of neurons. Due to its intrinsically disordered nature, it undergoes several post-translational modifications (PTMs) that are intricately linked to both the physiological and pathophysiological roles of Tau. Prior research has shown phosphorylation and O-GlcNAcylation to have contrasting effects on Tau aggregation; however, the precise molecular mechanisms and potential synergistic effects of these modifications remain elusive.
View Article and Find Full Text PDFProteins drive biochemical transformations by transitioning through distinct conformational states. Understanding these states is essential for modulating protein function. Although X-ray crystallography has enabled revolutionary advances in protein structure prediction by machine learning, this connection was made at the level of atomic models, not the underlying data.
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