Enhancing the Inhomogeneous Photodynamics of Canonical Bacteriophytochrome

Deciphering Photoreceptors Through Atomistic Modeling from Light Absorption to Conformational Response

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.

Reweighted Manifold Learning of Collective Variables from Enhanced Sampling Simulations

Enhanced sampling methods are indispensable in computational chemistry and physics, where atomistic simulations cannot exhaustively sample the high-dimensional configuration space of dynamical systems due to the sampling problem. A class of such enhanced sampling methods works by identifying a few slow degrees of freedom, termed collective variables (CVs), and enhancing the sampling along these CVs. Selecting CVs to analyze and drive the sampling is not trivial and often relies on chemical intuition. Despite routinely circumventing this issue using manifold learning to estimate CVs directly from standard simulations, such methods cannot provide mappings to a low-dimensional manifold from enhanced sampling simulations, as the geometry and density of the learned manifold are biased. Here, we address this crucial issue and provide a general reweighting framework based on anisotropic diffusion maps for manifold learning that takes into account that the learning data set is sampled from a biased probability distribution. We consider manifold learning methods based on constructing a Markov chain describing transition probabilities between high-dimensional samples. We show that our framework reverts the biasing effect, yielding CVs that correctly describe the equilibrium density. This advancement enables the construction of low-dimensional CVs using manifold learning directly from the data generated by enhanced sampling simulations. We call our framework reweighted manifold learning. We show that it can be used in many manifold learning techniques on data from both standard and enhanced sampling simulations.

Protein control of photochemistry and transient intermediates in phytochromes

Phytochromes are ubiquitous photoreceptors responsible for sensing light in plants, fungi and bacteria. Their photoactivation is initiated by the photoisomerization of the embedded chromophore, triggering large conformational changes in the protein. Despite numerous experimental and computational studies, the role of chromophore-protein interactions in controlling the mechanism and timescale of the process remains elusive. Here, we combine nonadiabatic surface hopping trajectories and adiabatic molecular dynamics simulations to reveal the molecular details of such control for the Deinococcus radiodurans bacteriophytochrome. Our simulations reveal that chromophore photoisomerization proceeds through a hula-twist mechanism whose kinetics is mainly determined by the hydrogen bond of the chromophore with a close-by histidine. The resulting photoproduct relaxes to an early intermediate stabilized by a tyrosine, and finally evolves into a late intermediate, featuring a more disordered binding pocket and a weakening of the aspartate-to-arginine salt-bridge interaction, whose cleavage is essential to interconvert the phytochrome to the active state.