Biomolecular Systems Research Articles

Granger causality based on vector time series and quaternion algebra with possible applications to molecular dynamics data analysis.

Causal analysis plays a significant role in physics, chemistry, and biology. Dynamics of complex (bio)molecular and nanosystems, from the microscopic to the macroscopic scale, are characterized by time-dependent vectors such as positions, forces, momenta, angular momenta, or torques. Identification and analysis of causal relationships between these time-dependent signals is an important problem in the multidimensional time-series analysis and is of great practical importance in describing the properties of such dynamical systems, and to understanding their functionality. For linear stochastic systems characterized by multidimensional scalar signals, Granger proposed a simple procedure to detect causal relationships, called Granger causality. In this study we extended this formalism to vector signals representing physical vector quantities. For this purpose, we used quaternion algebra, where vector signals are treated as time-dependent quaternions. The developed analytical model is based on the autoregressive formalism. This formalism (Q-MVAR) and its numerical implementation were validated using two simple dynamic models: a rigid body model represented by a benzenelike molecular fragment, interacting with a short-range harmonic potential with a wall, as well as a system of three model atomic balls moving inside a soft spherical surface and interacting with long range electrostatic forces. Although the motivation to these studies was the analysis of classical motions in complex (bio)molecular systems, described with a mechanical model and based on molecular dynamics (MD) simulations, in particular coarse-grained ones, it should be noted that the developed extended formalism can be applied to any system composed of many rigid elements that interact with arbitrary potentials and are characterized by complex internal motions. A description of the detailed procedure for calculating causality measures is provided in the Appendicesof the Supplemental Material. This formalism and the prototype of its numerical implementation can be further developed and applied in many different fields of physical, natural, and engineering sciences.

Relaxation-Assisted Magnetization Transfer Phenomena for a Sensitivity-Enhanced 2D NMR.

2D NOESY and TOCSY play central roles in contemporary NMR. We have recently discussed how solvent-driven exchanges can significantly enhance the sensitivity of such methods when attempting correlations between labile and nonlabile protons. This study explores two scenarios where similar sensitivity enhancements can be achieved in the absence of solvent exchange: the first one involves biomolecular paramagnetic systems, while the other involves small organic molecules in natural abundance. It is shown that, in both cases, the effects introduced by either differential paramagnetic shift and relaxation or by polarization sharing among networks of protons can provide a similar sensitivity boost, as previously discussed for solvent exchange. The origin and potential of the resulting enhancements are analyzed, and experiments that demonstrate them in protein and natural products are exemplified. Limitations and future improvements of these approaches are also briefly discussed.

Effects of Crowding and Cosolutes on Biomolecular Function at Extreme Environmental Conditions.

The extent of the effect of cellular crowding and cosolutes on the functioning of proteins and cells is manifold and includes the stabilization of the biomolecular systems, the excluded volume effect, and the modulation of molecular dynamics. Simultaneously, it is becoming increasingly clear how important it is to take the environment into account if we are to shed light on biological function under various external conditions. Many biosystems thrive under extreme conditions, including the deep sea and subseafloor crust, and can take advantage of some of the effects of crowding. These relationships have been studied in recent years using various biophysical techniques, including neutron and X-ray scattering, calorimetry, FTIR, UV-vis and fluorescence spectroscopies. Combining knowledge of the structure and conformational dynamics of biomolecules under extreme conditions, such as temperature, high hydrostatic pressure, and high salinity, we highlight the importance of considering all results in the context of the environment. Here we discuss crowding and cosolute effects on proteins, nucleic acids, membranes, and live cells and explain how it is possible to experimentally separate crowding-induced effects from other influences. Such findings will contribute to a better understanding of the homeoviscous adaptation of organisms and the limits of life in general.

Theoretical elucidation of the structure, bonding, and reactivity of the CaMn4Ox clusters in the whole Kok cycle for water oxidation embedded in the oxygen evolving center of photosystem II. New molecular and quantum insights into the mechanism of the O-O bond formation.

This paper reviews our historical developments of broken-symmetry (BS) and beyond BS methods that are applicable for theoretical investigations of metalloenzymes such as OEC in PSII. The BS hybrid DFT (HDFT) calculations starting from high-resolution (HR) XRD structure in the most stable S1 state have been performed to elucidate structure and bonding of whole possible intermediates of the CaMn4Ox cluster (1) in the Si (i = 0 ~ 4) states of the Kok cycle. The large-scale HDFT/MM computations starting from HR XRD have been performed to elucidate biomolecular system structures which are crucial for examination of possible water inlet and proton release pathways for water oxidation in OEC of PSII. DLPNO CCSD(T0) computations have been performed for elucidation of scope and reliability of relative energies among the intermediates by HDFT. These computations combined with EXAFS, XRD, XFEL, and EPR experimental results have elucidated the structure, bonding, and reactivity of the key intermediates, which are indispensable for understanding and explanation of the mechanism of water oxidation in OEC of PSII. Interplay between theory and experiments have elucidated important roles of four degrees of freedom, spin, charge, orbital, and nuclear motion for understanding and explanation of the chemical reactivity of 1 embedded in protein matrix, indicating the participations of the Ca(H2O)n ion and tyrosine(Yz)-O radical as a one-electron acceptor for the O-O bond formation. The Ca-assisted Yz-coupled O-O bond formation mechanisms for water oxidation are consistent with recent XES and very recent time-resolved SFX XFEL and FTIR results.

The linear framework II: using graph theory to analyse the transient regime of Markov processes.

The linear framework uses finite, directed graphs with labelled edges to model biomolecular systems. Graph vertices represent chemical species or molecular states, edges represent reactions or transitions and edge labels represent rates that also describe how the system is interacting with its environment. The present paper is a sequel to a recent review of the framework that focussed on how graph-theoretic methods give insight into steady states as rational algebraic functions of the edge labels. Here, we focus on the transient regime for systems that correspond to continuous-time Markov processes. In this case, the graph specifies the infinitesimal generator of the process. We show how the moments of the first-passage time distribution, and related quantities, such as splitting probabilities and conditional first-passage times, can also be expressed as rational algebraic functions of the labels. This capability is timely, as new experimental methods are finally giving access to the transient dynamic regime and revealing the computations and information processing that occur before a steady state is reached. We illustrate the concepts, methods and formulas through examples and show how the results may be used to illuminate previous findings in the literature.

Discovery of structure–property relations for molecules via hypothesis-driven active learning over the chemical space

The discovery of the molecular candidates for application in drug targets, biomolecular systems, catalysts, photovoltaics, organic electronics, and batteries necessitates the development of machine learning algorithms capable of rapid exploration of chemical spaces targeting the desired functionalities. Here, we introduce a novel approach for active learning over the chemical spaces based on hypothesis learning. We construct the hypotheses on the possible relationships between structures and functionalities of interest based on a small subset of data followed by introducing them as (probabilistic) mean functions for the Gaussian process. This approach combines the elements from the symbolic regression methods, such as SISSO and active learning, into a single framework. The primary focus of constructing this framework is to approximate physical laws in an active learning regime toward a more robust predictive performance, as traditional evaluation on hold-out sets in machine learning does not account for out-of-distribution effects which may lead to a complete failure on unseen chemical space. Here, we demonstrate it for the QM9 dataset, but it can be applied more broadly to datasets from both domains of molecular and solid-state materials sciences.

Potential of Mean Force of Short‐Chain Surface Adsorption using Non‐Uniform Sampling Windows for Optimal Computational Efficiency

AbstractFree energy calculation in molecular simulation is an computationally expensive process. Umbrella sampling (US) is a go‐to method for obtaining the potential of mean force (PMF) along a reaction coordinate. Its computational cost increases drastically as the molecular system gets more complex. For many polymeric and biomolecular systems, adequately sampling all configurational degrees of freedom is computationally prohibitive. Using the adsorption of a short‐chain methylcellulose on a cellulose crystalline surface as the test case, this study shows that the sampling time required for reliable results is much higher than typical choices made in the literature. The accuracy of the PMF profile is strongly affected by sampling inadequacy in a few regions along the reaction coordinate. Non‐uniform windows and sampling parameters are proposed to enhance the sampling in difficult regions. Sampling windows that vary with the local PMF steepness are allocated with a new algorithm. Parameters in this algorithm are optimized for the best sampling efficiency. It is demonstrated that significantly less computer time will be required to achieve the same sampling accuracy if computational resources are optimally distributed along the reaction coordinate.

An automated single-molecule FRET platform for high-content, multiwell plate screening of biomolecular conformations and dynamics

Single-molecule FRET (smFRET) has become a versatile tool for probing the structure and functional dynamics of biomolecular systems, and is extensively used to address questions ranging from biomolecular folding to drug discovery. Confocal smFRET measurements are amongst the widely used smFRET assays and are typically performed in a single-well format. Thus, sampling of many experimental parameters is laborious and time consuming. To address this challenge, we extend here the capabilities of confocal smFRET beyond single-well measurements by integrating a multiwell plate functionality to allow for continuous and automated smFRET measurements. We demonstrate the broad applicability of the multiwell plate assay towards DNA hairpin dynamics, protein folding, competitive and cooperative protein–DNA interactions, and drug-discovery, revealing insights that would be very difficult to achieve with conventional single-well format measurements. For the adaptation into existing instrumentations, we provide a detailed guide and open-source acquisition and analysis software.

Trace impurities in sodium phosphate influences the physiological activity of Escherichia coli in M9 minimal medium

In the field of applied microbiology, reproducibility and experimental variability are important factors that influence both basic research as well as process development for industrial applications. Experimental reproducibility and accuracy depend not only on culture conditions such as temperature and aeration but also on raw materials and procedures used for media preparation. The M9 minimal medium is one of the most common synthetic media for culturing Escherichia coli and other bacteria. This synthetic medium can be used to observe and evaluate the physiological activity of microbes under minimal nutritional requirements and determine the limiting factor for the desired phenotype. Although one of the advantages using the M9 medium is that its composition can be modulated, it is difficult to control presence of trace components and impurities from the reagents for preparing this medium. Herein, we showed that trace ingredients present in the reagents used for M9 media preparation affect the bacterial physiological activities (e.g., cell growth, substrate consumption, and byproduct formation). Additionally, we systematically identified the trace ingredient that influenced phenotypic differences. Our results showed that the selection of reagents and accuracy during reagent preparation is important for experimental reproducibility in the field of bio-engineering and systems biology focused on the systematic and continuous development of biomolecular systems (e.g., biorefinery, metabolic engineering, and synthetic biology).

An image cipher based on bio-molecular hyper chaotic system with dual diffusion scheme

An image cipher based on bio-molecular hyper chaotic system with dual diffusion scheme

Free energy along drug-protein binding pathways interactively sampled in virtual reality

We describe a two-step approach for combining interactive molecular dynamics in virtual reality (iMD-VR) with free energy (FE) calculation to explore the dynamics of biological processes at the molecular level. We refer to this combined approach as iMD-VR-FE. Stage one involves using a state-of-the-art ‘human-in-the-loop’ iMD-VR framework to generate a diverse range of protein–ligand unbinding pathways, benefitting from the sophistication of human spatial and chemical intuition. Stage two involves using the iMD-VR-sampled pathways as initial guesses for defining a path-based reaction coordinate from which we can obtain a corresponding free energy profile using FE methods. To investigate the performance of the method, we apply iMD-VR-FE to investigate the unbinding of a benzamidine ligand from a trypsin protein. The binding free energy calculated using iMD-VR-FE is similar for each pathway, indicating internal consistency. Moreover, the resulting free energy profiles can distinguish energetic differences between pathways corresponding to various protein–ligand conformations (e.g., helping to identify pathways that are more favourable) and enable identification of metastable states along the pathways. The two-step iMD-VR-FE approach offers an intuitive way for researchers to test hypotheses for candidate pathways in biomolecular systems, quickly obtaining both qualitative and quantitative insight.

Radiation-Induced Transfer of Charge, Atoms, and Energy within Isolated Biomolecular Systems.

In biological tissues, ionizing radiation interacts with a variety of molecules and the consequences include cell killing and the modification of mechanical properties. Applications of biological radiation action are for instance radiotherapy, sterilization, or the tailoring of biomaterial properties. During the first femtoseconds to milliseconds after the initial radiation action, biomolecular systems typically respond by transfer of charge, atoms, or energy. In the condensed phase, it is usually very difficult to distinguish direct effects from indirect effects. A straightforward solution for this problem is the use of gas-phase techniques, for instance from the field of mass spectrometry. In this review, we survey mainly experimental but also theoretical work, focusing on radiation-induced intra- and inter-molecular transfer of charge, atoms, and energy within biomolecular systems in the gas phase. Building blocks of DNA, proteins, and saccharides, but also antibiotics are considered. The emergence of general processes as well as their timescales and mechanisms are highlighted.

Computational biophysics meets cryo‐EM revolution in the search for the functional dynamics of biomolecular systems

AbstractThere is a variety of experimental and computational techniques available to explore protein dynamics, each presenting advantages and limitations. One promising experimental technique that is driving the development of computational methods is cryo‐electron microscopy (cryo‐EM). Cryo‐EM provides molecular‐level structural data and first estimates of conformational landscape from single particle analysis but cannot track real‐time protein dynamics and may contain uncertainties in atomic positions especially at highly dynamic regions. Molecular simulations offer atomic‐level insights into protein dynamics; however, their computing time requirements limit the conformational sampling accuracy, and it is often hard, to assess by full‐atomic simulations the cooperative movements of biological interest for large assemblies such as those resolved by cryo‐EM. Coarse‐grained (CG) simulations permit us to explore such systems, but at the costs of lower resolution and potentially incomplete sampling of conformational space. On the other hand, analytical methods may circumvent sampling limitations. In particular, elastic network models‐based normal mode analyses (ENM‐NMA) provide unique solutions for the complete mode spectra near equilibrium states, even for systems of megadaltons, and may thus deliver information on mechanisms of motions relevant to biological function. Yet, they lack atomic resolution as well as temporal information for non‐equilibrium systems. Given the complementary nature of these methods, the integration of molecular simulations and ENM‐NMA into hybrid methodologies has gained traction. This review presents the current state‐of‐the‐art in structure‐based computations and how they are helping us gain a deeper understanding of biological mechanisms, with emphasis on the development of hybrid methods accompanying the advances in cryo‐EM.This article is categorized under: Structure and Mechanism > Computational Biochemistry and Biophysics

Nonaqueous Ion Pairing Exemplifies the Case for Including Electronic Polarization in Molecular Dynamics Simulations.

The inclusion of electronic polarization is of crucial importance in molecular simulations of systems containing charged moieties. When neglected, as often done in force field simulations, charge-charge interactions in solution may become severely overestimated, leading to unrealistically strong bindings of ions to biomolecules. The electronic continuum correction introduces electronic polarization in a mean-field way via scaling of charges by the reciprocal of the square root of the high-frequency dielectric constant of the solvent environment. Here, we use ab initio molecular dynamics simulations to quantify the effect of electronic polarization on pairs of like-charged ions in a model nonaqueous environment where electronic polarization is the only dielectric response. Our findings confirm the conceptual validity of this approach, underlining its applicability to complex aqueous biomolecular systems. Simultaneously, the results presented here justify the potential employment of weaker charge scaling factors in force field development.

Pyrimidine-morpholine hybrids as potent druggable therapeutics for Alzheimer’s disease: Synthesis, biochemical and in silico analyses

The identification of effective and druggable cholinesterase inhibitors to treat progressive neurodegenerative Alzheimer’s disorder remains a continuous drug discovery hunt. In this perspective, the present study investigates the design and discovery of pyrimidine-morpholine hybrids (5a-l) as potent cholinesterase inhibitors. Palladium-catalyzed Suzuki-Miyaura cross-coupling reaction was employed to introduce the structural diversity on the pyrimidine heterocyclic core. A range of commercially available boronic acids was successfully coupled showing a high functional group tolerance. In vitro cholinesterase inhibitory potential using Ellman’s method revealed significantly strong potency. Compound 5h bearing a meta-tolyl substituent at 2-position of pyrimidine ring emerged as a lead candidate against AChE with an inhibitory potency of 0.43 ± 0.42 µM, ∼38-fold stronger value than neostigmine (IC50 = 16.3 ± 1.12 µM). Compound 5h also showed the lead inhibition against BuChE with an IC50 value of 2.5 ± 0.04 µM. The kinetics analysis of 5h revealed the non-competitive mode of inhibition against AChE whereas computational modelling results of potent leads depicted diverse contacts with the binding site amino acid residues. Molecular dynamics simulations revealed the stability of biomolecular system, while, ADME analysis demonstrated druglikeness behaviour of potent compounds. Overall, the investigated pyrimidine-morpholine scaffold presented a remarkable potential to be developed as efficacious anti-Alzheimer’s drugs.

Replica Exchange with Hybrid Tempering Efficiently Samples PGLa Peptide Binding to Anionic Bilayer.

We evaluated the utility of a variant of the replica exchange method, a replica exchange with hybrid tempering (REHT), for all-atom explicit water biomolecular simulations and compared it with a more traditional replica exchange with the solute tempering (REST) algorithm. As a test system, we selected a 21-mer antimicrobial peptide PGLa binding to an anionic DMPC/DMPG lipid bilayer. Application of REHT revealed the following binding mechanism. Due to the strong hydrophobic moment, the bound PGLa adopts an extensive helical structure. The binding free energy landscape identifies two major bound states, a metastable surface bound state and a dominant inserted state. In both states, positively charged PGLa amino acids maintain electrostatic interactions with anionic phosphate groups by rotating the PGLa helix around its axis. PGLa binding causes an influx of anionic DMPG and an efflux of zwitterionic DMPC lipids from the peptide proximity. PGLa thins the bilayer and disorders the adjacent fatty acid tails. Deep invasion of water wires into the bilayer hydrophobic core is detected in the inserted peptide state. The analysis of charge density distributions indicated that peptide positive charges are nearly compensated for by lipid negative charges and water dipole ordering, whereas ions play no role in peptide binding. Thus, electrostatic interactions are the key energetic factor in binding cationic PGLa to an anionic DMPC/DMPG bilayer. Comparison of REHT and REST shows that due to exclusion of lipids from tempered partition, REST lags behind REHT in peptide equilibration, particularly, with respect to peptide insertion and helix acquisition. As a result, REST struggles to provide accurate details of PGLa binding, although it still qualitatively maps the bimodal binding mechanism. Importantly, REHT not only equilibrates PGLa in the bilayer faster than REST, but also with less computational effort. We conclude that REHT is a preferable choice for studying interfacial biomolecular systems.

Polarizable Embedding Potentials through Molecular Fractionation with Conjugate Caps Including Hydrogen Bonds.

Polarizable embedding (PE) refers to classical embedding approaches, such as those used in quantum mechanics/molecular mechanics (QM/MM), that allow mutual polarization between the quantum and classical regions. The quality of the embedding potential is critical to provide accurate results, e.g., for spectroscopic properties and dynamical processes. High-quality embedding-potential parameters can be obtained by dividing the classical region into smaller fragments and deriving the parameters from ab initio calculations on the fragments. For solvents and other systems composed of small molecules, the fragments can be individual molecules, while a more complicated fragmentation procedure is needed for larger molecules, such as proteins and nucleic acids. One such fragmentation strategy is the molecular fractionation with conjugate caps (MFCC) approach. As is widely known, hydrogen bonds play a key role in many biomolecular systems, e.g., in proteins, where they are responsible for the secondary structure. In this work, we assess the effects of including hydrogen-bond fragmentation in the MFCC procedure [MFCC(HB)] for deriving the embedding-potential parameters. The MFCC(HB) extension is evaluated on several molecular systems, ranging from small model systems to proteins, directly in terms of molecular electrostatic potentials and embedding potentials and indirectly in terms of selected properties of chromophores embedded in water and complex protein environments.

Connected Component Analysis of Dynamical Perturbation Contact Networks.

Describing protein dynamical networks through amino acid contacts is a powerful way to analyze complex biomolecular systems. However, due to the size of the systems, identifying the relevant features of protein-weighted graphs can be a difficult task. To address this issue, we present the connected component analysis (CCA) approach that allows for fast, robust, and unbiased analysis of dynamical perturbation contact networks (DPCNs). We first illustrate the CCA method as applied to a prototypical allosteric enzyme, the imidazoleglycerol phosphate synthase (IGPS) enzyme from Thermotoga maritima bacteria. This approach was shown to outperform the clustering methods applied to DPCNs, which could not capture the propagation of the allosteric signal within the protein graph. On the other hand, CCA reduced the DPCN size, providing connected components that nicely describe the allosteric propagation of the signal from the effector to the active sites of the protein. By applying the CCA to the IGPS enzyme in different conditions, i.e., at high temperature and from another organism (yeast IGPS), and to a different enzyme, i.e., a protein kinase, we demonstrated how CCA of DPCNs is an effective and transferable tool that facilitates the analysis of protein-weighted networks.

Nano-Bio Interface Engineering Using Cyclovoltammetry and Design of Nanostructured Lanthanide Oxysulfide Thin Films

Nanoparticles (NPs) in which magnetic and optical properties coexist have been intensively explored for diverse biomedical applications including diagnostic, in vivo imaging and therapy. Gadolinium oxysulfide (Gd2O2S) NPs are promising candidates for biotechnologies as they have been used as MRI contrast agent or X-ray absorbing materials. When doped with cerium, they gain an additional functionality as visible light absorber due to the decrease in the material bandgap from 4.7 eV non-doped to 2.5 eV with 5% of Ce. Further biomedical applications may be envisioned thanks to the combined antioxidant properties of cerium and the magnetic properties of gadolinium.Understanding the molecular-level interactions between organisms and nanoparticles to guide and enable the design of novel materials that are less toxic remains a challenge. In order to understand these interactions at the nanoscale, we studied the change in the physico-chemical properties of (Gd,Ce) oxysulfide NPs when they are immersed in a biological medium. In biological medium, pristine nanomaterials transform and acquire a corona of biomolecules, such as proteins, which can modify their identity. This is known as the nano-bio interface. A better understanding of how nanoparticles interaction with a biological system affect their properties is critical to the future development of multifunctional NPs.Our recent work provides us with a privileged access to composition-controlled nanoplates with a narrow size distribution for a large range of Ln. In particular, we mastered the preparation of mixed-lanthanide nanoplates with tunable band gap and magnetic properties while providing an in-depth understanding of their structural and surface features. The challenge addressed here is to prepare and characterize ligand-free nanostructured thin films made from the NPs suspension. Compared to studies realized in solution, thin films allow to reach the surface of the nanoparticles without any interaction from the ligands. Moreover, it allows spectroscopic and electrochemical methods to be used for the monitoring of the NPs intrinsic properties.The design and development of nanostructured thin films started with the colloidal synthesis of (Gd,Ce) oxysulfide NPs which provides a phase-pure powder. The nanoparticles were then dispersed into an optimized mix of solvents in order to get a stable colloidal suspension. Dip coating is an easy method to deposit matter on a substrate while having a fine control of the thickness and homogeneity. This process was optimized to obtain homogenous films with a withdrawal speed of 2 mm/s under low relative humidity. Thin films of optical quality with a thickness from 40 nm to 150 nm were obtained using single-layer and multilayer deposition on various substrates including silicon, FTO and kapton (Figure A). In situ UV and IR Spectroscopic Ellipsometry were used to monitor the variations of thickness and optical constants, together with the chemical species present at the surface, upon heating the films in different conditions. This study allowed to finely tune the thermal treatment in order to get rid of the stabilizing ligands while preserving the integrity of the nanoplates, as confirmed by Transmission Electron Microscopy (Figure B shows the scraped film). As a result, we have access to the bare surface of the NPs, which was hardly possible in solution. The change in the band gap of the material was monitored through UV-Variable Angle Spectroscopic Ellipsometry. This non-invasive technique is the gold-standard for the characterization of optical quality thin films and gives refractive index of the material (Figure C shows the Tauc plot with the linear fit giving the band gap of the material).The film can be immersed into a biological medium where proteins are expected to bind to the surface of the NP and significantly change their reactivity and mobility. Cyclovoltammetry helped us to probe the access to the NPs and monitor the position of the conduction band. We used redox probes of different standard potentials as electrolytes (Figure D). Electron exchange with the semiconductor electrode is supposed to occur through the conduction band as the valence band is too far in energy. For a redox couple with a standard potential negative to the conduction band edge, when the applied potential equals E0 redox, the semiconductor is accumulating electrons at its surface in a so-called space charge layer. Under these conditions, whether a positive or negative bias is applied (compared to E0 redox), the SC is maintained in an accumulation mode. This was very helpful to check whereas the electronical properties of the material changed upon exposition to biological medium. This could lead to a better understanding and prediction of the chemical interactions at the interface with biomolecular systems. Figure 1

Facile Strategy to Output Fluorescein from Nucleic Acid Interactions.

Biomolecular operations, which involve the conversion of molecular signals or interactions into specific functional outputs, are fundamental to the field of biology and serve as the important foundation for the design of diagnostic and therapeutic systems. To maximize their functionalities and broaden their applicability, it is crucial to develop novel outputs and facile chemical transformation methods. With this aim, in this study, we present a straightforward method for converting nucleic acid signals into fluorescein outputs that exhibit a wide range of functionalities. This operation is designed through a DNA-templated reaction based on riboflavin-photocatalyzed oxidation of dihydrofluorescein, which is readily prepared by simple NaBH4 reduction of the fluorescein with no complicated chemical caging steps. The templated photooxidation exhibits high efficiency (kapp = 2.7 × 10-3/s), generating a clear fluorescein output signal distinguishable from a low background, originating from the high stability of the synthesized dihydrofluorescein. This facile and efficient operation allows the nucleic acid-initiated activation of various fluorescein functions, such as fluorescence and artificial oxidase activity, which are applied in the design of novel bioanalytical systems, including fluorescent and colorimetric DNA sensors. The operation presented herein would expand the scope of biomolecular circuit systems for diagnostic and therapeutic applications.