Toward dynamic structural biology: Two decades of single-molecule Förster resonance energy transfer

Internal energy recycling in FAPbI3/MXene for enhanced photocatalytic H2 evolution

Carrier recombination is a significant impediment to efficient charge separation, thereby severely limiting the performance of photocatalytic systems. In this study, we feature an innovative internal energy cycling mechanism through the non-radiative fluorescence resonance energy transfer (FRET) between perovskite and MXene, to exploit the energy released by carrier recombination for enhancing H2 evolution rate. Consequently, a rapid H2 evolution rate of 2394 µmol g-1 h-1 under 1.5 AM simulated sunlight, from the composite of FAPbI3/MXene/Pt, was acquired, which is more than one order of magnitude higher than that of FAPbI3/Pt (64 µmol g-1 h-1). The innovative approach of FRET induced internal energy cycling will open up opportunities to design other novel heterogeneous catalytic materials and promote their application potential in various catalytic fields.

Single-molecule detection of oligonucleotides using the fluorescent nucleobase analogue ABN

Fluorescent nucleobase analogues (FBAs) have emerged as powerful tools for understanding nucleic acid systems at the molecular level. However, their application at the single-molecule level has been limited by low brightness and an incomplete understanding of how local chemical environments affect their properties. In this study, we investigate the bright fluorescent pyrimidine analogue ABN in duplex DNA oligonucleotides and study its single-molecule applications. Time-resolved fluorescence spectroscopy reveals its unique tautomeric behavior, including photo-induced double proton transfer, influenced by base-pairing partners. This tautomerization directly impacts ABN's quantum yield and spectral characteristics. By favoring a high quantum yield thymine-like tautomer through base pairing, surface-immobilized ABN-containing DNA duplexes are readily observed as bright spots using single-molecule fluorescence microscopy, exhibiting well-defined single-exponential bleaching kinetics. The brightness and photostability are enhanced by oxygen depletion. These results demonstrate that ABN is unique among FBAs in enabling single-molecule fluorescence studies of oligonucleotides using a standard microscopy setup.

On the breakdown of Förster energy transfer theory due to solvent effects: atomistic simulations unveil distance-dependent dielectric screening in calmodulin

Förster resonance energy transfer (FRET) is a powerful technique used to investigate the conformational preferences of biosystems, and molecular simulations have emerged as an ideal complement to FRET due to their ability to provide structural models that can be compared with experiments. This synergy is however hampered by the approximations underlying Förster theory regarding the electronic coupling between the participating dyes: a dipole-dipole term attenuated by a simple dielectric screening factor 1/n 2 that depends on the refractive index of the medium. Whereas the limits of the dipole approximation are well-known, detailed insights on how environment effects deviate from the 1/n 2 assumption and modify the R -6 distance dependence that characterizes FRET as a spectroscopic ruler are still not well understood, especially in biosystems characterized by significant structural disorder. Here we address this using a rigorous theoretical framework based on electrostatic potential-fitted transition charges coupled to an atomistic polarizable classical environment, which allows investigation of dielectric screening in atomic detail in extended simulations of disordered systems. We apply this strategy to investigate the conformational preferences of calmodulin, a protein that plays a major role in the transmission of calcium signals. Our results indicate that dielectric screening displays an exponential decay at donor/acceptor separations below 20 Å, significantly modifying the R -6 distance dependence widely adopted in FRET studies. Screening appears to be maximized at separations ∼15 Å, a situation in which the fluorophores are partially excluded from the solvent and thus screening is dictated by the more polarizable protein environment.

Physical Isolation of Single Protein Molecules within Well-Defined Coordination Cages to Enhance Their Stability

Encapsulation of a single protein within a confined space can lead to distinct properties compared to bulk solutions, but controlling the number of encapsulated proteins and their environment remains challenging. This study demonstrates the encapsulation of single proteins within well-defined, tunable cavities of self-assembled coordination cages, thereby enhancing protein stability. Within uniform cavities of size-tunable coordination cages, 15 different proteins of varying sizes (3-6 nm in diameter) and properties (e.g., isoelectric points and hydrophobicity) were successfully confined. Various analytical techniques confirmed that the proteins maintained their secondary structures and enzymatic activities under denaturing conditions such as exposure to organic solvents, heat, and buffers. These findings suggest that such coordination cages have the potential to serve as synthetic hosts for precisely controlling protein functions within their customizable cavities.

Determination of absolute intramolecular distances in proteins using anomalous X-ray scattering interferometry

Biomolecular structures are typically determined using frozen or crystalline samples. Measurement of intramolecular distances in solution can provide additional insights into conformational heterogeneity and dynamics of biological macromolecules and their complexes. The established molecular ruler techniques used for this (NMR, FRET, and EPR) are, however, limited in their dynamic range and require model assumptions to determine absolute distance or distance distributions. Here, we introduce anomalous X-ray scattering interferometry (AXSI) for intramolecular distance measurements in proteins, which are labeled at two sites with small gold nanoparticles of 0.7 nm radius. We apply AXSI to two different cysteine-variants of maltose binding protein in the presence and absence of its ligand maltose and find distances in quantitative agreement with single-molecule FRET experiments. Our study shows that AXSI enables determination of intramolecular distance distributions under virtually arbitrary solution conditions and we anticipate its broad use to characterize protein conformational ensembles and dynamics.

Genetic Code Expansion: Recent Developments and Emerging Applications

The concept of genetic code expansion (GCE) has revolutionized the field of chemical and synthetic biology, enabling the site-specific incorporation of noncanonical amino acids (ncAAs) into proteins, thus opening new avenues in research and applications across biology and medicine. In this review, we cover the principles of GCE, including the optimization of the aminoacyl-tRNA synthetase (aaRS)/tRNA system and the advancements in translation system engineering. Notable developments include the refinement of aaRS/tRNA pairs, enhancements in screening methods, and the biosynthesis of noncanonical amino acids. The applications of GCE technology span from synthetic biology, where it facilitates gene expression regulation and protein engineering, to medicine, with promising approaches in drug development, vaccine production, and gene editing. The review concludes with a perspective on the future of GCE, underscoring its potential to further expand the toolkit of biology and medicine. Through this comprehensive review, we aim to provide a detailed overview of the current state of GCE technology, its challenges, opportunities, and the frontier it represents in the expansion of the genetic code for novel biological research and therapeutic applications.

The conformational space of RNase P RNA in solution

RNA conformational diversity has fundamental biological roles1-5, but direct visualization of its full conformational space in solution has not been possible using traditional biophysical techniques. Using solution atomic force microscopy, a deep neural network and statistical analyses, we show that the ribonuclease P (RNase P) RNA adopts heterogeneous conformations consisting of a conformationally invariant core and highly flexible peripheral structural elements that sample a broad conformational space, with amplitudes as large as 20-60 Å in a multitude of directions, with very low net energy cost. Increasing Mg2+ drives compaction and enhances enzymatic activity, probably by narrowing the conformational space. Moreover, analyses of the correlations and anticorrelations between spatial flexibility and sequence conservation suggest that the functional roles of both the structure and dynamics of key regions are embedded in the primary sequence. These findings reveal the structure-dynamics basis for the embodiment of both enzymatic precision and substrate promiscuity in the RNA component of the RNase P. Mapping the conformational space of the RNase P RNA demonstrates a new general approach to studying RNA structure and dynamics.

The conserved lysine residue in transmembrane helix 5 is pivotal for the cytoplasmic gating of the L-amino acid transporters

L-Amino acid transporters (LATs) play a key role in a wide range of physiological processes. Defects in LATs can lead to neurological disorders and aminoacidurias, while the overexpression of these transporters is related to cancer. BasC is a bacterial LAT transporter with an APC fold. In this study, to monitor the cytoplasmic motion of BasC, we developed a single-molecule Förster resonance energy transfer assay that can characterize the conformational states of the intracellular gate in solution at room temperature. Based on combined biochemical and biophysical data and molecular dynamics simulations, we propose a model in which the conserved lysine residue in TM5 supports TM1a to explore both open and closed states within the cytoplasmic gate under apo conditions. This equilibrium can be altered by substrates, mutation of conserved lysine 154 in TM5, or a transport-blocking nanobody interacting with TM1a. Overall, these findings provide insights into the transport mechanism of BasC and highlight the significance of the lysine residue in TM5 in the cytoplasmic gating of LATs.

Single-molecule dynamic structural biology with vertically arranged DNA on a fluorescence microscope

The intricate interplay between DNA and proteins is key for biological functions such as DNA replication, transcription and repair. Dynamic nanoscale observations of DNA structural features are necessary for understanding these interactions. Here we introduce graphene energy transfer with vertical nucleic acids (GETvNA), a method to investigate DNA-protein interactions that exploits the vertical orientation adopted by double-stranded DNA on graphene. This approach enables the dynamic study of DNA conformational changes via energy transfer from a probe dye to graphene, achieving spatial resolution down to the Ångström scale at subsecond temporal resolution. We measured DNA bending induced by adenine tracts, bulges, abasic sites and the binding of endonuclease IV. In addition, we observed the translocation of the O6-alkylguanine DNA alkyltransferase on DNA, reaching single base-pair resolution and detecting preferential binding to adenine tracts. This method promises widespread use for dynamical studies of nucleic acids and nucleic acid-protein interactions with resolution so far reserved for traditional structural biology techniques.

The known unknowns of the Hsp90 chaperone

Molecular chaperones are vital proteins that maintain protein homeostasis by assisting in protein folding, activation, degradation, and stress protection. Among them, heat-shock protein 90 (Hsp90) stands out as an essential proteostasis hub in eukaryotes, chaperoning hundreds of 'clients' (substrates). After decades of research, several 'known unknowns' about the molecular function of Hsp90 remain unanswered, hampering rational drug design for the treatment of cancers, neurodegenerative, and other diseases. We highlight three fundamental open questions, reviewing the current state of the field for each, and discuss new opportunities, including single-molecule technologies, to answer the known unknowns of the Hsp90 chaperone.

Accounting for Fast vs Slow Exchange in Single Molecule FRET Experiments Reveals Hidden Conformational States

Proteins are dynamic systems whose structural preferences determine their function. Unfortunately, building atomically detailed models of protein structural ensembles remains challenging, limiting our understanding of the relationships between sequence, structure, and function. Combining single molecule Förster resonance energy transfer (smFRET) experiments with molecular dynamics simulations could provide experimentally grounded, all-atom models of a protein's structural ensemble. However, agreement between the two techniques is often insufficient to achieve this goal. Here, we explore whether accounting for important experimental details like averaging across structures sampled during a given smFRET measurement is responsible for this apparent discrepancy. We present an approach to account for this time-averaging by leveraging the kinetic information available from Markov state models of a protein's dynamics. This allows us to accurately assess which time scales are averaged during an experiment. We find this approach significantly improves agreement between simulations and experiments in proteins with varying degrees of dynamics, including the well-ordered protein T4 lysozyme, the partially disordered protein apolipoprotein E (ApoE), and a disordered amyloid protein (Aβ40). We find evidence for hidden states that are not apparent in smFRET experiments because of time averaging with other structures, akin to states in fast exchange in nuclear magnetic resonance, and evaluate different force fields. Finally, we show how remaining discrepancies between computations and experiments can be used to guide additional simulations and build structural models for states that were previously unaccounted for. We expect our approach will enable combining simulations and experiments to understand the link between sequence, structure, and function in many settings. Understanding protein dynamics is crucial for understanding protein function, yet few methodologies report on protein motion at an atomic level. Combining single molecule Förster resonance energy transfer (smFRET) experiments with computer simulations could provide atomistic models of protein ensembles which are grounded in experiments, however, there has been limited agreement between the two methods to date. Here, we present an algorithm to recapitulate smFRET experiments from molecular dynamics simulations. This approach significantly improves agreement between simulations and experiments for proteins across the ordered spectrum. Moreover, with this approach we can confidently create atomic models for states observed during smFRET experiments which were otherwise difficult to model due to high amounts of flexibility, disorder, or large deviations from crystal-like states.

Time-heterogeneity of the Förster Radius from Dipole Orientational Dynamics Impacts Single-Molecule FRET Experiments

Förster resonance energy transfer (FRET) is a quantum mechanical phenomenon involving the non-radiative transfer of energy between coupled electric dipoles. Due to the strong dependence of FRET on the distance between the dipoles, it is frequently used as a "molecular ruler" in biology, chemistry, and physics. This is done by placing dipolar molecules called dyes on molecules of interest. In time-resolved confocal single-molecule FRET (smFRET) experiments, the joint distribution of the FRET efficiency and the donor fluorescence lifetime can reveal underlying molecular conformational dynamics via deviation from their theoretical Förster relationship. This deviation is referred to as a dynamic shift. Quantifying the dynamic shift caused by the motion of the fluorescent dyes is essential to decoupling the dynamics of the studied molecules and the dyes. We develop novel Langevin models for the dye linker dynamics, including rotational dynamics, based on first principle physics and proper dye linker chemistry to match accessible volumes predicted by molecular dynamics simulations. By simulating the dyes' stochastic translational and rotational dynamics, we show that the observed dynamic shift can largely be attributed to the mutual orientational dynamics of the electric dipole moments associated with the dyes, not their accessible volume. Our models provide the most up-to-date and accurate estimation of FRET.

Deep learning based local feature classification to automatically identify single molecule fluorescence events

Long-term single-molecule fluorescence measurements are widely used powerful tools to study the conformational dynamics of biomolecules in real time to further elucidate their conformational dynamics. Typically, thousands or even more single-molecule traces are analyzed to provide statistically meaningful information, which is labor-intensive and can introduce user bias. Recently, several deep-learning models have been developed to automatically classify single-molecule traces. In this study, we introduce DEBRIS (Deep lEarning Based fRagmentatIon approach for Single-molecule fluorescence event identification), a deep-learning model focusing on classifying local features and capable of automatically identifying steady fluorescence signals and dynamically emerging signals of different patterns. DEBRIS efficiently and accurately identifies both one-color and two-color single-molecule events, including their start and end points. By adjusting user-defined criteria, DEBRIS becomes the pioneer in using a deep learning model to accurately classify four different types of single-molecule fluorescence events using the same trained model, demonstrating its universality and ability to enrich the current toolbox.

Optical scattering methods for the label-free analysis of single biomolecules

Single-molecule techniques to analyze proteins and other biomolecules involving labels and tethers have allowed for new understanding of the underlying biophysics; however, the impact of perturbation from the labels and tethers has recently been shown to be significant in several cases. New approaches are emerging to measure single proteins through light scattering without the need for labels and ideally without tethers. Here, the approaches of interference scattering, plasmonic scattering, microcavity sensing, nanoaperture optical tweezing, and variants are described and compared. The application of these approaches to sizing, oligomerization, interactions, conformational dynamics, diffusion, and vibrational mode analysis is described. With early commercial successes, these approaches are poised to have an impact in the field of single-molecule biophysics.

smFRET-assisted RNA structure prediction

Single-molecule Förster Resonance Energy Transfer (smFRET) is a powerful biophysical technique that utilizes the distance-dependent energy transfer between donor and acceptor dyes linked to individual molecules, providing insights into molecular conformational changes and interactions at the single-molecule level. Prior investigations leveraged smFRET to study the conformational dynamics of single truncated Ubc4 pre-mRNA molecules during splicing, yet these efforts did not prioritize structural modeling. In this study, we develop an smFRET-assisted RNA prediction method to predict the 2D and 3D structures of this pre-mRNA. To achieve this, we initiate the process by generating RNA structural ensembles through coarse-grained molecular dynamics (MD) simulations. Subsequently, inter-dye distances are calculated for these RNA structural ensembles by performing all-atom MD simulations of the dye groups. The ultimate determination of the 2D and 3D structures for the pre-mRNA is achieved by comparing the calculated inter-dye distances with experimental counterparts. Notably, our computational results demonstrate a significant alignment with experimental findings, which involve a conformational change at the 2D level.

Simple methods to determine the dissociation constant, Kd

The determination of the dissociation constant (Kd) is pivotal in biochemistry and pharmacology for understanding binding affinities in chemical reactions, which is crucial for drug development and comprehending biological systems. Here, we introduce a single-molecule fluorescence resonance energy transfer-based method for determining Kd, alongside the conventional electrophoretic mobility shift assay method of Kd, offering insights into thermodynamic interactions between proteins and substrates. The single-molecule fluorescence resonance energy transfer approach is highlighted for its ability to accurately measure binding and dissociation kinetics through fluorescence labeling and the intrinsic nature of protein-DNA interactions, representing a significant advancement in the fields of molecular biology and pharmacology.

Using Förster Resonance Energy Transfer (FRET) to Understand the Ubiquitination Landscape

Förster resonance energy transfer (FRET) is a fluorescence technique that allows quantitative measurement of protein interactions, kinetics and dynamics. This review covers the use of FRET to study the structures and mechanisms of ubiquitination and related proteins. We survey FRET assays that have been developed where donor and acceptor fluorophores are placed on E1, E2 or E3 enzymes and ubiquitin (Ub) to monitor steady-state and real-time transfer of Ub through the ubiquitination cascade. Specialized FRET probes placed on Ub and Ub-like proteins have been developed to monitor Ub removal by deubiquitinating enzymes (DUBs) that result in a loss of a FRET signal upon cleavage of the FRET probes. FRET has also been used to understand conformational changes in large complexes such as multimeric E3 ligases and the proteasome, frequently using sophisticated single molecule methods. Overall, FRET is a powerful tool to help unravel the intricacies of the complex ubiquitination system.

Single-molecule detection and super-resolution imaging with a portable and adaptable 3D-printed microscopy platform (Brick-MIC)

Over the past decades, single-molecule and super-resolution microscopy have advanced and represent essential tools for life science research. There is, however, a growing gap between the state of the art and what is accessible to biologists, biochemists, medical researchers, or labs with financial constraints. To bridge this gap, we introduce Brick-MIC, a versatile and affordable open-source 3D-printed microspectroscopy and imaging platform. Brick-MIC enables the integration of various fluorescence imaging techniques with single-molecule resolution within a single platform and exchange between different modalities within minutes. We here present variants of Brick-MIC that facilitate single-molecule fluorescence detection, fluorescence correlation spectroscopy, time-correlated single-photon counting and super-resolution imaging (STORM and PAINT). Detailed descriptions of the hardware and software components, as well as data analysis routines, are provided, to allow non-optics specialists to operate their own Brick-MIC with minimal effort and investments. We foresee that our affordable, flexible, and open-source Brick-MIC platform will be a valuable tool for many laboratories worldwide.

Insight into Single-Molecule Imaging Techniques for the Study of Prokaryotic Genome Maintenance

Genome maintenance comprises a group of complex and interrelated processes crucial for preserving and safeguarding genetic information within all organisms. Key aspects of genome maintenance involve DNA replication, transcription, recombination, and repair. Improper regulation of these processes could cause genetic changes, potentially leading to antibiotic resistance in bacterial populations. Due to the complexity of these processes, ensemble averaging studies may not provide the level of detail required to capture the full spectrum of molecular behaviors and dynamics of each individual biomolecule. Therefore, researchers have increasingly turned to single-molecule approaches, as these techniques allow for the direct observation and manipulation of individual biomolecules, and offer a level of detail that is unattainable with traditional ensemble methods. In this review, we provide an overview of recent in vitro and in vivo single-molecule imaging approaches employed to study the complex processes involved in prokaryotic genome maintenance. We will first highlight the principles of imaging techniques such as total internal reflection fluorescence microscopy and atomic force microscopy, primarily used for in vitro studies, and highly inclined and laminated optical sheet and super-resolution microscopy, mainly employed in in vivo studies. We then demonstrate how applying these single-molecule techniques has enabled the direct visualization of biological processes such as replication, transcription, DNA repair, and recombination in real time. Finally, we will showcase the results obtained from super-resolution microscopy approaches, which have provided unprecedented insights into the spatial organization of different biomolecules within bacterial organisms.

Enhancing Therapeutic Response and Overcoming Resistance to Checkpoint Inhibitors in Ovarian Cancer through Cell Cycle Regulation

Tumor cells invade normal surrounding tissues through continuous division. In this study, we hypothesized that cell cycle regulation changes the immune efficacy of ovarian cancer. To investigate this hypothesis, a Förster resonance energy transfer (FRET) sensor was constructed to characterize the cell activity in real time. Cell shrinkage caused by apoptosis induces the aggregation of proteins on the cell membrane, leading to variations in the fluorescence lifetime of FRET sensors. Moreover, we tracked cell activity across various cycles following co-culture with an immune checkpoint inhibitor. Consequently, we assessed how cell cycle regulation influences immunotherapy in a tumor mouse model. This approach, which involves inhibiting typical cell cycle processes, markedly enhances the effectiveness of immunotherapy. Our findings suggest that modulating the cycle progression of cancer cells may represent a promising approach to enhance the immune response of ovarian cancer cells and the efficacy of immunotherapy based on immune checkpoint inhibitors.

Utilizing Molecular Dynamics Simulations, Machine Learning, Cryo-EM, and NMR Spectroscopy to Predict and Validate Protein Dynamics

Protein dynamics play a crucial role in biological function, encompassing motions ranging from atomic vibrations to large-scale conformational changes. Recent advancements in experimental techniques, computational methods, and artificial intelligence have revolutionized our understanding of protein dynamics. Nuclear magnetic resonance spectroscopy provides atomic-resolution insights, while molecular dynamics simulations offer detailed trajectories of protein motions. Computational methods applied to X-ray crystallography and cryo-electron microscopy (cryo-EM) have enabled the exploration of protein dynamics, capturing conformational ensembles that were previously unattainable. The integration of machine learning, exemplified by AlphaFold2, has accelerated structure prediction and dynamics analysis. These approaches have revealed the importance of protein dynamics in allosteric regulation, enzyme catalysis, and intrinsically disordered proteins. The shift towards ensemble representations of protein structures and the application of single-molecule techniques have further enhanced our ability to capture the dynamic nature of proteins. Understanding protein dynamics is essential for elucidating biological mechanisms, designing drugs, and developing novel biocatalysts, marking a significant paradigm shift in structural biology and drug discovery.

Massively parallel analysis of single-molecule dynamics on next-generation sequencing chips

Single-molecule techniques are ideally poised to characterize complex dynamics but are typically limited to investigating a small number of different samples. However, a large sequence or chemical space often needs to be explored to derive a comprehensive understanding of complex biological processes. Here we describe multiplexed single-molecule characterization at the library scale (MUSCLE), a method that combines single-molecule fluorescence microscopy with next-generation sequencing to enable highly multiplexed observations of complex dynamics. We comprehensively profiled the sequence dependence of DNA hairpin properties and Cas9-induced target DNA unwinding-rewinding dynamics. The ability to explore a large sequence space for Cas9 allowed us to identify a number of target sequences with unexpected behaviors. We envision that MUSCLE will enable the mechanistic exploration of many fundamental biological processes.

Bayesian reweighting of biomolecular structural ensembles using heterogeneous cryo-EM maps with the cryoENsemble method

Cryogenic electron microscopy (cryo-EM) has emerged as a powerful method for the determination of structures of complex biological molecules. The accurate characterisation of the dynamics of such systems, however, remains a challenge. To address this problem, we introduce cryoENsemble, a method that applies Bayesian reweighting to conformational ensembles derived from molecular dynamics simulations to improve their agreement with cryo-EM data, thus enabling the extraction of dynamics information. We illustrate the use of cryoENsemble to determine the dynamics of the ribosome-bound state of the co-translational chaperone trigger factor (TF). We also show that cryoENsemble can assist with the interpretation of low-resolution, noisy or unaccounted regions of cryo-EM maps. Notably, we are able to link an unaccounted part of the cryo-EM map to the presence of another protein (methionine aminopeptidase, or MetAP), rather than to the dynamics of TF, and model its TF-bound state. Based on these results, we anticipate that cryoENsemble will find use for challenging heterogeneous cryo-EM maps for biomolecular systems encompassing dynamic components.

Regioselective enzymatic depolymerization of aromatic-aliphatic polyester revealed by computational modelling

Poly(butylene adipate-co-terephthalate) (PBAT) is widely utilized in the production of food packaging and mulch films. Its extensive application has contributed significantly to global solid waste, posing numerous environmental challenges. Recently, enzymatic recycling has emerged as a promising eco-friendly solution for the management of plastic waste. Here, we systematically investigate the depolymerization mechanism of PBAT catalyzed by cutinase TfCutSI with molecular docking, molecular dynamics simulations, and quantum mechanics/molecular mechanics calculations. Although the binding affinities for acid ester and terephthalic acid ester bonds are similar, a regioselective depolymerization mechanism and a "chain-length" effect on regioselectivity were proposed and evidenced. The regioselectivity is highly associated with specific structural parameters, namely Substrate@O4-Met@H7 and Substrate@C1-Ser@O1 distances. Notably, the binding mode of BTa captured by X-ray crystallography does not facilitate subsequent depolymerization. Instead, a previously unanticipated binding mode, predicted through computational analysis, is confirmed to play a crucial role in BTa depolymerization. This finding proves the critical role of computational modelling in refining experimental results. Furthermore, our results revealed that both the hydrogen bond network and enzyme's intrinsic electric field are instrumental in the formation of the final product. In summary, these novel molecular insights into the PBAT depolymerization mechanism offer a fundamental basis for enzyme engineering to enhance industrial plastic recycling.

Probing and imaging phospholipid dynamics in live cells

Distinct phospholipid species display specific distribution patterns across cellular membranes, which are important for their structural and signaling roles and for preserving the integrity and functionality of the plasma membrane and organelles. Recent advancements in lipid biosensor technology and imaging modalities now allow for direct observation of phospholipid distribution, trafficking, and dynamics in living cells. These innovations have markedly advanced our understanding of phospholipid function and regulation at both cellular and subcellular levels. Herein, we summarize the latest developments in phospholipid biosensor design and application, emphasizing the contribution of cutting-edge imaging techniques to elucidating phospholipid dynamics and distribution with unparalleled spatiotemporal precision.

Quantifying Microsecond Solution-Phase Conformational Dynamics of a DNA Hairpin at the Single-Molecule Level

Quantifying the rapid conformational dynamics of biological systems is fundamental to understanding the mechanism. However, biomolecules are complex, often containing static and dynamic heterogeneity, thus motivating the use of single-molecule methods, particularly those that can operate in solution. In this study, we measure microsecond conformational dynamics of solution-phase DNA hairpins at the single-molecule level using an anti-Brownian electrokinetic (ABEL) trap. Different conformational states were distinguished by their fluorescence lifetimes, and kinetic parameters describing transitions between these states were determined using two-dimensional fluorescence lifetime correlation (2DFLCS) analysis. Rather than combining fluorescence signals from the entire data set ensemble, long observation times of individual molecules allowed ABEL-2DFLCS to be performed on each molecule independently, yielding the underlying distribution of the system's kinetic parameters. ABEL-2DFLCS on the DNA hairpins resolved an underlying heterogeneity of fluorescence lifetimes and provided signatures of two-state exponential dynamics with rapid ( Collapse

Key Words

• conformational dynamics
• single-molecule spectroscopy
• förster correlation spectroscopy
• nucleic acid hairpin
• fluorescence resonance energy transfer

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MESH Headings Collapse

Grants

• R01 GM136981 NIGMS NIH HHS
• National Institute of General Medical Sciences
• Morino Foundation for Molecular Science
• Japan Society for the Promotion of Science

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Affiliation(s)

Alexander K. Foote Department of Chemistry, University of Wisconsin—Madison, Madison, Wisconsin 53706, United States
Kunihiko Ishii Molecular Spectroscopy Laboratory, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan Ultrafast Spectroscopy Research Team, RIKEN Center for Advanced Photonics (RAP), 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
Brendan Cullinane Department of Chemistry, University of Wisconsin—Madison, Madison, Wisconsin 53706, United States
Tahei Tahara Molecular Spectroscopy Laboratory, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan Ultrafast Spectroscopy Research Team, RIKEN Center for Advanced Photonics (RAP), 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
Randall H. Goldsmith Department of Chemistry, University of Wisconsin—Madison, Madison, Wisconsin 53706, United States

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Developing Multichannel smFRET Approach to Dissecting Ribosomal Mechanisms

The ribosome, a 2.6 megadalton biomolecule measuring approximately 20 nm in diameter, coordinates numerous ligands, factors, and regulators to translate proteins with high fidelity and speed. Understanding its complex functions necessitates multiperspective observations. We developed a dual-FRET single-molecule Förste Resonance Energy Transfer method (dual-smFRET), allowing simultaneous observation and correlation of tRNA dynamics and Elongation Factor G (EF-G) conformations in the same complex, in a 10 s time window. By synchronizing laser shutters and motorized filter sets, two FRET signals are captured in consecutive 5 s intervals with a time gap of 50-100 ms. We observed distinct fluorescent emissions from single-, double-, and quadruple-labeled ribosome complexes. Through comprehensive spectrum analysis and correction, we distinguish and correlate conformational changes in two parts of the ribosome, offering additional perspectives on its coordination and timing during translocation. Our setup's versatility, accommodating up to six FRET pairs, suggests broader applications in studying large biomolecules and various biological systems.

Unraveling the complexity: Advanced methods in analyzing DNA, RNA, and protein interactions

Exploring the intricate interplay within and between nucleic acids, as well as their interactions with proteins, holds pivotal significance in unraveling the molecular complexities steering cancer initiation and progression. To investigate these interactions, a diverse array of highly specific and sensitive molecular techniques has been developed. The selection of a particular technique depends on the specific nature of the interactions. Typically, researchers employ an amalgamation of these different techniques to obtain a comprehensive and holistic understanding of inter- and intramolecular interactions involving DNA-DNA, RNA-RNA, DNA-RNA, or protein-DNA/RNA. Examining nucleic acid conformation reveals alternative secondary structures beyond conventional ones that have implications for cancer pathways. Mutational hotspots in cancer often lie within sequences prone to adopting these alternative structures, highlighting the importance of investigating intra-genomic and intra-transcriptomic interactions, especially in the context of mutations, to deepen our understanding of oncology. Beyond these intramolecular interactions, the interplay between DNA and RNA leads to formations like DNA:RNA hybrids (known as R-loops) or even DNA:DNA:RNA triplex structures, both influencing biological processes that ultimately impact cancer. Protein-nucleic acid interactions are intrinsic cellular phenomena crucial in both normal and pathological conditions. In particular, genetic mutations or single amino acid variations can alter a protein's structure, function, and binding affinity, thus influencing cancer progression. It is thus, imperative to understand the differences between wild-type (WT) and mutated (MT) genes, transcripts, and proteins. The review aims to summarize the frequently employed methods and techniques for investigating interactions involving nucleic acids and proteins, highlighting recent advancements and diverse adaptations of each technique.

iMAX FRET (Information Maximized FRET) for Multipoint Single-Molecule Structural Analysis

Understanding the structure of biomolecules is vital for deciphering their roles in biological systems. Single-molecule techniques have emerged as alternatives to conventional ensemble structure analysis methods for uncovering new biology in molecular dynamics and interaction studies, yet only limited structural information could be obtained experimentally. Here, we address this challenge by introducing iMAX FRET, a one-pot method that allows ab initio 3D profiling of individual molecules using two-color FRET measurements. Through the stochastic exchange of fluorescent weak binders, iMAX FRET simultaneously assesses multiple distances on a biomolecule within a few minutes, which can then be used to reconstruct the coordinates of up to four points in each molecule, allowing structure-based inference. We demonstrate the 3D reconstruction of DNA nanostructures, protein quaternary structures, and conformational changes in proteins. With iMAX FRET, we provide a powerful approach to advance the understanding of biomolecular structure by expanding conventional FRET analysis to three dimensions.

Single-molecule detection and super-resolution imaging with a portable and adaptable 3D-printed microscopy platform (Brick-MIC)

Over the past decades, single-molecule and super-resolution microscopy have advanced and represent essential tools for life science research. There is,however, a growing gap between the state-of-the-art and what is accessible to biologists, biochemists, medical researchers or labs with financial constraints. To bridge this gap, we introduce Brick-MIC, a versatile and affordable open-source 3D-printed micro-spectroscopy and imaging platform. Brick-MIC enables the integration of various fluorescence imaging techniques with single-molecule resolution within a single platform and exchange between different modalities within minutes. We here present variants of Brick-MIC that facilitate single-molecule fluorescence detection, fluorescence correlation spectroscopy and super-resolution imaging (STORM and PAINT). Detailed descriptions of the hardware and software components, as well as data analysis routines are provided, to allow non-optics specialist to operate their own Brick-MIC with minimal effort and investments. We foresee that our affordable, flexible, and opensource Brick-MIC platform will be a valuable tool for many laboratories worldwide.

Single-Molecule Imaging of Integral Membrane Protein Dynamics and Function

Integral membrane proteins (IMPs) play central roles in cellular physiology and represent the majority of known drug targets. Single-molecule fluorescence and fluorescence resonance energy transfer (FRET) methods have recently emerged as valuable tools for investigating structure-function relationships in IMPs. This review focuses on the practical foundations required for examining polytopic IMP function using single-molecule FRET (smFRET) and provides an overview of the technical and conceptual frameworks emerging from this area of investigation. In this context, we highlight the utility of smFRET methods to reveal transient conformational states critical to IMP function and the use of smFRET data to guide structural and drug mechanism-of-action investigations. We also identify frontiers where progress is likely to be paramount to advancing the field.

Single-Molecule Electrical Profiling of Peptides and Proteins

In recent decades, there has been a significant increase in the application of single-molecule electrical analysis platforms in studying proteins and peptides. These advanced analysis methods have the potential for deep investigation of enzymatic working mechanisms and accurate monitoring of dynamic changes in protein configurations, which are often challenging to achieve in ensemble measurements. In this work, the prominent research progress in peptide and protein-related studies are surveyed using electronic devices with single-molecule/single-event sensitivity, including single-molecule junctions, single-molecule field-effect transistors, and nanopores. In particular, the successful commercial application of nanopores in DNA sequencing has made it one of the most promising techniques in protein sequencing at the single-molecule level. From single peptides to protein complexes, the correlation between their electrical characteristics, structures, and biological functions is gradually being established. This enables to distinguish different molecular configurations of these biomacromolecules through real-time electrical monitoring of their life activities, significantly improving the understanding of the mechanisms underlying various life processes.

Four Parallel Pathways in T4 Ligase-Catalyzed Repair of Nicked DNA with Diverse Bending Angles

The structural diversity of biological macromolecules in different environments contributes complexity to enzymological processes vital for cellular functions. Fluorescence resonance energy transfer and electron microscopy are used to investigate the enzymatic reaction of T4 DNA ligase catalyzing the ligation of nicked DNA. The data show that both the ligase-AMP complex and the ligase-AMP-DNA complex can have four conformations. This finding suggests the parallel occurrence of four ligation reaction pathways, each characterized by specific conformations of the ligase-AMP complex that persist in the ligase-AMP-DNA complex. Notably, these complexes have DNA bending angles of ≈0°, 20°, 60°, or 100°. The mechanism of parallel reactions challenges the conventional notion of simple sequential reaction steps occurring among multiple conformations. The results provide insights into the dynamic conformational changes and the versatile attributes of T4 DNA ligase and suggest that the parallel multiple reaction pathways may correspond to diverse T4 DNA ligase functions. This mechanism may potentially have evolved as an adaptive strategy across evolutionary history to navigate complex environments.

Recovering true FRET efficiencies from smFRET investigations requires triplet state mitigation

Single-molecule fluorescence resonance energy transfer (smFRET) methods employed to quantify time-dependent compositional and conformational changes within biomolecules require elevated illumination intensities to recover robust photon emission streams from individual fluorophores. Here we show that outside the weak-excitation limit, and in regimes where fluorophores must undergo many rapid cycles of excitation and relaxation, non-fluorescing, excitation-induced triplet states with lifetimes orders of magnitude longer lived than photon-emitting singlet states degrade photon emission streams from both donor and acceptor fluorophores resulting in illumination-intensity-dependent changes in FRET efficiency. These changes are not commonly taken into consideration; therefore, robust strategies to suppress excited state accumulations are required to recover accurate and precise FRET efficiency, and thus distance, estimates. We propose both robust triplet state suppression and data correction strategies that enable the recovery of FRET efficiencies more closely approximating true values, thereby extending the spatial and temporal resolution of smFRET.

Evidence for a compact σ70 conformation in vitro and in vivo

The initiation of transcription in Escherichia coli (E. coli) is facilitated by promoter specificity factors, also known as σ factors, which may bind a promoter only as part of a complex with RNA polymerase (RNAP). By performing in vitro cross-linking mass spectrometry (CL-MS) of apo-σ70, we reveal structural features suggesting a compact conformation compared to the known RNAP-bound extended conformation. Then, we validate the existence of the compact conformation using in vivo CL-MS by identifying cross-links similar to those found in vitro, which deviate from the extended conformation only during the stationary phase of bacterial growth. Conclusively, we provide information in support of a compact conformation of apo-σ70 that exists in live cells, which might represent a transcriptionally inactive form that can be activated upon binding to RNAP.

Unraveling Burst Selection Bias in Single-Molecule FRET of Species with Unequal Brightness and Diffusivity

Single-molecule free diffusion experiments enable accurate quantification of coexisting species or states. However, unequal brightness and diffusivity introduce a burst selection bias and affect the interpretation of experimental results. We address this issue with a photon-by-photon maximum likelihood method, burstML, which explicitly considers burst selection criteria. BurstML accurately estimates parameters, including photon count rates, diffusion times, Förster resonance energy transfer (FRET) efficiencies, and population, even in cases where species are poorly distinguished in FRET efficiency histograms. We develop a quantitative theory that determines the fraction of photon bursts corresponding to each species and thus obtain accurate species populations from the measured burst fractions. In addition, we provide a simple approximate formula for burst fractions and establish the range of parameters where unequal brightness and diffusivity can significantly affect the results obtained by conventional methods. The performance of the burstML method is compared with that of a maximum likelihood method that assumes equal species brightness and diffusivity, as well as standard Gaussian fitting of FRET efficiency histograms, using both simulated and real single-molecule data for cold-shock protein, protein L, and protein G. The burstML method enhances the accuracy of parameter estimation in single-molecule fluorescence studies.

Accounting for fast vs slow exchange in single molecule FRET experiments reveals hidden conformational states

Proteins are dynamic systems whose structural preferences determine their function. Unfortunately, building atomically detailed models of protein structural ensembles remains challenging, limiting our understanding of the relationships between sequence, structure, and function. Combining single molecule Förster resonance energy transfer (smFRET) experiments with molecular dynamics simulations could provide experimentally grounded, all-atom models of a protein's structural ensemble. However, agreement between the two techniques is often insufficient to achieve this goal. Here, we explore whether accounting for important experimental details like averaging across structures sampled during a given smFRET measurement is responsible for this apparent discrepancy. We present an approach to account for this time-averaging by leveraging the kinetic information available from Markov state models of a protein's dynamics. This allows us to accurately assess which timescales are averaged during an experiment. We find this approach significantly improves agreement between simulations and experiments in proteins with varying degrees of dynamics, including the well-ordered protein T4 lysozyme, the partially disordered protein apolipoprotein E (ApoE), and a disordered amyloid protein (Aβ40). We find evidence for hidden states that are not apparent in smFRET experiments because of time averaging with other structures, akin to states in fast exchange in NMR, and evaluate different force fields. Finally, we show how remaining discrepancies between computations and experiments can be used to guide additional simulations and build structural models for states that were previously unaccounted for. We expect our approach will enable combining simulations and experiments to understand the link between sequence, structure, and function in many settings.

Single-Molecule Spectroscopy and Super-Resolution Mapping of Physicochemical Parameters in Living Cells

By superlocalizing the positions of millions of single molecules over many camera frames, a class of super-resolution fluorescence microscopy methods known as single-molecule localization microscopy (SMLM) has revolutionized how we understand subcellular structures over the past decade. In this review, we highlight emerging studies that transcend the outstanding structural (shape) information offered by SMLM to extract and map physicochemical parameters in living mammalian cells at single-molecule and super-resolution levels. By encoding/decoding high-dimensional information-such as emission and excitation spectra, motion, polarization, fluorescence lifetime, and beyond-for every molecule, and mass accumulating these measurements for millions of molecules, such multidimensional and multifunctional super-resolution approaches open new windows into intracellular architectures and dynamics, as well as their underlying biophysical rules, far beyond the diffraction limit.

Trapping and recapturing single DNA molecules with pore-cavity-pore device

Single-molecule detection technology is a technique capable of detecting molecules at the single-molecule level, characterized by high sensitivity, high resolution, and high specificity. Nanopore technology, as one of the single-molecule detection tools, is widely used to study the structure and function of biomolecules. In this study, we constructed a small-sized nanopore with a pore-cavity-pore structure, which can achieve a higher reverse capture rate. Through simulation, we investigated the electrical potential distribution of the nanopore with a pore-cavity-pore structure and analyzed the influence of pore size on the potential distribution. Accordingly, different pore sizes can be designed based on the radius of gyration of the target biomolecules, restricting their escape paths inside the chamber. In the future, nanopores with a pore-cavity-pore structure based on two-dimensional thin film materials are expected to be applied in single-molecule detection research, which provides new insights for various detection needs.

Pulsed-Interleaved-Excitation Two-Dimensional Fluorescence Lifetime Correlation Spectroscopy

We report on pulsed-interleaved-excitation two-dimensional fluorescence lifetime correlation spectroscopy (PIE 2D FLCS) to study biomolecular structural dynamics with high sensitivity and high time resolution using Förster resonance energy transfer (FRET). PIE 2D FLCS is an extension of 2D FLCS, which is a unique single-molecule fluorescence method that uses fluorescence lifetime information to distinguish different fluorescence species in equilibrium and resolves their interconversion dynamics with a submicrosecond time resolution. Because 2D FLCS has used only a single-color excitation so far, it was difficult to distinguish a very low-FRET (or zero-FRET) species from only donor-labeled species. We overcome this difficulty by implementing the PIE scheme (i.e., alternate excitation of the donor and acceptor dyes using two temporally interleaved excitations with different colors) to 2D FLCS, realizing two-color excitation and two-color fluorescence detection in 2D FLCS. After proof-of-principle PIE 2D FLCS analysis on the photon data synthesized with Monte Carlo simulation, we apply PIE 2D FLCS to a DNA-hairpin sample and show that this method readily distinguishes four fluorescent species, i.e., high-FRET, low-FRET, and two single-dye-labeled species. In addition, we show that PIE 2D FLCS can also quantitatively evaluate the contributions of the donor-acceptor spectral crosstalk, which often appears as artifacts in FRET studies and degrades the information obtained.

Microwave analogy of Förster resonance energy transfer and effect of finite antenna length

The near-field interaction between quantum emitters, governed by Förster resonance energy transfer (FRET), plays a pivotal role in nanoscale energy transfer mechanisms. However, FRET measurements in the optical regime are challenging as they require nanoscale control of the position and orientation of the emitters. To overcome these challenges, microwave measurements were proposed for enhanced spatial resolution and precise orientation control. However, unlike in optical systems for which the dipole can be taken to be infinitesimal in size, the finite size of microwave antennas can affect energy transfer measurements, especially at short distances. This highlights the necessity to consider the finite antenna length to obtain accurate results. In this study, we advance the understanding of dipole-dipole energy transfer in the microwave regime by developing an analytical model that explicitly considers finite antennas. Unlike previous works, our model calculates the mutual impedance of finite-length thin-wire dipole antennas without assuming a uniform current distribution. We validate our analytical model through experiments investigating energy transfer between antennas placed adjacent to a perfect electric conductor mirror. This allows us to provide clear guidelines for designing microwave experiments, distinguishing conditions where finite-size effects can be neglected and where they must be taken into account. Our study not only contributes to the fundamental physics of energy transfer but also opens avenues for microwave antenna impedance-based measurements to complement optical FRET experiments and quantitatively explore dipole-dipole energy transfer in a wider range of conditions.

The substrate-binding domains of the osmoregulatory ABC importer OpuA transiently interact

Bacteria utilize various strategies to prevent internal dehydration during hypertonic stress. A common approach to countering the effects of the stress is to import compatible solutes such as glycine betaine, leading to simultaneous passive water fluxes following the osmotic gradient. OpuA from Lactococcus lactis is a type I ABC-importer that uses two substrate-binding domains (SBDs) to capture extracellular glycine betaine and deliver the substrate to the transmembrane domains for subsequent transport. OpuA senses osmotic stress via changes in the internal ionic strength and is furthermore regulated by the 2nd messenger cyclic-di-AMP. We now show, by means of solution-based single-molecule FRET and analysis with multi-parameter photon-by-photon hidden Markov modeling, that the SBDs transiently interact in an ionic strength-dependent manner. The smFRET data are in accordance with the apparent cooperativity in transport and supported by new cryo-EM data of OpuA. We propose that the physical interactions between SBDs and cooperativity in substrate delivery are part of the transport mechanism.

Exploiting halide perovskites for heavy metal ion detection

Heavy metal ions such as mercury (Hg), copper (Cu), and cadmium (Cd) pose significant threats to ecosystems and human health due to their toxicity and bioaccumulation potential. With growing environmental concerns over heavy metal ion pollution, there is an urgent need to develop efficient detection methods for safeguarding public health and the environment. Various materials, including polymers, nanomaterials, and porous substances, have been used for heavy metal ion detection and have shown promising performance for different scenarios. However, each of these materials has certain limitations as probes. Metal halide perovskites (MHPs), known for their exceptional optoelectronic properties and high structural and chemical tunability, have gained great attention in applications such as photovoltaics and LEDs. Yet, their potential as metal ion probes remains rarely explored. This review assesses MHPs as prospective materials for heavy metal ion detection, taking their structure, chemical properties, and responses to external stimuli into consideration. Three key detection mechanisms-cation exchange (CE), electron transfer (ET), and fluorescence resonance energy transfer (FRET), are explored to understand how metal ions trigger fluorescence changes on perovskites, enabling their detection. Finally, current avenues of developing perovskite probes are discussed, which include exploration of lead-free perovskites to mitigate environmental concerns arising from lead leakage and the pursuit of achieving high-sensitivity and stable detection in aqueous media, summarizing the existing and promising strategies in this field.

A practical guide to time-resolved fluorescence microscopy and spectroscopy

Time-correlated single photon counting (TCSPC) coupled with confocal microscopy is a versatile biophysical tool that enables real-time monitoring of biomolecular dynamics across many timescales. With TCSPC, Fluorescence correlation spectroscopy (FCS) and pulsed interleaved excitation-Förster resonance energy transfer (PIE-FRET) are collected simultaneously on diffusing molecules to extract diffusion characteristics and proximity information. This article is a guide to calibrating FCS and PIE-FRET measurements with several biological samples including liposomes, streptavidin-coated quantum dots, proteins, and nucleic acids for reliable determination of diffusion coefficients and FRET efficiency. The FRET efficiency results are also compared to surface-attached single molecules using fluorescence lifetime imaging microscopy (FLIM-FRET). Combining the methods is a powerful approach to revealing mechanistic details of biological processes and pathways.

CombFold: predicting structures of large protein assemblies using a combinatorial assembly algorithm and AlphaFold2

Deep learning models, such as AlphaFold2 and RosettaFold, enable high-accuracy protein structure prediction. However, large protein complexes are still challenging to predict due to their size and the complexity of interactions between multiple subunits. Here we present CombFold, a combinatorial and hierarchical assembly algorithm for predicting structures of large protein complexes utilizing pairwise interactions between subunits predicted by AlphaFold2. CombFold accurately predicted (TM-score >0.7) 72% of the complexes among the top-10 predictions in two datasets of 60 large, asymmetric assemblies. Moreover, the structural coverage of predicted complexes was 20% higher compared to corresponding Protein Data Bank entries. We applied the method on complexes from Complex Portal with known stoichiometry but without known structure and obtained high-confidence predictions. CombFold supports the integration of distance restraints based on crosslinking mass spectrometry and fast enumeration of possible complex stoichiometries. CombFold's high accuracy makes it a promising tool for expanding structural coverage beyond monomeric proteins.

The copious photochemistry of 2,6-diaminopurine: Luminescence, triplet population, and ground state recovery

9H- and 7H-2,6-Diaminopurine (26DAP) photoinduced events in vacuum were studied at the MS-CASPT2/cc-pVDZ level of theory. The S1 1 (ππ* La ) state is initially populated evolving barrierless towards its minimum energy structure, from where two photochemical events can take place in both tautomers. The first is the return of the electronic population to the ground state via the C6 conical intersection (CI-C6). The second involves an internal conversion to the ground through the C2 conical intersection (CI-C2). According to our geodesic interpolated paths connecting the critical structures, the second route is less favorable in both tautomers, due to the presence of high energy barriers. Our calculations suggest a competition between fluorescence and ultrafast relaxation to the electronic ground state via internal conversion process. Based on our calculated potential energy surfaces and experimental excited state lifetimes from the literature, we can infer that the 7H- must have a greater fluorescence yield than the 9H-tautomer. We also explored the triplet state population mechanisms on the 7H-26DAP to understand their long-lived components observed experimentally.

Fractional Extended Diffusion Theory to capture anomalous relaxation from biased/accelerated molecular simulations

Biased and accelerated molecular simulations (BAMS) are widely used tools to observe relevant molecular phenomena occurring on time scales inaccessible to standard molecular dynamics, but evaluation of the physical time scales involved in the processes is not directly possible from them. For this reason, the problem of recovering dynamics from such kinds of simulations is the object of very active research due to the relevant theoretical and practical implications of dynamics on the properties of both natural and synthetic molecular systems. In a recent paper [A. Rapallo et al., J. Comput. Chem. 42, 586-599 (2021)], it has been shown how the coupling of BAMS (which destroys the dynamics but allows to calculate average properties) with Extended Diffusion Theory (EDT) (which requires input appropriate equilibrium averages calculated over the BAMS trajectories) allows to effectively use the Smoluchowski equation to calculate the orientational time correlation function of the head-tail unit vector defined over a peptide in water solution. Orientational relaxation of this vector is the result of the coupling of internal molecular motions with overall molecular rotation, and it was very well described by correlation functions expressed in terms of weighted sums of suitable time-exponentially decaying functions, in agreement with a Brownian diffusive regime. However, situations occur where exponentially decaying functions are no longer appropriate to capture the actual dynamical behavior, which exhibits persistent long time correlations, compatible with the so called subdiffusive regimes. In this paper, a generalization of EDT will be given, exploiting a fractional Smoluchowski equation (FEDT) to capture the non-exponential character observed in the relaxation of intramolecular distances and molecular radius of gyration, whose dynamics depend on internal molecular motions only. The calculation methods, proper to EDT, are adapted to implement the generalization of the theory, and the resulting algorithm confirms FEDT as a tool of practical value in recovering dynamics from BAMS, to be used in general situations, involving both regular and anomalous diffusion regimes.

DNA binding redistributes activation domain ensemble and accessibility in pioneer factor Sox2

More than 1600 human transcription factors orchestrate the transcriptional machinery to control gene expression and cell fate. Their function is conveyed through intrinsically disordered regions (IDRs) containing activation or repression domains but lacking quantitative structural ensemble models prevents their mechanistic decoding. Here we integrate single-molecule FRET and NMR spectroscopy with molecular simulations showing that DNA binding can lead to complex changes in the IDR ensemble and accessibility. The C-terminal IDR of pioneer factor Sox2 is highly disordered but its conformational dynamics are guided by weak and dynamic charge interactions with the folded DNA binding domain. Both DNA and nucleosome binding induce major rearrangements in the IDR ensemble without affecting DNA binding affinity. Remarkably, interdomain interactions are redistributed in complex with DNA leading to variable exposure of two activation domains critical for transcription. Charged intramolecular interactions allowing for dynamic redistributions may be common in transcription factors and necessary for sensitive tuning of structural ensembles.