Large Biomolecules Research Articles

Ab initio characterization of protein molecular dynamics with AI2BMD.

Biomolecular dynamics simulation is a fundamental technology for life sciences research, and its usefulness depends on its accuracy and efficiency1-3. Classical molecular dynamics simulation is fast but lacks chemical accuracy4,5. Quantum chemistry methods such as density functional theory can reach chemical accuracy but cannot scale to support large biomolecules6. Here we introduce an artificial intelligence-based ab initio biomolecular dynamics system (AI2BMD) that can efficiently simulate full-atom large biomolecules with ab initio accuracy. AI2BMD uses a protein fragmentation scheme and a machine learning force field7 to achieve generalizable ab initio accuracy for energy and force calculations for various proteins comprising more than 10,000 atoms. Compared to density functional theory, it reduces the computational time by several orders of magnitude. With several hundred nanoseconds of dynamics simulations, AI2BMD demonstrated its ability to efficiently explore the conformational space of peptides and proteins, deriving accurate 3J couplings that match nuclear magnetic resonance experiments, and showing protein folding and unfolding processes. Furthermore, AI2BMD enables precise free-energy calculations for protein folding, and the estimated thermodynamic properties are well aligned with experiments. AI2BMD could potentially complement wet-lab experiments, detect the dynamic processes of bioactivities and enable biomedical research that is impossible to conduct at present.

Transformative personalized oxalate biomarker analysis through a wrist-worn microneedle device integrated with duplex nanozyme toolbox

The interstitial fluid (ISF) is valuable for disease diagnosis due to its unique biomarkers. Microneedles (MNs) offer a painless method for ISF sampling, facilitating primary diagnostics. This study introduces a minimally invasive, biocompatible MN patch made from a swellable hydrogel of polyvinyl alcohol (PVA) and polyvinyl pyrrolidone (PVP), which effectively extracts ISF. The hydrogel selectively permits small molecules like oxalate, a kidney disease biomarker, while blocking large biomolecules. The MN patch is integrated with a multilayer sensor via microfluidic channels, featuring cotton fiber, agarose, and Mn3[Fe(CN)6]2, alongside Fe3[Fe(CN)6]3 (AGH-CP/MnFeCN/FeFeCN). These nanozymes exhibit oxidase-like activity, reacting with 3,3′,5,5′-tetramethylbenzidine (TMB) to indicate oxalate levels through a color change from green (no oxalate) to light or dark blue, based on concentration. The designed sensor demonstrates high performance with a detection limit of 0.897 μM and an RSD of 1.22 %, enabling accurate quantification via smartphone image analysis as readout platforms for more accessibility and user-friendliness which helps to reach personalized healthcare goals. This integration facilitates real-time, remote, precise disease detection, biochemical analysis and forsooth miniaturization, leading to the development of portable, flexible, and wearable sensors. The MN patch and integrated sensor show excellent stability, selectivity, sensitivity, reliability, and long-term durability. This minimally invasive sensing system, designed for wristband integration, opens new avenues for precision point-of-care monitoring, enhancing personal healthcare.

BEMM-GEN: A Toolkit for Generating a Biomolecular Environment-Mimicking Model for Molecular Dynamics Simulation.

Understanding the influence of the cellular environment on protein conformations is crucial for elucidating protein functions within living cells. In studies using molecular dynamics (MD) simulation, carbon nanotubes and hydrophobic cages have been widely used to emulate the cellular environment inside specific large biomolecules such as ribosome tunnels and chaperones. However, recent studies suggest that these uniform hydrophobic models may not adequately capture the environmental effects inside each biomolecule. Based on these facts, it is necessary to generate spherical and cylindrical models with varied chemical properties corresponding to the components within target biomolecules. We developed a biomolecular environment-mimicking model generator (BEMM-GEN) that generates spherical and cylindrical models with user-specified chemical properties and allows the integration of arbitrary protein conformations into the generated models. BEMM-GEN provides model and protein complex structures, along with the corresponding parameter files for MD simulation (AMBER and GROMACS), and users immediately run their MD simulation based on the generated input files. BEMM-GEN can be freely downloaded and installed via a Python package manager (pip install BEMM-gen). The source code files and a user manual for operation are provided on GitHub (https://github.com/y4suda/BEMM-GEN).

Equimolar Cross-Coupling Using Reactive Coiled Coils for Covalent Protein Assemblies.

Biocompatible cross-coupling reactions enable the efficient covalent attachment of large biomolecules at near-stoichiometric ratios, ensuring the stability and integrity of the resulting products. We present an affinity-based peptide platform utilizing coiled coils containing reactive side chains for proximity-driven protein cross-coupling in the presence of a cross-linking agent. This platform supports both chemical synthesis and recombinant expression, using canonical amino acids to generate reactive affinity tags. Employing the E3/R3 coiled coil pair as a scaffold, we design four complementary coils with cysteine residues as cross-linking sites, achieving >90% conversion to covalent heterodimeric coupling products using 3,4-dibromomaleimide. Equimolar mixtures of proteins with reactive coils at their termini yield near-quantitative heterodimeric cross-coupling products. The strategic selection of complementary coiled coil pairs and cross-linking agents enables orthogonal assembly of macromolecules with diverse architectures. This method offers a versatile approach for creating covalent fusion proteins, enhancing their stability and functionality for applications in chemical biology, biotechnology, and medicine.

Imaged Capillary Isoelectric Focusing Coupled to High-Resolution Mass Spectrometry (icIEF-MS) for Cysteine-Linked Antibody-Drug Conjugate (ADC) Heterogeneity Characterization Under Native Condition.

Native mass spectrometry (nMS) is a cutting-edge technique that leverages electrospray ionization MS (ESI-MS) to investigate large biomolecules and their complexes in solution. The goal of nMS is to retain the native structural features and interactions of the analytes during the transition to the gas phase, providing insights into their natural conformations. In biopharmaceutical development, nMS serves as a powerful tool for analyzing complex protein heterogeneity, allowing for the examination of non-covalently bonded assemblies in a state that closely resembles their natural folded form. Herein, we present an imaged capillary isoelectric focusing-MS (icIEF-MS) workflow to characterize cysteine-linked antibody-drug conjugate (ADC) under native conditions. Two ADCs were analyzed: a latest generation cysteine-linked ADC polatuzumab vedotin and the first FDA-approved cysteine-linked ADC brentuximab vedotin. This workflow benefits from a recently developed icIEF system that is MS-friendly and capable of directly coupling to a high-sensitivity MS instrument. Results show that the icIEF separation is influenced by both drug payloads and the post-translational modifications (PTMs), which are then promptly identified by MS. Overall, this native icIEF-MS method demonstrates the potential to understand and control the critical quality attributes (CQAs) that are essential for the safe and effective use of ADCs.

Nuclear Type I Myosins are Essential for Life and Genome Organization.

The active transport of large biomolecules within a cell is critical for homeostasis. While the cytoplasmic process is well-studied, how the spacing of nucleoplasmic cargo is coordinated is poorly understood. We investigated the impact of myosin motors in the nucleus of budding yeast. We found that life requires a nuclear type I myosin whereas the essential type II or V myosins were not requisite in the nucleus. Nuclear depletion of type I myosins triggered 3D genome disorganization, nucleolar disruption, broad gene expression changes, and nuclear membrane morphology collapse. Genome disorganization occurred first supporting a model where type I myosins actively maintain genome architecture that scaffolds nuclear membrane and nucleolar morphologies. Overall, nuclear myosin is critical for the form and function of the nucleus.

Sulfation pathways in the maintenance of functional beta-cell mass and implications for diabetes.

Diabetes Type 1 and Type 2 are widely occurring diseases. In spite of a vast amount of biomedical literature about diabetic processes in general, links to certain biological processes are only becoming evident these days. One such area of biology is the sulfation of small molecules, such as steroid hormones or metabolites from the gastrointestinal tract, as well as larger biomolecules, such as proteins and proteoglycans. Thus, modulating the physicochemical propensities of the different sulfate acceptors, resulting in enhanced solubility, expedited circulatory transit, or enhanced macromolecular interaction. This review lists evidence for the involvement of sulfation pathways in the maintenance of functional pancreatic beta-cell mass and the implications for diabetes, grouped into various classes of sulfated biomolecule. Complex heparan sulfates might play a role in the development and maintenance of beta-cells. The sulfolipids sulfatide and sulfo-cholesterol might contribute to beta-cell health. In beta-cells, there are only very few proteins with confirmed sulfation on some tyrosine residues, with the IRS4 molecule being one of them. Sulfated steroid hormones, such as estradiol-sulfate and vitamin-D-sulfate, may facilitate downstream steroid signaling in beta-cells, following de-sulfation. Indoxyl sulfate is a metabolite from the intestine, that causes kidney damage, contributing to diabetic kidney disease. Finally, from a technological perspective, there is heparan sulfate, heparin, and chondroitin sulfate, that all might be involved in next-generation beta-cell transplantation. Sulfation pathways may play a role in pancreatic beta-cells through multiple mechanisms. A more coherent understanding of sulfation pathways in diabetes will facilitate discussion and guide future research.

Yeast Surface-Displayed Quenchbody as a Novel Whole-Cell Biosensor for One-Step Detection of Influenza A (H1N1) Virus.

Timely surveillance of airborne pathogens is essential to preventing the spread of infectious diseases and safeguard human health. Methods for sensitive, efficient, and cost-effective detection of airborne viruses are needed. With advances in synthetic biology, whole-cell biosensors have emerged as promising platforms for environmental monitoring and medical diagnostics. However, the current design paradigm of whole-cell biosensors is mostly based on intracellular detection of analytes that can transport across the cell membrane, which presents a critical challenge for viral pathogens and large biomolecules. To address this challenge, we developed a new type of whole-cell biosensor by expressing and displaying VHH-based quenchbody (Q-body) on the surface of the yeast Saccharomyces cerevisiae for simple one-step detection of influenza A (H1N1) virus. Seventeen VHH antibody fragments targeting the hemagglutinin protein H1N1-HA were displayed on the yeast cells and screened for the H1N1-HA binding affinity. The functionally displayed VHHs were selected to create surface-displayed Q-body biosensors. The surface-displayed Q-body exhibiting the highest quenching and dequenching efficiency was identified. The biosensor quantitatively detected H1N1-HA in a range from 0.5 to 16 μg/mL, with a half-maximal concentration of 2.60 μg/mL. The biosensor exhibited high specificity for H1N1-HA over other hemagglutinin proteins from various influenza A virus subtypes. Moreover, the biosensor succeeded in detecting the H1N1 virus at concentrations from 2.4 × 104 to 1.5 × 107 PFU/mL. The results from this study demonstrated a new whole-cell biosensor design that circumvents the need for transport of analytes into biosensor cells, enabling efficient detection of the target virus particles.

Dynamics of the Aspiration of Charged Droplets into a LC-ESI-MS System.

Electrospray ionization (ESI) enables coupling between liquid chromatography (LC) and mass spectrometry (MS). Since it is a gentle ionization method, it is frequently used for the analysis of large biomolecules. In recent years, several experimental setups have demonstrated that the use of ESI results in the formation of charged droplets that are aspirated into the vacuum systems of mass spectrometers. This results in a variety of consequences, such as instrument contamination, which can impede the analytical performance. We investigate the signatures of aspirated charged droplets with a commercial LC-ESI-MS system at analytical conditions. Previous observations without LC coupling are reproduced and show that significant droplet aspiration is probably taking place at analytical LC-ESI-MS conditions. This common phenomenon likely decreases the instrument sensitivity. Analyte can be released by isolation and fragmentation of droplet fragments; thus, aspirated droplets can mask analyte even in the mass analyzer region. The complex morphology of droplet MS/MS mass spectra is highly reproducible at the same experimental conditions. This implies the existence of distinct molecular reaction pathways of the droplet fragments. To assess the effect of droplet aspiration on analytical applications, relevant method and ion source parameters, which are commonly varied during method optimization, were investigated. Further variations of the solvent composition revealed that the aspirated droplets and their fragmentation are particularly sensitive to the solvent composition and thus also to the LC solvent gradient in an analytical experiment.

Integrating, Validating, and Expanding Information Space in Single-Molecule Surface-Enhanced Raman Spectroscopy for Biomolecules.

Single-molecule surface-enhanced Raman spectroscopy (SM-SERS) is an ultrahigh-resolution spectroscopic method for directly obtaining the complex vibrational mode information on individual molecules. SM-SERS offers a wide range of submolecular information on the hidden heterogeneity in its functional groups and varying structures, dynamics of conformational changes, binding and reaction kinetics, and interactions with the neighboring molecule and environment. Despite the richness in information on individual molecules and potential of SM-SERS in various detection targets, including large and complex biomolecules, several issues and practical considerations remain to be addressed, such as the requirement of long integration time, challenges in forming reliable and controllable interfaces between nanostructures and biomolecules, difficulty in determining hotspot size and shape, and most importantly, insufficient signal reproducibility and stability. Moreover, utilizing and interpreting SERS spectra is challenging, mainly because of the complexity and dynamic nature of molecular fingerprint Raman spectra, and this leads to fragmentary analysis and incomplete understanding of the spectra. In this Perspective, we discuss the current challenges and future opportunities of SM-SERS in views of system approaches by integrating molecules of interest, Raman dyes, plasmonic nanostructures, and artificial intelligence, particularly for detecting and analyzing biomolecules to realize the validation and expansion of information space in SM-SERS.

CO2 Fixation to Prebiotic Intermediates over Heterogeneous Catalysts.

ConspectusThe study of the origin of life requires a multifaceted approach to understanding where and how life arose on Earth. One of the most compelling hypotheses is the chemosynthetic origin of life at hydrothermal vents, as this condition has been considered viable for early forms of life. The continuous production of H2 and heat by serpentinization generates reductive conditions at hydrothermal vents, in which CO2 can be used to build large biomolecules. Although this involves surface catalysis and an autocatalytic process, in which solid minerals act as catalysts in the conversion of CO2 to metabolically important organic molecules, the systematic investigation of heterogeneous catalysis to comprehend prebiotic chemistry at hydrothermal vents has not been undertaken.In this Account, we discuss geochemical CO2 fixation to metabolic intermediates by synthetic minerals at hydrothermal vents from the perspective of heterogeneous catalysis. Ni and Fe are the most abundant transition metals at hydrothermal vents and occur in the active site of the enzymes carbon monoxide dehydrogenases/acetyl coenzyme A synthases (CODH/ACS). Synthetic free-standing NiFe alloy nanoparticles can convert CO2 to acetyl coenzyme A pathway intermediates such as formate, acetate, and pyruvate. The same alloy can further convert pyruvate to citramalate, which is essential in the biological citramalate pathway. Thermal treatment of Ni3Fe nanoparticles under NH3, which can occur in hydrothermal vents, results in Ni3FeN/Ni3Fe heterostructures. This catalyst has been demonstrated to produce prebiotic formamide and acetamide from CO2 and H2O using Ni3FeN/Ni3Fe as both substrate and catalyst. In the process of serpentinization, Co can be reduced in the vicinity of olivine, a Mg-Fe silicate mineral. This produces CoFe and CoFe2 with serpentine in nature, representing SiO2-supported CoFe alloys. In mimicking these natural minerals, synthetic SiO2-supported CoFe alloys demonstrate the same liquid products as NiFe alloys, namely, formate, acetate, and pyruvate under mild hydrothermal vent conditions. In contrast to the NiFe system, hydrocarbons up to C6 were detected in the gas phase, which is also present in hydrothermal vents. The addition of alkali and alkaline-earth metals to the catalysts results in enhanced formate concentration, playing a promotional role in CO2 reduction. Finally, Co was loaded onto ordered mesoporous SiO2 after modification with cations to simulate the minerals found in hydrothermal vents. These catalysts were then investigated under diminished H2O concentration, revealing the conversion of CO2 to CO, CH4, methanol, and acetate. Notably, the selectivity to metabolically relevant methanol was enhanced in the presence of cations that could generate and stabilize the methoxy intermediate. Calculation using the machine learning approach revealed the possibility of predicting the selectivity of CO2 fixation when modifying mesoporous SiO2 supports with heterocations. Our research demonstrates that minerals at hydrothermal vents can convert CO2 into metabolites under a variety of prebiotic conditions, potentially paving the way for modern biological CO2 fixation processes.

MiMiC: A high-performance framework for multiscale molecular dynamics simulations.

MiMiC is a framework for performing multiscale simulations in which loosely coupled external programs describe individual subsystems at different resolutions and levels of theory. To make it highly efficient and flexible, we adopt an interoperable approach based on a multiple-program multiple-data (MPMD) paradigm, serving as an intermediary responsible for fast data exchange and interactions between the subsystems. The main goal of MiMiC is to avoid interfering with the underlying parallelization of the external programs, including the operability on hybrid architectures (e.g., CPU/GPU), and keep their setup and execution as close as possible to the original. At the moment, MiMiC offers an efficient implementation of electrostatic embedding quantum mechanics/molecular mechanics (QM/MM) that has demonstrated unprecedented parallel scaling in simulations of large biomolecules using CPMD and GROMACS as QM and MM engines, respectively. However, as it is designed for high flexibility with general multiscale models in mind, it can be straightforwardly extended beyond QM/MM. In this article, we illustrate the software design and the features of the framework, which make it a compelling choice for multiscale simulations in the upcoming era of exascale high-performance computing.

Raman spectroscopy in lung cancer diagnostics: Can an in vivo setup compete with ex vivo applications?

Lung carcinoma remains the leading cause of cancer death worldwide. The tactic to change this unfortunate rate may be a timely and rapid diagnostic, which may in many cases improve patient prognosis.In our study, we focus on the comparison of two novel methods of rapid lung carcinoma diagnostics, label-free in vivo and ex vivo Raman spectroscopy of the epithelial tissue, and assess their feasibility in clinical practice. As these techniques are sensitive not only to the basic molecular composition of the analyzed sample but also to the secondary structure of large biomolecules, such as tissue proteins, they represent suitable candidate methods for epithelial cancer diagnostics.During routine bronchoscopy, we collected 78 in vivo Raman spectra of normal and cancerous lung tissue and 37 samples of endobronchial pathologies, which were subsequently analyzed ex vivo. Using machine learning techniques, namely principal component analysis (PCA) and support vector machines (SVM), we were able to reach 87.2% (95% CI, 79.8–94.6%) and 100.0% (95% CI, 92.1–100.0%) of diagnostic accuracy for in vivo and ex vivo setup, respectively. Although the ex vivo approach provided superior results, the rapidity of in vivo Raman spectroscopy might become unmatchable in the acceleration of the diagnostic process.

Solution-state methyl NMR spectroscopy of large non-deuterated proteins enabled by deep neural networks

Methyl-TROSY nuclear magnetic resonance (NMR) spectroscopy is a powerful technique for characterising large biomolecules in solution. However, preparing samples for these experiments is demanding and entails deuteration, limiting its use. Here we demonstrate that NMR spectra recorded on protonated, uniformly 13C labelled samples can be processed using deep neural networks to yield spectra that are of similar quality to typical deuterated methyl-TROSY spectra, potentially providing information for proteins that cannot be produced in bacterial systems. We validate the methodology experimentally on three proteins with molecular weights in the range 42–360 kDa. We further demonstrate the applicability of our methodology to 3D NOESY spectra of Escherichia coli Malate Synthase G (81 kDa), where observed NOE cross-peaks are in good agreement with the available structure. The method represents an advance in the field of using deep learning to analyse complex magnetic resonance data and could have an impact on the study of large biomolecules in years to come.

Investigating the Mechanism of Aluminum Fluoride Chelation.

Aluminum fluoride (AlF) complexes have been used over the past decade to incorporate [18F]fluoride into large biomolecules in a highly selective fashion by using relatively facile conditions. However, despite their widespread usage, there are a large number of variations in the reaction conditions, without a definitive discussion provided on the mechanism to understand how these changes would alter the end result. Herein, we report a detailed mechanistic investigation of the reaction, using a mixture of theoretical studies, fluorine-19 and fluorine-18 chemistry, and the consequences it has on the efficient clinical translation of AlF-containing imaging agents.

Programmable RNA Loading of Extracellular Vesicles with Toehold-Release Purification.

Synthetic nanoparticles as lipid nanoparticles (LNPs) are widely used as drug delivery vesicles. However, they hold several drawbacks, including low biocompatibility and unfavorable immune responses. Naturally occurring extracellular vesicles (EVs) hold the potential as native, safe, and multifunctional nanovesicle carriers. However, loading of EVs with large biomolecules remains a challenge. Here, we present a controlled loading methodology using DNA-mediated and programmed fusion between EVs and messenger RNA (mRNA)-loaded liposomes. The fusion efficiency is characterized at the single-particle level by real-time microscopy through EV surface immobilization via lipidated biotin-DNA handles. Subsequently, fused EV-liposome particles (EVLs) can be collected by employing a DNA strand-replacement reaction. Transferring the fusion reaction to magnetic beads enables us to scale up the production of EVLs one million times. Finally, we demonstrated encapsulation of mCherry mRNA, transfection, and improved translation using the EVLs compared to liposomes or LNPs in HEK293-H cells. We envision this as an important tool for the EV-mediated delivery of RNA therapeutics.

A potential building block for spintronic devices: Theoretical description of electronic transport and magnetoresistance of catechol under an external magnetic field stimulus

Understanding the electronic transport properties of low-dimensional devices has increased dramatically in recent decades, especially for those with a promising future for application in nanotechnology. Among these nanoscopic systems are molecular systems, particularly organic molecules such as catechol, representing the small piece of a potential conductor assembled through larger biomolecules and inserted between two or more metal contacts. In this work, we present a theoretical description of the electronic transport of catechol, based on its π-conjugated aromatic system, under an external magnetic field stimulus, which is transverse to the alignment of the molecule. Thus, we analyze catechol’s spintronic properties through the magnetoresistance generated by this field. We model the molecule using a tight-binding Hamiltonian and Green’s functions; the transmission probability is calculated by means of the Fisher-Lee relation, and the characteristic current–voltage, spin polarization, and magnetoresistance curves based on Landauer’s approach for two linking models of catechol to the metallic contacts. The results suggest a strong dependence on the spin direction of the charge carriers and the Zeeman energy (Ez) on the Fermi level, generating a switch-like mechanism going from conducting to semiconducting material. This behavior opens a potential application of these catechol-based systems in future spintronic devices.

Isoporous Membrane Mediated Imprinting Mass Spectrometry Imaging for Spatially-Resolved Metabolomics and Rapid Histopathological Diagnosis.

Surface-assisted laser desorption/ionization (SALDI) mass spectrometry imaging (MSI) holds great value in spatial metabolomics and tumor diagnosis. Tissue imprinting on the SALDI target can avoid laser-induced tissue ablation and simplifies the sample preparation. However, the tissue imprinting process always causes lateral diffusion of biomolecules, thereby losing the fidelity of metabolite distribution on tissue. Herein, a membrane-mediated imprinting mass spectrometry imaging (MMI-MSI) strategy is proposed using isoporous nuclepore track-etched membrane as a mediating imprinting layer to selectively transport metabolites through uniform and vertical pores onto silicon nanowires (SiNWs) array. Compared with conventional direct imprinting technique, MMI-MSI can not only exclude the adsorption of large biomolecules but also avoid the lateral diffusion of metabolites. The whole time for MMI-based sample preparation can be reduced to 2min, and the lipid peak number can increase from 46 to 113 in kidney tissue detection. Meanwhile, higher resolution of MSI can be achieved due to the confinement effect of the pore channel in the diffusion of metabolites. Based on MMI-MSI, the tumor margins of liver cancer can be clearly discriminated and their different subtypes can be precisely classified. This work demonstrates MMI-MSI is a rapid, highly sensitive, robust and high-resolution technique for spatially-resolved metabolomics and pathological diagnosis.

Expanding Differential Ion Mobility Separations into the MegaDalton Range.

Along with mass spectrometry (MS), ion mobility separations (IMS) are advancing to ever larger biomolecules. The emergence of electrospray ionization (ESI) and native MS enabled the IMS/MS analyses of proteins up to ∼100 kDa in the 1990s and whole protein complexes and viruses up to ∼10 MDa since the 2000s. Differential IMS (FAIMS) is substantially orthogonal to linear IMS based on absolute mobility K and offers exceptional resolution, unique selectivity, and steady filtering readily compatible with slower analytical methods such as electron capture or transfer dissociation (ECD/ETD). However, the associated MS stages had limited FAIMS to ions with m/z < 8000 and masses under ∼300 kDa. Here, we integrate high-definition FAIMS with the Q-Exactive Orbitrap UHMR mass spectrometer that can handle m/z up to 80,000 and MDa-size ions in the native ESI regime. In the initial evaluation, the oligomers of monoclonal antibody adalimumab (148 kDa) are size-selected up to at least the nonamers (1.34 MDa) with m/z values up to ∼17,000. This demonstrates the survival and efficient separation of noncovalent MDa assemblies in the FAIMS process, opening the door to novel analyses of the heaviest macromolecules.

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.