Exploring protein functions from structural flexibility using CABS-flex modeling.

Understanding protein function often necessitates characterizing the flexibility of protein structures. However, simulating protein flexibility poses significant challenges due to the complex dynamics of protein systems, requiring extensive computational resources and accurate modeling techniques. In response to these challenges, the CABS-flex method has been developed as an efficient modeling tool that combines coarse-grained simulations with all-atom detail. Available both as a web server and a standalone package, CABS-flex is dedicated to a wide range of users. The web server version offers an accessible interface for straightforward tasks, while the standalone command-line program is designed for advanced users, providing additional features, analytical tools, and support for handling large systems. This paper examines the application of CABS-flex across various structure-function studies, facilitating investigations into the interplay among protein structure, dynamics, and function in diverse research fields. We present an overview of the current status of the CABS-flex methodology, highlighting its recent advancements, practical applications, and forthcoming challenges.

Simulation-Guided Rational Design of DNA Walker-Based Theranostic Platform.

Biomolecule-functionalized nanoparticles represent a type of promising biomaterials in biomedical applications owing to their excellent biocompatibility and versatility. DNA-based reactions on nanoparticles have enabled emerging applications including intelligent biosensors, drug delivery, and biomimetic devices. Among the reactions, strand hybridization is the critical step to control the sensitivity and specificity of biosensing, and the efficiency of drug delivery. However, a comprehensive understanding of DNA hybridization on nanoparticles is still lacking, which may differ from the process in homogeneous solutions. To address this limitation, coarse-grained model-based molecular dynamic simulation is harnessed to disclose the critical factors involved in intermolecular hybridization. Based on simulation guidance, DNA walker-based smart theranostic platform (DWTP) based on "on-particle" hybridization is developed, showing excellent consistency with simulation. DWTP is successfully applied for highly sensitive miRNA 21 detection and tumor-specific miRNA 21 imaging, driven by tumor-endogenous APE 1 enzyme. It enables the precise release of antisense oligonucleotide triggered by tumor-endogenous dual-switch miRNA 21 and APE 1, facilitating effective gene silencing therapy with high biosafety. The simulation of "on-particle" DNA hybridization has improved the corresponding biosensing performance and the release efficiency of therapeutic agents, representing a conceptually new approach for DNA-based device design.

ABC2A: A Straightforward and Fast Method for the Accurate Backmapping of RNA Coarse-Grained Models to All-Atom Structures.

RNAs play crucial roles in various essential biological functions, including catalysis and gene regulation. Despite the widespread use of coarse-grained (CG) models/simulations to study RNA 3D structures and dynamics, their direct application is challenging due to the lack of atomic detail. Therefore, the reconstruction of full atomic structures is desirable. In this study, we introduced a straightforward method called ABC2A for reconstructing all-atom structures from RNA CG models. ABC2A utilizes diverse nucleotide fragments from known structures to assemble full atomic structures based on the CG atoms. The diversification of assembly fragments beyond standard A-form ones, commonly used in other programs, combined with a highly simplified structure refinement process, ensures that ABC2A achieves both high accuracy and rapid speed. Tests on a recent large dataset of 361 RNA experimental structures (30-692 nt) indicate that ABC2A can reconstruct full atomic structures from three-bead CG models with a mean RMSD of ~0.34 Å from experimental structures and an average runtime of ~0.5 s (maximum runtime < 2.5 s). Compared to the state-of-the-art Arena, ABC2A achieves a ~25% improvement in accuracy and is five times faster in speed.

Multiscale modelling of biomolecular corona formation on metallic surfaces.

In the realm of food industry, the choice of non-consumable materials used plays a crucial role in ensuring consumer safety and product quality. Aluminum is widely used in food packaging and food processing applications, including dairy products. However, the interaction between aluminum and milk content requires further investigation to understand its implications. In this work, we present the results of multiscale modelling of the interaction between various surfaces, that is (100), (110), and (111), of fcc aluminum with the most abundant milk proteins and lactose. Our approach combines atomistic molecular dynamics, a coarse-grained model of protein adsorption, and kinetic Monte Carlo simulations to predict the protein corona composition in the deposited milk layer on aluminum surfaces. We consider a simplified model of milk, which is composed of the six most abundant milk proteins found in natural cow milk and lactose, which is the most abundant sugar found in dairy. Through our study, we ranked selected proteins and lactose adsorption affinities based on their corresponding interaction strength with aluminum surfaces and predicted the content of the naturally forming biomolecular corona. Our comprehensive investigation sheds light on the implications of aluminum in food processing and packaging, particularly concerning its interaction with the most abundant milk proteins and lactose. By employing a multiscale modelling approach, we simulated the interaction between metallic aluminum surfaces and the proteins and lactose, considering different crystallographic orientations. The results of our study provide valuable insights into the mechanisms of lactose and protein deposition on aluminum surfaces, which can aid in the general understanding of protein corona formation.

Energy landscapes for proteins described by the UNRES coarse-grained potential.

The self-assembly of proteins is encoded in the underlying potential energy surface (PES), from which we can predict structure, dynamics, and thermodynamic properties. However, the corresponding analysis becomes increasingly challenging with larger protein sizes, due to the computational time required, which grows significantly with the number of atoms. Coarse-grained models offer an attractive approach to reduce the computational cost. In this Feature Article, we describe our implementation of the UNited RESidue (UNRES) coarse-grained potential in the Cambridge energy landscapes software. We have applied this framework to explore the energy landscapes of four proteins that exhibit native states involving different secondary structures. Here we have tested the ability of the UNRES potential to represent the global energy landscape of proteins containing up to 100 amino acid residues. The resulting potential energy landscapes exhibit good agreement with experiment, with low-lying minima close to the PDB geometries and to results obtained using the all-atom AMBER force field. The new program interfaces will allow us to investigate larger biomolecules in future work, using the UNRES potential in combination with all the methodology available in the computational energy landscapes framework.

Quantifying the large-scale chromosome structural dynamics during the mitosis-to-G1 phase transition of cell cycle.

Cell cycle is known to be regulated by the underlying gene network. Chromosomes, which serve as the scaffold for gene expressions, undergo significant structural reorganizations during mitosis. Understanding the mechanism of the cell cycle from the chromosome structural perspective remains a grand challenge. In this study, we applied an integrated theoretical approach to investigate large-scale chromosome structural dynamics during the mitosis-to-G1 phase transition. We observed that the chromosome structural expansion and adaptation of the structural asphericity do not occur synchronously and attributed this behaviour to the unique unloading sequence of the two types of condensins. Furthermore, we observed that the coherent motions between the chromosomal loci are primarily enhanced within the topologically associating domains (TADs) as cells progress to the G1 phase, suggesting that TADs can be considered as both structural and dynamical units for organizing the three-dimensional chromosome. Our analysis also reveals that the quantified pathways of chromosome structural reorganization during the mitosis-to-G1 phase transition exhibit high stochasticity at the single-cell level and show nonlinear behaviours in changing TADs and contacts formed at the long-range regions. Our findings offer valuable insights into large-scale chromosome structural dynamics after mitosis.

Quantifying RNA structures and interactions with a unified reduced chain representation model.

RNA is a pivotal molecule that plays critical roles in various cellular processes. Quantifying RNA structures and interactions is essential to understanding RNA function and developing RNA-based therapeutics. Using a unified five-bead model and a non-redundant database, this paper investigates the structural features and interactions of five commonly occurring RNA motifs, i.e., double-stranded helices, hairpin loops, internal/bulge loops, multi-branched junctions, and single-stranded terminal tails. Analyzing detailed distributions of RNA local structural features and base-base interactions reveals a preference for helical structures in both local backbone structures and base orientations. The interactions between adjacent bases exhibit motif-specific and sequence-dependent characteristics, reflecting the distinct topological constraints imposed by different loop-helix connection modes and the varying pairing and stacking interactions among different sequences. These findings shed light on the stability of RNA helices, emphasizing their significance in providing dominant base pairing and stacking interactions for RNA structures and stability. The four non-helix motifs encompass unpaired nucleotide loops and exhibit diverse base-base interactions, contributing to the structural diversity observed in RNA. Overall, the complexity of RNA structure arises from the intricate interplay of base-base interactions.

Principles of assembly and regulation of condensates of Polycomb repressive complex 1 through phase separation.

Polycomb repressive complex 1 (PRC1) undergoes phase separation to form Polycomb condensates that are multi-component hubs for silencing Polycomb target genes. In this study, we demonstrate that formation and regulation of PRC1 condensates are consistent with the scaffold-client model, where the Chromobox 2 (CBX2) protein behaves as the scaffold while the other PRC1 proteins are clients. Such clients induce a re-entrant phase transition of CBX2 condensates. The composition of the multi-component PRC1 condensates (1) determines the dynamic properties of the scaffold protein; (2) selectively promotes the formation of CBX4-PRC1 condensates while dissolving condensates of CBX6-, CBX7-, and CBX8-PRC1; and (3) controls the enrichment of CBX4-, CBX7-, and CBX8-PRC1 in CBX2-PRC1 condensates and the exclusion of CBX6-PRC1 from CBX2-PRC1 condensates. Our findings uncover how multi-component PRC1 condensates are assembled via an intricate scaffold-client mechanism whereby the properties of the PRC1 condensates are sensitively regulated by its composition and stoichiometry.

Advancing RNA 3D structure prediction: Exploring hierarchical and hybrid approaches in CASP15.

In CASP15, we used an integrated hierarchical and hybrid approach to predict RNA structures. The approach involves three steps. First, with the use of physics-based methods, Vfold2D-MC and VfoldMCPX, we predict the 2D structures from the sequence. Second, we employ template-based methods, Vfold3D and VfoldLA, to build 3D scaffolds for the predicted 2D structures. Third, using the 3D scaffolds as initial structures and the predicted 2D structures as constraints, we predict the 3D structure from coarse-grained molecular dynamics simulations, IsRNA and RNAJP. Our approach was evaluated on 12 RNA targets in CASP15 and ranked second among all the 34 participating teams. The result demonstrated the reliability of our method in predicting RNA 2D structures with high accuracy and RNA 3D structures with moderate accuracy. Further improvements in RNA structure prediction for the next round of CASP may come from the incorporation of the physics-based method with machine learning techniques.

Mesoscale Simulations of Structure Formation in Polyacrylonitrile Nascent Fibers Induced by Binary Solvent Mixture.

Polyacrylonitrile (PAN) is widely used as a raw material for the production of high-modulus carbon fibers, the internal structure of which is directly affected by the spinning of the precursor. Although PAN fibers have been studied for a long time, the formation of their internal structure has not been sufficiently investigated theoretically. This is due to the large number of stages in the process and the parameters controlling them. In this study, we present a mesoscale model describing the evolution of nascent PAN fibers during the coagulation. It is constructed within the framework of a mesoscale dynamic density functional theory. We use the model to study the influence of a combined solvent of dimethyl sulfoxide (DMSO, a good solvent) and water (a non-solvent) on the microstructure of the fibers. A porous structure of PAN is formed as a result of the microphase separation of the polymer and the residual combined solvent at a high water content in the system. The model shows that one of the possible ways to obtain the homogeneous fiber structure is to slow down the coagulation by increasing the amount of good solvent in the system. This result is in agreement with the existing experimental data and confirms the efficiency of the presented model.

SARS-CoV-2 omicron RBD forms a weaker binding affinity to hACE2 compared to Delta RBD in in-silico studies.

The COVID-19 pandemic sparked an unprecedented race in biotechnology in a search for effective therapies and a preventive vaccine. The continued appearance of SARS-CoV-2 variants of concern (VoCs) further swept the world. The entry of SARS-CoV-2 into cells is mediated by binding the receptor-binding domain (RBD) of the S protein to the cell-surface receptor, human angiotensin-converting enzyme 2 (hACE2). In this study, using a coarse-grained force field to parameterize the system, we employed steered-molecular dynamics (SMD) simulations to reveal the binding of SARS-CoV-2 Delta/Omicron RBD to hACE2. Our benchmarked results demonstrate a good correlation between computed rupture force and experimental binding free energy for known protein-protein systems. Moreover, our findings show that the Omicron RBD has a weaker binding affinity to hACE2, consistent with the respective experimental results. This indicates that our method can effectively be applied to other emerging SARS-CoV-2 strains.Communicated by Ramaswamy H. Sarma.

Inorganically Connecting Colloidal Nanocrystals Significantly Improves Mechanical Properties.

Understanding and characterizing the mechanical behavior of colloidal nanocrystal (NC) assemblies are important for developing nanocrystalline materials with exceptional mechanical properties for robust electronic, thermoelectric, photovoltaic, and optoelectronic devices. However, the limited ranges of Young's modulus, hardness, and fracture toughness (≲1-10 GPa, ≲50-500 MPa, and ≲10-50 kPa m1/2, respectively) in as-synthesized NC assemblies present challenges for their mechanical stability and therefore their practical applications. In this work, we demonstrate using a combination of nanoindentation measurements and coarse-grained modeling that the mechanical response of assemblies of as-synthesized NCs is governed by the van der Waals interactions of the organic surface ligands. More importantly, we report tremendous ∼60× enhancements in Young's modulus and hardness and an ∼80× enhancement in fracture toughness of CdSe NC assemblies through a simple inorganic Sn2S64- ligand exchange process. Moreover, our observation of softening in nanocrystalline materials with decreasing CdSe NC diameter is consistent with atomistic simulations.

Coarse-Grained Modeling of EUV Patterning Process Reflecting Photochemical Reactions and Chain Conformations.

Enabling extreme ultraviolet lithography (EUVL) as a viable and efficient sub-10 nm patterning tool requires addressing the critical issue of reducing line edge roughness (LER). Stochastic effects from random and local variability in photon distribution and photochemical reactions have been considered the primary cause of LER. However, polymer chain conformation has recently attracted attention as an additional factor influencing LER, necessitating detailed computational studies with explicit chain representation and photon distribution to overcome the existing approach based on continuum models and random variables. We developed a coarse-grained molecular simulation model for an EUV patterning process to investigate the effect of chain conformation variation and stochastic effects via photon shot noise and acid diffusion on the roughness of the pattern. Our molecular simulation demonstrated that final LER is most sensitive to the variation in photon distributions, while material distributions and acid diffusion rate also impact LER; thus, the intrinsic limit of LER is expected even at extremely suppressed stochastic effects. Furthermore, we proposed and tested a novel approach to improve the roughness by controlling the initial polymer chain orientation.

Organization of the bacterial nucleoid by DNA-bridging proteins and globular crowders.

The genomic DNA of bacteria occupies only a fraction of the cell called the nucleoid, although it is not bounded by any membrane and would occupy a volume hundreds of times larger than the cell in the absence of constraints. The two most important contributions to the compaction of the DNA coil are the cross-linking of the DNA by nucleoid proteins (like H-NS and StpA) and the demixing of DNA and other abundant globular macromolecules which do not bind to the DNA (like ribosomes). The present work deals with the interplay of DNA-bridging proteins and globular macromolecular crowders, with the goal of determining the extent to which they collaborate in organizing the nucleoid. In order to answer this question, a coarse-grained model was developed and its properties were investigated through Brownian dynamics simulations. These simulations reveal that the radius of gyration of the DNA coil decreases linearly with the effective volume ratio of globular crowders and the number of DNA bridges formed by nucleoid proteins in the whole range of physiological values. Moreover, simulations highlight the fact that the number of DNA bridges formed by nucleoid proteins depends crucially on their ability to self-associate (oligomerize). An explanation for this result is proposed in terms of the mean distance between DNA segments and the capacity of proteins to maintain DNA-bridging in spite of the thermal fluctuations of the DNA network. Finally, simulations indicate that non-associating proteins preserve a high mobility inside the nucleoid while contributing to its compaction, leading to a DNA/protein complex which looks like a liquid droplet. In contrast, self-associating proteins form a little deformable network which cross-links the DNA chain, with the consequence that the DNA/protein complex looks more like a gel.

Investigation of Dynamic Impact Responses of Layered Polymer-Graphene Nanocomposite Films Using Coarse-Grained Molecular Dynamics Simulations.

Polymer nanocomposite films have recently shown superior energy dissipation capability through the micro-projectile impact testing method. However, how stress waves interact with nanointerfaces and the underlying deformation mechanisms have remained largely elusive. This paper investigates the detailed stress wave propagation process and dynamic failure mechanisms of layered poly(methyl methacrylate) (PMMA) - graphene nanocomposite films during piston impact through coarse-grained molecular dynamics simulations. The spatiotemporal contours of stress and local density clearly demonstrate shock front, reflected wave, and release wave. By plotting shock front velocity (U s ) against piston velocity (U p ), we find that the linear Hugoniot U s - U p relationship generally observed for bulk polymer systems also applies to the layered nanocomposite system. When the piston reaches a critical velocity, PMMA crazing can emerge at the location where the major reflected wave and release wave meet. We show that the activation of PMMA crazing significantly enhances the energy dissipation ratio of the nanocomposite films, defined as the ratio between the dissipated energy through irreversible deformation and the input kinetic energy. The ratio maximizes at the critical U p when the PMMA crazing starts to develop and then decreases as U p further increases. We also find that a critical PMMA-graphene interfacial strength is required to activate PMMA crazing instead of interfacial separation. Additionally, layer thickness affects the amount of input kinetic energy and dissipated energy of nanocomposite films under impact. This study provides important insights into the detailed dynamic deformation mechanisms and how nanointerfaces/nanostructures affect the energy dissipation capability of layered nanocomposite films.

Influence of Polymer Characteristics on the Self-Assembly of Polymer-Grafted Metal-Organic Framework Particles.

Polymer-grafted metal-organic frameworks (MOFs) can combine the properties of MOFs and polymers into a single, matrix-free composite material. Herein, we examine polymer-grafted MOF particles (using UiO-66 as a model system) to examine how the molecular weight, grafting density, and chemical functionality of the polymer graft affects the preparation of free-standing self-assembled MOF monolayers (SAMMs). The physical properties of the monolayers are influenced by the choice of polymer, and robust, flexible monolayers were achieved more readily with poly(methyl acrylate) when compared to poly(methyl methacrylate) or poly(benzyl methacrylate). Molecular dynamics simulations were carried out to provide insights into the orientation and ordering of MOFs in the monolayers with respect to MOF size, graft length, and hydrophobicity. The relationship between molecular weight and graft density of the polymer brush was investigated and related to polymer brush conformation, offering design rules for further optimizations to balance mechanical strength, MOF weight fraction, and processability for this class of hybrid materials.

Simulation-Assisted Localized DNA Logical Circuits for Cancer Biomarkers Detection and Imaging.

DNA-based nanodevices equipped with localized modules have been promising probes for biomarker detection. Such devices heavily rely on the intramolecular hybridization reaction. However, there is a lack of mechanistic insights into this reaction that limits the sensing speed and sensitivity. A coarse-grained model is utilized to simulate the intramolecular hybridization of localized DNA circuits (LDCs) not only optimizing the performance, but also providing mechanistic insights into the hybridization reaction. The simulation guided-LDCs enable the detection of multiple biomarkers with high sensitivity and rapid speed showing good consistency with the simulation. Fluorescence assays demonstrate that the simulation-guided LDC shows an enhanced sensitivity up to 9.3 times higher than that of the same probes without localization. The detection limits of ATP, miRNA, and APE1 reach 0.14 mM, 0.68 pM, and 0.0074 U mL-1 , respectively. The selected LDC is operated in live cells with good success in simultaneously detecting the biomarkers and discriminating between cancer cells and normal cells. LDC is successfully applied to detect the biomarkers in cancer tissues from patients, allowing the discrimination of cancer/adjacent/normal tissues. This work herein presents a design workflow for DNA nanodevices holding great potential for expanding the applications of DNA nanotechnology in diagnostics and therapeutics.

Exploring the binding kinetics and behaviors of self-aggregated beta-amyloid oligomers to phase-separated lipid rafts with or without ganglioside-clusters.

Lipid binding kinetics and energetics of self-aggregated and disordered beta-amyloid oligomers of various sizes, from solution to lipid raft surfaces, were investigated using MD simulations. Our systems include small (monomers to tetramers) and larger (octamers and dodecamers) oligomers. Our lipid rafts contain saturated and unsaturated phosphatidylcholine (PC), cholesterol, and with or without asymmetrically distributed monosialotetrahexosylganglioside (GM1). All rafts exhibited dynamic and structurally diversified domains including liquid-ordered (Lo), liquid-disordered (Ld), and interfacial Lod domains. For rafts without GM1, all oligomers bound to the Lod domain. For GM1-containing rafts, all small oligomers and most larger oligomers bound specifically to the GM1-clusters embedded in the Lo domain. Lipid-protein binding energies followed an order of GM1 >> unsaturated PC > saturated PC > cholesterol for all rafts. In addition, protein-induced membrane structural disruption increased progressively with the size of the oligomer for the annular lipids surrounding the membrane-bound protein in non-GM1-containing rafts. We propose that the tight binding of beta-amyloid oligomers to the GM1-clusters and the structural perturbation of lipids surrounding the membrane-bound proteins at the Lod domain are early molecular events of the beta-amyloid aggregation process on neuronal membrane surfaces that trigger the onset of Alzheimer's.

Computationally exploring the mechanism of bacteriophage T7 gp4 helicase translocating along ssDNA.

Bacteriophage T7 gp4 helicase has served as a model system for understanding mechanisms of hexameric replicative helicase translocation. The mechanistic basis of how nucleoside 5'-triphosphate hydrolysis and translocation of gp4 helicase are coupled is not fully resolved. Here, we used a thermodynamically benchmarked coarse-grained protein force field, Associative memory, Water mediated, Structure and Energy Model (AWSEM), with the single-stranded DNA (ssDNA) force field 3SPN.2C to investigate gp4 translocation. We found that the adenosine 5'-triphosphate (ATP) at the subunit interface stabilizes the subunit-subunit interaction and inhibits subunit translocation. Hydrolysis of ATP to adenosine 5'-diphosphate enables the translocation of one subunit, and new ATP binding at the new subunit interface finalizes the subunit translocation. The LoopD2 and the N-terminal primase domain provide transient protein-protein and protein-DNA interactions that facilitate the large-scale subunit movement. The simulations of gp4 helicase both validate our coarse-grained protein-ssDNA force field and elucidate the molecular basis of replicative helicase translocation.

Rotational Mechanism of FO Motor in the F-Type ATP Synthase Driven by the Proton Motive Force.

In FOF1 ATP synthase, driven by the proton motive force across the membrane, the FO motor rotates the central rotor and induces conformational changes in the F1 motor, resulting in ATP synthesis. Recently, many near-atomic resolution structural models have been obtained using cryo-electron microscopy. Despite high resolution, however, static information alone cannot elucidate how and where the protons pass through the FO and how proton passage is coupled to FO rotation. Here, we review theoretical and computational studies based on FO structure models. All-atom molecular dynamics (MD) simulations elucidated changes in the protonation/deprotonation of glutamate-the protein-carrier residue-during rotation and revealed the protonation states that form the "water wire" required for long-range proton hopping. Coarse-grained MD simulations unveiled a free energy surface based on the protonation state and rotational angle of the rotor. Hybrid Monte Carlo and MD simulations showed how proton transfer is coupled to rotation.