Folding Model Research Articles

Rarγ-Foxa1 signaling promotes luminal identity in prostate progenitors and is disrupted in prostate cancer.

Retinoic acid (RA) signaling is a master regulator of vertebrate development with crucial roles in body axis orientation and tissue differentiation, including in the reproductive system. However, a mechanistic understanding of how RA signaling governs cell lineage identity is often missing. Here, leveraging prostate organoid technology, we show that RA signaling orchestrates the commitment of adult mouse prostate progenitors to glandular identity, epithelial barrier integrity, and specification of prostatic lumen. RA-dependent RARγ activation promotes the expression of Foxa1, which synergizes with the androgen pathway for luminal expansion, cytoarchitecture and function. FOXA1 mutations are common in prostate and breast cancers, though their pathogenic mechanism is incompletely understood. Combining functional genetics with structural modeling of FOXA1 folding and chromatin binding analyses, we discover that FOXA1F254E255 is a loss-of-function mutation compromising its transcriptional function and luminal fate commitment of prostate progenitors. Overall, we define RA as an instructive signal for glandular identity in adult prostate progenitors. Importantly, we identify cancer-associated FOXA1 indels affecting residue F254 as loss-of-function mutations promoting dedifferentiation of adult prostate progenitors.

Ligand response of guanidine-IV riboswitch at single-molecule level

Riboswitches represent a class of non-coding RNA that possess the unique ability to specifically bind ligands and, in response, regulate gene expression. A recent report unveiled a type of riboswitch, known as the guanidine-IV riboswitch, which responds to guanidine levels to regulate downstream genetic transcription. However, the precise molecular mechanism through which the riboswitch senses its target ligand and undergoes conformational changes remain elusive. This gap in understanding has impeded the potential applications of this riboswitch. To bridge this knowledge gap, our study investigated the conformational dynamics of the guanidine-IV riboswitch RNA upon ligand binding. We employed single-molecule fluorescence resonance energy transfer (smFRET) to dissect the behaviors of the aptamer, terminator, and full-length riboswitch. Our findings indicated that the aptamer portion exhibited higher sensitivity to guanidine compared to the terminator and full-length constructs. Additionally, we utilized Position-specific Labelling of RNA (PLOR) combined with smFRET to observe, at the single-nucleotide and single-molecule level, the structural transitions experienced by the guanidine-IV riboswitch during transcription. Notably, we discovered that the influence of guanidine on the riboswitch RNA’s conformations was significantly reduced after the transcription of 88 nucleotides. Furthermore, we proposed a folding model for the guanidine-IV riboswitch in the absence and presence of guanidine, thereby providing insights into its ligand-response mechanism.

Ligand response of guanidine-IV riboswitch at single-molecule level.

Riboswitches represent a class of non-coding RNA that possess the unique ability to specifically bind ligands and, in response, regulate gene expression. A recent report unveiled a type of riboswitch, known as the guanidine-IV riboswitch, which responds to guanidine levels to regulate downstream genetic transcription. However, the precise molecular mechanism through which the riboswitch senses its target ligand and undergoes conformational changes remain elusive. This gap in understanding has impeded the potential applications of this riboswitch. To bridge this knowledge gap, our study investigated the conformational dynamics of the guanidine-IV riboswitch RNA upon ligand binding. We employed single-molecule fluorescence resonance energy transfer (smFRET) to dissect the behaviors of the aptamer, terminator, and full-length riboswitch. Our findings indicated that the aptamer portion exhibited higher sensitivity to guanidine compared to the terminator and full-length constructs. Additionally, we utilized Position-specific Labelling of RNA (PLOR) combined with smFRET to observe, at the single-nucleotide and single-molecule level, the structural transitions experienced by the guanidine-IV riboswitch during transcription. Notably, we discovered that the influence of guanidine on the riboswitch RNA's conformations was significantly reduced after the transcription of 88 nucleotides. Furthermore, we proposed a folding model for the guanidine-IV riboswitch in the absence and presence of guanidine, thereby providing insights into its ligand-response mechanism.

Memory in cyclically crumpled sheets

We investigate the crumpling of an elastoplastic sheet as it is repeatedly crushed onto itself by rolling it into a cylinder and twisting it axially while allowing the end-to-end length to evolve freely. The sheet buckles and folds into structures that repeat but sharpen over hundreds of cycles to a remarkable degree before forming different configurations. Below a critical amplitude, reconfigurations decrease with applied cycles but continue to occur for large enough loading amplitude as the topology of the sheet changes as it tears. The sheet structure as measured by the mean curvature and the total crease length evolves logarithmically with cycle number with a rate that increases with compaction. We explain the progress of creasing using a flat folding model, and we show the logarithmic growth as being a consequence of individual creases becoming sharper with the number of folding cycles, leading to bifurcations in the folding pathway. Published by the American Physical Society 2024

Structure-informed mutagenesis identifies a conserved region critical for mouse insulin receptor 5'UTR IRES function.

The RNA structural requirements for cap-independent translation initiation facilitated by the Mus musculus insulin receptor (Insr) 5' untranslated region (5'UTR) are unknown. RNA secondary structure probing of the Insr 5'UTR in cells provides a folding model used to identify elements required for cap-independent translation initiation. A small region of the Insr 5'UTR distal to the translation start codon is necessary for cap-independent translation initiation and is fully sufficient in the proper structural context.

Viscous shear is a key force in Drosophila ventral furrow morphogenesis.

Ventral furrow (VF) formation in Drosophila melanogaster is an important model of epithelial folding. Previous models of VF formation require cell volume conservation to convert apically localized constriction forces into lateral cell elongation and tissue folding. Here, we have investigated embryonic morphogenesis in anillin knockdown (scra RNAi) embryos, where basal cell membranes fail to form and therefore cells can lose cytoplasmic volume through their basal side. Surprisingly, the mesoderm elongation and subsequent folding that comprise VF formation occurred essentially normally. We hypothesized that the effects of viscous shear may be sufficient to drive membrane elongation, providing effective volume conservation, and thus driving tissue folding. Since this hypothesis may not be possible to test experimentally, we turned to a computational approach. To test whether viscous shear is a dominant force for morphogenesis in vivo, we developed a 3D computational model incorporating both accurate cell and tissue geometry, and experimentally measured material parameters. Results from this model demonstrate that viscous shear generates sufficient force to drive cell elongation and tissue folding in vivo.

Unconditionally Energy-Stable SAV-FEM for the Dynamics Model of Protein Folding

Unconditionally Energy-Stable SAV-FEM for the Dynamics Model of Protein Folding

Slow Conformational Exchange between Partially Folded and Near-Native States of Ubiquitin: Evidence for a Multistate Folding Model.

The mechanism by which small proteins fold, i.e., via intermediates or via a two-state mechanism, is a subject of intense investigation. Intermediate states in the folding pathways of these proteins are sparsely populated due to transient lifetimes under normal conditions rendering them transparent to a majority of the biophysical methods employed for structural, thermodynamic, and kinetic characterization, which attributes are essential for understanding the cooperative folding/unfolding of such proteins. Dynamic NMR spectroscopy has enabled the characterization of folding intermediates of ubiquitin that exist in equilibrium under conditions of low pH and denaturants. At low pH, an unlocked state defined as N' is in fast exchange with an invisible state, U″, as observed by CEST NMR. Addition of urea to ubiquitin at pH 2 creates two new states F' and U', which are in slow exchange (kF'→U' = 0.14 and kU'→F' = 0.28 s-1) as indicated by longitudinal ZZ-magnetization exchange spectroscopy. High-resolution solution NMR structures of F' show it to be in an "unlocked" conformation with measurable changes in rotational diffusion, translational diffusion, and rotational correlational times. U' is characterized by the presence of just the highly conserved N-terminal β1-β2 hairpin. The folding of ubiquitin is cooperative and is nucleated by the formation of an N-terminal β-hairpin followed by significant hydrophobic collapse of the protein core resulting in the formation of bulk of the secondary structural elements stabilized by extensive tertiary contacts. U' and F' may thus be described as early and late folding intermediates in the ubiquitin folding pathway.

Prediction and functional interpretation of inter-chromosomal genome architecture from DNA sequence with TwinC.

Three-dimensional nuclear DNA architecture comprises well-studied intra-chromosomal (cis) folding and less characterized inter-chromosomal (trans) interfaces. Current predictive models of 3D genome folding can effectively infer pairwise cis-chromatin interactions from the primary DNA sequence but generally ignore trans contacts. There is an unmet need for robust models of trans-genome organization that provide insights into their underlying principles and functional relevance. We present TwinC, an interpretable convolutional neural network model that reliably predicts trans contacts measurable through genome-wide chromatin conformation capture (Hi-C). TwinC uses a paired sequence design from replicate Hi-C experiments to learn single base pair relevance in trans interactions across two stretches of DNA. The method achieves high predictive accuracy (AUROC=0.80) on a cross-chromosomal test set from Hi-C experiments in heart tissue. Mechanistically, the neural network learns the importance of compartments, chromatin accessibility, clustered transcription factor binding and G-quadruplexes in forming trans contacts. In summary, TwinC models and interprets trans genome architecture, shedding light on this poorly understood aspect of gene regulation.

Impact of Nonlocality Effects in Proton Optical Potential from Folding Model on $$p$$+$$^{16}$$O Elastic Scattering at Low Energies

Impact of Nonlocality Effects in Proton Optical Potential from Folding Model on $$p$$+$$^{16}$$O Elastic Scattering at Low Energies

The Folding Potential of Elastically Scattered d+ 24Mg Employing B3Y-Fetal Interaction within the Double Folding Model Framework

Study’s Excerpt/Novelty In this study, double-folding model with the B3Y-Fetal interaction was applied to derive optical potentials for deuteron scattering from 24Mg. The research validates the efficacy of mass-dependent interactions in optical potential calculations by accurately reproducing experimental differential cross-sections across a broad energy range. This work advances the understanding of nuclear reactions by demonstrating the suitability of the B3Y-Fetal interaction in modeling elastic scattering phenomena. Full Abstract The analysis of the deuteron scattering from was performed in the elastic channel using the double-folding model to evaluate the optical potentials of the present study. Both the real and the imaginary parts of the optical potentials were computed using a mass-dependent interaction (B3Y-Fetal) in the double-folding formalism. The derived double-folding potentials were used to analyse the differential cross-sections of within the energy range of 60-170 MeV. With the derived optical potentials, the reaction and differential cross-sections of were extracted in the optical model. The plots of the computed differential cross-sections were made and the results were compared to those obtained experimentally to ascertain the suitability of the derived potentials and the B3Y-Fetal interaction. In conclusion, the optical potentials obtained using the double-folding model with the B3Y-Fetal interaction were successful in reproducing the experimental data.

Design and Output Voltage Model of Folding Magnetized Electronic Skin for Intelligent Manipulator

Design and Output Voltage Model of Folding Magnetized Electronic Skin for Intelligent Manipulator

Hybrid Ising Machine and Reinforcement Learning Approach to Folding Lattice Proteins

The hydrophobic polarity (HP) protein folding model is a simplified computation model utilized to study the folding of proteins into their three-dimensional structures. Understanding how proteins fold and misfold is fundamental to designing effective, safe drugs, allowing for targeted therapies and better patient outcomes. The amino acids of a protein can be categorized as either hydrophobic or polar, where the hydrophobic beads tend to cluster together in a properly folded protein to minimize exposure to the surrounding environment. Determining the lowest energy configurations of the HP model is a non-deterministic polynomial (NP) hard problem. One method is formulating the HP model as a quadratic unconstrained binary optimization (QUBO) problem which can be mapped to an Ising machine. In the Ising model, the lowest energy state of the system represents the correct lattice configuration of the folded protein. The Ising machine technique utilized of simulated annealing allows for future application of the work on an integrated silicon photonic chip. Alternatively, reinforcement learning designed with an energy-based reward function can optimize the HP model by adapting to the environment without the consequence of remaining in local minima like that of the Ising machine. A hybrid pipeline combining the Ising machine and reinforcement learning sequentially was designed to determine the two-dimensional lattice configurations of various protein chain lengths and sequences, combining the parallel optimization of the Ising machine on an integrated photonic platform and the adaptability of the reinforcement learning algorithm. Results found that this hybrid model improved the accuracy and ability of determining the lowest energy state in contrast to the Ising machine alone as well as improved the efficiency by reducing the number of iterations required when compared solely to reinforcement learning. Future work focuses on implementing a parallel pipeline approach as well as adapting to a three-dimensional model.

Vocal Fold Injury Produces Similar Biomechanical Outcomes in Male and Female Rabbits

Sex differences in response to trauma and physiologic stressors have been identified in numerous organ systems but have not yet been defined in the larynx. The objective of this study was to develop an endoscopic vocal fold injury model in rabbits and to compare structural and functional outcomes between male and female subjects. Basic science study. Two male and two female rabbits underwent unilateral endoscopic cordectomy. Animals were intubated with a size 3-0 neonatal endotracheal tube, and laryngoscopy was performed with a 4mm Hopkins rod telescope. While visualizing, a 2mm cupped forceps grasped and resected the mid-membranous portion of the right true vocal fold. Larynges were then harvested after 8weeks. Excised larynx phonation with high-speed videography and kymography was used to assess vibrational quality. Tissue elastic (Young's) modulus was measured by indentation. Injured larynges phonated with fundamental frequencies between 237-415Hz. In both males and females, the scarred vocal fold exhibited an increased Young's modulus compared to the contralateral nonoperated vocal fold. There were no notable differences in glottal closure pattern or vocal fold oscillation symmetry between sexes. We have demonstrated a model for vocal fold scarring in rabbits. Vibrational and structural outcomes were similar between the examined male and female larynges.

Tissue-scale in vitro epithelial wrinkling and wrinkle-to-fold transition

Although epithelial folding is commonly studied using in vivo animal models, such models exhibit critical limitations in terms of real-time observation and independent control of experimental parameters. Here, we develop a tissue-scale in vitro epithelial bilayer folding model that incorporates an epithelium and extracellular matrix (ECM) hydrogel, thereby emulating various folding structures found in in vivo epithelial tissue. Beyond mere folding, our in vitro model realizes a hierarchical transition in the epithelial bilayer, shifting from periodic wrinkles to a single deep fold under compression. Experimental and theoretical investigations of the in vitro model imply that both the strain-stiffening of epithelium and the poroelasticity of ECM influence the folded structures of epithelial tissue. The proposed in vitro model will aid in investigating the underlying mechanism of tissue-scale in vivo epithelial folding relevant to developmental biology and tissue engineering.

Hyperelastic material models for simulating deformation of silicone ring pessaries

Pessaries are removable gynecological prosthetic devices that provide mechanical support for temporary or long-term symptom relief of pelvic floor disorders, such as pelvic organ prolapse and stress urinary incontinence. To date, limited mechanical tests have been performed on physical pessary designs to characterize their behaviour under load; however, custom pessary manufacturing is expensive and time consuming. As an alternative, finite element (FE) modeling can provide detailed numerical insight into the response of a pessary design under load but to date has seen limited application, with little data available for pessary silicone materials. This study aimed to identify hyperelastic material models for two silicone materials used in custom pessary cocoon moulded manufacturing towards FE analysis of ring with support (RWS) pessaries. It was hypothesized that hyperelastic material models could be identified to capture the force and deformation response of multiple RWS sizes under different boundary conditions and silicone materials (Shore 60A and 40A). To understand the material characteristics of pessary silicone, uniaxial tension and compression tests were performed then the experimental data was fit with Mooney-Rivlin (MR) material models. To ensure the material models characterize the pessary behaviour, data from mechanical tests representing the RWS pessary folding and modified 3-point bending were compared to FE recreations (FEBio) of the same tests with the MR materials applied to the pessaries. The FE model results demonstrated good agreement in the force-displacement response for the fold and 3-point bending models for different pessary sizes and silicone stiffnesses. This work demonstrates the hyperelastic material models’ efficacy and will enable future studies to improve biomechanical analysis of silicone pessary designs.

KNNDM CV: k-fold nearest-neighbour distance matching cross-validation for map accuracy estimation

Abstract. Random and spatial cross-validation (CV) methods are commonly used to evaluate machine-learning-based spatial prediction models, and the performance values obtained are often interpreted as map accuracy estimates. However, the appropriateness of such approaches is currently the subject of controversy. For the common case where no probability sample for validation purposes is available, in Milà et al. (2022) we proposed the nearest-neighbour distance matching (NNDM) leave-one-out (LOO) CV method. This method produces a distribution of geographical nearest-neighbour distances (NNDs) between test and training locations during CV that matches the distribution of NNDs between prediction and training locations. Hence, it creates predictive conditions during CV that are comparable to what is required when predicting a defined area. Although NNDM LOO CV produced largely reliable map accuracy estimates in our analysis, as a LOO-based method, it cannot be applied to the large datasets found in many studies. Here, we propose a novel k-fold CV strategy for map accuracy estimation inspired by the concepts of NNDM LOO CV: the k-fold NNDM (kNNDM) CV. The kNNDM algorithm tries to find a k-fold configuration such that the empirical cumulative distribution function (ECDF) of NNDs between test and training locations during CV is matched to the ECDF of NNDs between prediction and training locations. We tested kNNDM CV in a simulation study with different sampling distributions and compared it to other CV methods including NNDM LOO CV. We found that kNNDM CV performed similarly to NNDM LOO CV and produced reasonably reliable map accuracy estimates across sampling patterns. However, compared to NNDM LOO CV, kNNDM resulted in significantly reduced computation times. In an experiment using 4000 strongly clustered training points, kNNDM CV reduced the time spent on fold assignment and model training from 4.8 d to 1.2 min. Furthermore, we found a positive association between the quality of the match of the two ECDFs in kNNDM and the reliability of the map accuracy estimates. kNNDM provided the advantages of our original NNDM LOO CV strategy while bypassing its sample size limitations.

Synthetic, self-oscillating vocal fold models for voice production researcha).

Sound for the human voice is produced by vocal fold flow-induced vibration and involves a complex coupling between flow dynamics, tissue motion, and acoustics. Over the past three decades, synthetic, self-oscillating vocal fold models have played an increasingly important role in the study of these complex physical interactions. In particular, two types of models have been established: "membranous" vocal fold models, such as a water-filled latex tube, and "elastic solid" models, such as ultrasoft silicone formed into a vocal fold-like shape and in some cases with multiple layers of differing stiffness to mimic the human vocal fold tissue structure. In this review, the designs, capabilities, and limitations of these two types of models are presented. Considerations unique to the implementation of elastic solid models, including fabrication processes and materials, are discussed. Applications in which these models have been used to study the underlying mechanical principles that govern phonation are surveyed, and experimental techniques and configurations are reviewed. Finally, recommendations for continued development of these models for even more lifelike response and clinical relevance are summarized.

Resource analysis of quantum algorithms for coarse-grained protein folding models

Protein folding processes are a vital aspect of molecular biology that is hard to simulate with conventional computers. Quantum algorithms have been proven superior for certain problems and may help tackle this complex life science challenge. We analyze the resource requirements for simulating simplified yet computationally challenging protein folding models on a quantum computer, assessing the feasibility of these existing approaches in the current and near-future technological landscape. We calculate the minimum number of qubits, interactions, and two-qubit gates necessary to build a heuristic quantum algorithm with the specific information of a folding problem. Particularly, we focus on the resources needed to build quantum operations based on the Hamiltonian linked to the protein folding models for a given amino acid count. Such operations are a fundamental component of these quantum algorithms, guiding the evolution of the quantum state for efficient computations. Specifically, we study coarse-grained folding models on the lattice and the fixed backbone side-chain conformation model and assess their compatibility with the constraints of existing quantum hardware given different bit encodings. We conclude that the number of qubits required falls within current technological capabilities. However, the limiting factor is the high number of interactions in the Hamiltonian, resulting in a quantum gate count unavailable today. Published by the American Physical Society 2024

Inferring potential landscapes: A Schrödinger bridge approach to maximum caliber

Schrödinger bridges have emerged as an enabling framework for unveiling the stochastic dynamics of systems based on marginal observations at different points in time. The terminology “bridge” refers to a probability law that suitably interpolates such marginals. The theory plays a pivotal role in a variety of contemporary developments in machine learning, stochastic control, thermodynamics, and biology, to name a few, impacting disciplines such as single-cell genomics, meteorology, and robotics. In this work, we extend Schrödinger's paradigm of bridges to account for integral constraints along paths, in a way akin to maximum caliber—a maximum entropy principle applied in a dynamic context. The maximum caliber principle has proven useful to infer the dynamics of complex systems, e.g., model gene circuits and protein folding. We unify these two problems via a maximum likelihood formulation to reconcile stochastic dynamics with ensemble-path data. A variety of data types can be encompassed, ranging from distribution moments to average currents along paths. The framework enables inference of time-varying potential landscapes that drive the process. The resulting forces can be interpreted as the optimal control that drives the system in a way that abides by specified integral constraints. This, in turn, relates to a similarly constrained optimal mass transport problem in the zero-noise limit. Analogous results are presented in a discrete-time, discrete-space setting and specialized to steady-state dynamics. We finish by illustrating the practical applicability of the framework through paradigmatic examples, such as that of bit erasure or protein folding. In doing so, we highlight the strengths of the proposed framework, namely, the generality of the theory, its elegant analytical structure, the ease of computation, and the ability to interpret results in terms of system dynamics. This is in contrast to maximum caliber problems where the focus is typically on updating a probability law on paths. Published by the American Physical Society 2024