Small Domains Research Articles

Decentralized Finite‐Time Adaptive Neural Output‐Feedback Quantized Control for Switched Nonlinear Large‐Scale Delayed Systems

ABSTRACTThis paper considers the problem of decentralized finite‐time adaptive neural output‐feedback quantized control for a class of switched nonlinear large‐scale delayed systems. A switched high‐gain quantized state observer is therefore constructed for each subsystem to estimate unavailable system states. Different from the traditional Lyapunov–Krasovskii functional method, multiple Lyapunov–Krasovskii functions are introduced to develop the decentralized adaptive output‐feedback control strategy with neural network approximation for the switched nonlinear large‐scale delayed systems. Under a category of switching signals with persistent dwell time, all signals in the closed‐loop switched system are semi‐globally uniformly ultimate bounded. Meanwhile, the tracking errors can remain in a small domain of origin in finite time. Case studies are finally used to illustrate the flexibility and effectiveness of the proposed control approach, including the switched two continuous stirred tank reactor delayed systems.

Evaluation of Eight-day Typhoon Quantitative Precipitation Forecasts in Taiwan by the 2.5-km CReSS Model: Overall Performance during 2012-2016 and Impact of Domain Size

Abstract The skill of 24-h daily quantitative precipitation forecasts (QPFs) in Taiwan by a cloud-resolving model out to eight days was evaluated for 27 typhoons (84 days) during 2012-2016. Overall, the skill increased as the lead time shortened, and most of the QPFs were of high quality on both day 1 (0-24 h) and day 2 (24-48 h) with a minimum tendency to over-forecast rainfall. At longer lead times from day 4 (72-96 h) to day 8 (168-192 h), where under-forecasting became increasingly apparent, decent QPFs that resembled the observation could still be realized if the track errors were small enough due to better quality in the initial and boundary conditions from the global model. For the 14 typhoons that had an observed peak daily amount of ≥ 350 mm, such QPFs occurred in 10 of them (71%) and the earliest around day 5 on average. Thus, good rainfall scenarios could be provided quite early for many typhoons by this high-resolution system. By comparing the QPF results above to those by the three-day forecasts that used a smaller domain, potential benefits of an enlarged fine domain were assessed. The only major difference occurred on day 1 at the 750-mm threshold, where the threat score (TS) was 0.17 (0.05) using a larger (smaller) domain, contributed only by two typhoons. While this result appeared random, the larger domain simulated the responsible rainband slightly better and had a higher accumulation to produce hits at a key station on both occasions despite a very similar TC track, and thus could be beneficial for typhoon QPFs.

Novel NaNbO3-based, ferroelectric ceramics with excellent polarization and electric potential for antibacterial applications

Low surface electric potential (<1V) limits the large-scale commercial application of ferroelectric antibacterial ceramics. We propose a strategy based on charge-balancing doping to enhance polarization and potential in NaNbO3(NN)-based ceramics for disinfection application. The Mg2+ modified NN showed a superior bactericidal effect greater than 80% for 1.5 h and 99.8% for 3 h without heating or ultrasonication, which is superior to other published works. This is mainly due to its excellent surface electric potential of 1.72 V and defect-related discharge current of 141.9 pA compared to NN and Ca2+ modified NN. Ferroelectric properties demonstrated that NN-Mg possesses a lower EC of ∼40 kV/cm and a higher Pr of ∼32 μC/cm2. Furthermore, the combination of XRD, Raman shift, PFM, and permittivity testing suggests that the smaller domain and enhanced ferroelectric properties in NN-Mg originated from amphoteric doping. Finally, simulation results of the electric field distribution indicated that NN-Mg had a stronger attraction or repulsion to bacteria with negatively charged surfaces.

The proposal and calculation method of the annular domain weight function for the electromagnetic flowmeter under annular conductivity distribution

Researching on the characteristic of weight function distribution under non-uniform conductivity distribution is of significant importance for expanding the engineering applications of electromagnetic flowmeter. In this paper, the characteristic of weight function distribution is firstly explored for annular conductivity distribution where the center and outer ring are both conductive. The research results indicate an important finding that the average value of the weight function within any small annular domain of the center or outer ring remains constant as the radial position changes. Therefore, the concept of ‘annular domain weight function’ is then innovatively proposed. Furthermore, the relationship is studied between the ratio of the annular domain weight function of the center and outer ring and the annular feature parameters. Ultimately, the correlations are obtained for calculating the annular domain weight functions of the center and outer ring.

Rapid prediction of key residues for foldability by machine learning model enables the design of highly functional libraries with hyperstable constrained peptide scaffolds.

Peptides are an emerging modality for developing therapeutics that can either agonize or antagonize cellular pathways associated with disease, yet peptides often suffer from poor chemical and physical stability, which limits their potential. However, naturally occurring disulfide-constrained peptides (DCPs) and de novo designed Hyperstable Constrained Peptides (HCPs) exhibiting highly stable and drug-like scaffolds, making them attractive therapeutic modalities. Previously, we established a robust platform for discovering peptide therapeutics by utilizing multiple DCPs as scaffolds. However, we realized that those libraries could be further improved by considering the foldability of peptide scaffolds for library design. We hypothesized that specific sequence patterns within the peptide scaffolds played a crucial role in spontaneous folding into a stable topology, and thus, these sequences should not be subject to randomization in the original library design. Therefore, we developed a method for designing highly diverse DCP libraries while preserving the inherent foldability of each scaffold. To achieve this, we first generated a large-scale dataset from yeast surface display (YSD) combined with shotgun alanine scan experiments to train a machine-learning (ML) model based on techniques used for natural language understanding. Then we validated the ML model with experiments, showing that it is able to not only predict the foldability of peptides with high accuracy across a broad range of sequences but also pinpoint residues critical for foldability. Using the insights gained from the alanine scanning experiment as well as prediction model, we designed a new peptide library based on a de novo-designed HCP, which was optimized for enhanced folding efficiency. Subsequent panning trials using this library yielded promising hits having good folding properties. In summary, this work advances peptide or small protein domain library design practices. These findings could pave the way for the efficient development of peptide-based therapeutics in the future.

Giant Piezoelectric Coefficient of Polyvinylidene Fluoride with Rationally Engineered Ultrafine Domains Achieved by Rapid Freezing Processing.

Domains play an essential role in determining the piezoelectric properties of polymers. The conventional method for achieving ultrafine piezoelectric domain structures for polymers is multiphase polymerization, which is not the primary choice for industrial-scale applications because of its complex synthesis and weak mechanical properties. In this study, it is demonstrated for the first time that a nanoscale domain design can be achieved in a commercially available polyvinylidene fluoride (PVDF) homopolymer through a simple fabrication method involving cyclic compression and rapid freezing. The domain-engineered PVDF exhibits largely enhanced piezoelectric output with a record-breaking piezoelectric coefficient (d33) of 191.4 picocoulombs per Newton (8.9 times higher than that of PVDF without engineered domain structure) and electromechanical coupling factor (k33) of 77.1%. Moreover, nanoscale domain-induced ferroelectric and dielectric evolutions are revealed. A smaller domain is found to be beneficial for domain switching. An in-depth understanding of the interplay between the domain structure and piezoelectric properties reveals a simple, low-cost method for fabricating high-performance polymeric piezoelectric.

On the Analytic Continuation of Appell’s Hypergeometric Function F2 to Some Symmetric Domains in the Space C2

The paper considers the problem of representation and extension of Appell’s hypergeometric functions by a special family of functions—branched continued fractions. Here, we establish new symmetric domains of the analytical continuation of Appell’s hypergeometric function F2 with real and complex parameters, using their branched continued fraction expansions whose elements are polynomials in the space C2. To do this, we used a technique that extends the domain of convergence of the branched continued fraction, which is already known for a small domain, to a larger domain, as well as the PC method to prove that it is also the domain of analytical continuation. A few examples are provided at the end to illustrate this.

MRCK-1 activates non-muscle myosin for outgrowth of a unicellular tube in Caenorhabditis elegans.

The formation and patterning of unicellular biological tubes is essential for metazoan development. It is well established that vascular tubes and neurons use similar guidance cues to direct their development, but the downstream mechanisms that promote the outgrowth of biological tubes are not well characterized. We show that the conserved kinase MRCK-1 and its substrate the regulatory light chain of non-muscle myosin, MLC-4, are required for outgrowth of the unicellular excretory canal in C. elegans. Ablation of MRCK-1 or MLC-4 in the canal causes severe truncations with unlumenized projections of the basal membrane. Structure-function analysis of MRCK-1 indicates that the kinase domain, but not the small GTPase-binding CRIB domain, is required for canal outgrowth. Expression of a phosphomimetic form of MLC-4 rescues canal truncations in mrck-1 mutants and shows enrichment at the growing canal tip. Moreover, our work reveals a novel function for non-muscle myosin downstream of MRCK-1 in excretory canal outgrowth that may be conserved in the development of seamless tubes in other organisms.

Photothermal AFM-IR Depth Sensitivity: An Original Pathway to Tomographic Reconstruction.

Photothermal atomic force microscopy-infrared (AFM-IR) enables label-free chemical imaging and spectroscopy with nanometer-scale spatial resolution through the integration of atomic force microscopy (AFM) and infrared radiation. The capability for subsurface and three-dimensional (3D) tomographic material analysis remains, however, largely unexplored. Here, we establish a simple and robust empirical relationship between the probing depth and laser repetition rate for three important modes of AFM-IR operation: resonance-enhanced, tapping, and surface-sensitive AFM-IR. Using this empirical relationship, we demonstrate, based on the example of resonance-enhanced operation, how photothermal AFM-IR of thin surface/subsurface layers of polystyrene domains in the poly(methyl methacrylate) matrix can result in 3D representations revealing the size and thickness of small polystyrene domains in the poly(methyl methacrylate) matrix with nanometer-scale resolution. Experimental findings are confirmed by analytical models.

Giant energy storage density, high efficiency and excellent stability achieved in lead-free KNN-based ceramic via a composition optimization strategy

The (1-x)K0.5Na0.5NbO3-xBi(Zn2/3Sb1/3)O3 ceramics, abbreviated as (1-x)KNN-xBZS with x values of 0.05, 0.10, 0.15, and 0.20, were prepared via solid-state reaction technique. Their structural and electrical characteristics, including dielectric and ferroelectric characteristics, were systematically examined. The achievement of an optimized phase transition-field and the broadening of the bandgap in the 0.85KNN-0.15BZS ceramics contribute to the delay of polarization and improvement in the breakdown field strength. Dielectric measurements indicate that the introduction of BZS disrupts the original large domain structure of KNN ceramics, giving rise to small domains and polar nano regions (PNRs). Specifically, the 0.85KNN-0.15BZS ceramic exhibits exceptional energy storage density (Wrec = 5.90 J/cm3) and an ultra-high energy efficiency (η = 79.9%) at an applied electric field of 570 kV/cm. Furthermore, this ceramic displays excellent frequency stability in the range of 1-100 Hz and temperature stability between 30-150 °C. The remarkable energy storage properties of (1-x)KNN-xBZS ceramics position them as highly promising materials for future pulse power capacitors and various energy storage applications.

AMBER: A Modular Model for Tumor Growth, Vasculature and Radiation Response.

Computational models of tumor growth are valuable for simulating the dynamics of cancer progression and treatment responses. In particular, agent-based models (ABMs) tracking individual agents and their interactions are useful for their flexibility and ability to model complex behaviors. However, ABMs have often been confined to small domains or, when scaled up, have neglected crucial aspects like vasculature. Additionally, the integration into tumor ABMs of precise radiation dose calculations using gold-standard Monte Carlo (MC) methods, crucial in contemporary radiotherapy, has been lacking. Here, we introduce AMBER, an Agent-based fraMework for radioBiological Effects in Radiotherapy that computationally models tumor growth and radiation responses. AMBER is based on a voxelized geometry, enabling realistic simulations at relevant pre-clinical scales by tracking temporally discrete states stepwise. Its hybrid approach, combining traditional ABM techniques with continuous spatiotemporal fields of key microenvironmental factors such as oxygen and vascular endothelial growth factor, facilitates the generation of realistic tortuous vascular trees. Moreover, AMBER is integrated with TOPAS, an MC-based particle transport algorithm that simulates heterogeneous radiation doses. The impact of radiation on tumor dynamics considers the microenvironmental factors that alter radiosensitivity, such as oxygen availability, providing a full coupling between the biological and physical aspects. Our results show that simulations with AMBER yield accurate tumor evolution and radiation treatment outcomes, consistent with established volumetric growth laws and radiobiological understanding. Thus, AMBER emerges as a promising tool for replicating essential features of tumor growth and radiation response, offering a modular design for future expansions to incorporate specific biological traits.

MAD2L2 Dimerization Is Not Essential for Mitotic Regulation.

MAD2L2 is a small HORMA domain protein that plays a crucial role in DNA repair and mitosis. In both TLS and shieldin, the dimerization of MAD2L2 via its HORMA domain is critical for the stability and function of these complexes. However, in mitosis, the dimerization state of MAD2L2 remains unknown. To assess the importance of MAD2L2's dimerization during mitosis, we utilized CRISPR/Cas9 to generate MAD2L2 knockout cells, which were subsequently complemented with MAD2L2 species carrying different dimer-disrupting point mutations. We assessed the ability of these MAD2L2 dimer-disrupting mutants to regulate mitosis by evaluating early mitotic events and mitotic fidelity. Our findings indicate that MAD2L2 can function in its monomeric form during mitosis, suggesting that MAD2L2 homodimerization is dispensable for early mitotic regulation. Furthermore, our results suggest that the binding of CDH1 to MAD2L2 is a key regulating factor in mitosis that may actively prevent the formation of MAD2L2 dimers, thereby shifting the cellular balance toward MAD2L2-CDH1 interaction. Thus, the equilibrium between the monomeric and dimeric forms of MAD2L2 is an important cellular factor regulating the MAD2L2-containing complexes.

Thousands of planetesimals: Simulating the streaming instability in very large computational domains

The streaming instability is a mechanism whereby pebble-sized particles in protoplanetary discs spontaneously come together in dense filaments, which collapse gravitationally to form planetesimals upon reaching the Roche density. The extent of the filaments along the orbital direction is nevertheless poorly characterised, due to a focus in the literature on small simulation domains where the behaviour of the streaming instability on large scales cannot be determined. We present here computer simulations of the streaming instability in boxes with side lengths up to $6.4$ scale heights in the plane. This is $32$ times larger than typically considered simulation domains and nearly a factor $1,000$ times the volume. We show that the azimuthal extent of filaments in the non-linear state of the streaming instability is limited to approximately one gas scale height. The streaming instability will therefore not transform the pebble density field into axisymmetric rings; rather the non-linear state of the streaming instability appears as a complex structure of loosely connected filaments. Including the self-gravity of the pebbles, our simulations form up to $4,000$ planetesimals. This allows us to probe the high-mass end of the initial mass function of planetesimals with much higher statistical confidence than previously. We find that this end is well-described by a steep exponential tapering. Since the resolution of our simulations is moderate -- a necessary trade-off given the large domains -- the mass distribution is incomplete at the low-mass end. When putting comparatively less weight on the numbers at low masses, at intermediate masses we nevertheless reproduce the power-law shape of the distribution established in previous studies.

The development of single-domain VHH nanobodies that target the Candida albicans cell surface.

Candida albicans causes life-threatening invasive infections that are hard to diagnose and treat, with drug resistance leading to treatment failure. The goal of this study was to develop VHH (single variable domain on a heavy chain) nanobodies to detect drug-resistant infections. Llamas were immunized with a mixture of heat killed and fixed C. albicans cells of different morphologies. Llama lymphocyte RNA was used to generate phage display libraries that were tested for binding to C. albicans cells or cell wall fractions, and single antibody domains were isolated. The libraries were panned against echinocandin-resistant C. albicans isolates and counter-selected against echinocandin-susceptible isolates with the aim of isolating binding domains specific for antigens on drug-resistant cells. Thirty diverse VHH nanobodies were selected, and binding characteristics were assessed via dose-response ELISA. Binding was tested against a variety of C. albicans isolates and other Candida species, indicating that the VHHs were specific for C. albicans. The VHH nanobodies were sorted into four distinct groups based on their binding patterns. Two of the groups bound preferentially to the yeast cell poles and hyphae, respectively. Nanobody binding to C. albicans deletion mutants was tested by fluorescence microscopy and ELISA to identify the antigen targets. VHH19 nanobody, belonging to the largest group, recognized the Als4 adhesin. VHH14 antibody in the hyphae-specific group recognized Als3. None of the isolated VHH nanobodies was selective for drug-resistant clinical isolates. Our data indicate that this approach can generate valuable single-domain antibodies specific to C. albicans proteins.IMPORTANCEThe human fungal pathogen Candida albicans causes a range of diseases from superficial mucosal infections such as oral and vaginal thrush to life-threatening, systemic infections. Accurate and rapid diagnosis of these infections remains challenging, and currently, there are no rapid ways to diagnose drug-resistant infections without performing drug susceptibility testing from blood culture, which can take several days. In this proof-of-concept study, we have generated a diverse set of single domain VHH antibodies (nanobodies) from llamas that recognize and bind specifically to C. albicans cell surface. The nanobodies were classified into four groups based on their binding patterns, for example, cell poles or hyphae. Specific nanobodies were verified as recognizing the important adhesin Als4 or the hyphae associated invasin Als3, respectively. The data validate the approach that small VHH antibody domains hold future promise for diagnostic applications and as probes to study the fungal cell surface.

Human IL-22 receptor-targeted small protein antagonist suppress murine DSS-induced colitis

BackgroundHuman interleukin-22 (IL-22) is known as a “dual function” cytokine that acts as a master regulator to maintain homeostasis, structural integrity of the intestinal epithelial barrier, and shielding against bacterial pathogens. On the other hand, the overexpression of IL-22 is associated with hyper-proliferation and recruitment of pathologic effector cells, leading to tissue damage and chronic inflammation in specific diseases including inflammatory bowel disease (IBD). To study a role of IL-22-mediated signaling axis during intestinal inflammation, we generated a set of small protein blockers of IL-22R1 and verified their inhibitory potential on murine model of colitis.MethodsWe used directed evolution of proteins to identify binders of human IL-22 receptor alpha (IL-22R1), designated as ABR ligands. This approach combines the assembly of a highly complex combinatorial protein library derived from small albumin-binding domain scaffold and selection of promising protein variants using ribosome display followed by large-scale ELISA screening. The binding affinity and specificity of ABR variants were analyzed on transfected HEK293T cells by flow cytometry and LigandTracer. Inhibitory function was further verified by competition ELISA, HEK-Blue IL-22 reporter cells, and murine dextran sulfate sodium (DSS)-induced colitis.ResultsWe demonstrate that ABR specifically recognizes transgenic IL-22R1 expressed on HEK293T cells and IL-22R1 on TNFα/IFNγ-activated HaCaT cells. Moreover, some ABR binders compete with the IL-22 cytokine and function as IL-22R1 antagonists in HEK-Blue IL22 reporter cells. In a murine model of DSS-induced acute intestinal inflammation, daily intraperitoneal administration of the best IL-22R1 antagonist, ABR167, suppressed the development of clinical and histological markers of colitis including prevention of mucosal inflammation and architecture deterioration. In addition, ABR167 reduces the DSS-induced increase in mRNA transcript levels of inflammatory cytokines such as IL-1β, IL-6, IL-10, and IL-17A.ConclusionsWe developed small anti-human IL-22R1 blockers with antagonistic properties that ascertain a substantial role of IL-22-mediated signaling in the development of intestinal inflammation. The developed ABR blockers can be useful as a molecular clue for further IBD drug development.

Arc bubble edge detection method based on deep transfer learning in underwater wet welding.

The stability of arc bubble is a crucial indicator of underwater wet welding process. However, limited research exists on detecting arc bubble edges in such environments, and traditional algorithms often produce blurry and discontinuous results. To address these challenges, we propose a novel arc bubble edge detection method based on deep transfer learning for processing underwater wet welding images. The proposed method integrates two training stages: pre-training and fine-tuning. In the pre-training stage, a large source domain dataset is used to train VGG16 as a feature extractor. In the fine-tuning stage, we introduce the Attention-Scale-Semantics (ASS) model, which consists of a Convolutional Block Attention Module (CBAM), a Scale Fusion Module (SCM) and a Semantic Fusion Module (SEM). The ASS model is further trained on a small target domain dataset specific to underwater wet welding to fine-tune the model parameters. The CBAM can adaptively weight the feature maps, focusing on more crucial features to better capture edge information. The SCM training method maximizes feature utilization and simplifies training by combining multi-scale features. Additionally, the skip structure of SEM effectively mitigates semantic loss in the high-level network, enhancing the accuracy of edge detection. On the BSDS500 dataset and a self-constructed underwater wet welding dataset, the ASS model was evaluated against conventional edge detection models-Richer Convolutional Features (RCF), Fully Convolutional Network (FCN), and UNet-as well as state-of-the-art models LDC and TEED. In terms of Mean Absolute Error (MAE), accuracy, and other evaluation metrics, the ASS model consistently outperforms these models, demonstrating edge detection capabilities that are both effective and stable in detecting arc bubble edges in underwater wet welding images.

A strategy for improving piezoelectricity and thermal stability of Na0.25K0.25Bi2.5Nb2O9-based piezoceramics via A/B-site co-doping

Obviously improved piezoelectricity and thermal stability of Na0.25K0.25Bi2.5Nb2O9-based ceramics have been urgently required for high-temperature piezoelectric applications. In this work, Na0.25K0.25Bi2.5-xCexNb2-yWyO9 (NKBCxNWy, x = 0.01, 0.02, 0.03, 0.04; y = 0.02) piezoceramics were developed via a traditional solid-state reaction method. The effect of Ce/W co-doping on the crystal structure and microscopic morphology was systematically investigated, along with the ferroelectric domains and electrical properties. An optimum composition of Na0.25K0.25Bi2.48Ce0.02Nb1.98W0.02O9 was achieved, which shows a high curie temperature of 670 ℃, a good piezoelectric coefficient d33 of 24.4 pC/N. The enhanced d33 stems from small domain sizes and high domain wall density in NKBC0.02NW0.02 ceramics. More importantly, the maximum d33 can remain above 80 % of the d33 (@25 ℃), even if the annealing temperature increases to 500 ℃. This work provides a simple and viable method to obtain high piezoelectric properties and excellent thermal stability in Na0.25K0.25Bi2.5Nb2O9-based ceramics.

Crystal structure of l-threonine-O-3-phosphate decarboxylase CobC from Sinorhizobium meliloti involved in vitamin B12 biosynthesis

Vitamin B12 is involved in many important biochemical reactions for humans, and its deficiency can lead to serious diseases. The industrial production of vitamin B12 is achieved through microbial fermentation. In this work, we determine the crystal structures of the l-threonine-O-3-phosphate (Thr-P) decarboxylase CobC from Sinorhizobium meliloti (SmCobC), an industrial vitamin B12-producing bacterium, in apo form and in complex with a reaction intermediate. Our structures supported the Thr-P decarboxylase activity of SmCobC and revealed that the positively charged substrate-binding pocket between the large and small domains determines its substrate selectivity for Thr-P. Moreover, our results provided evidence for the proposition that the AP-P linker is formed by direct incorporation of AP-P in the biosynthetic pathway of vitamin B12 in S.meliloti.

Pore-scale study of coupled heat and mass transfer during primary freeze-drying using an irregular pore network model

This study presents a pore network (PN) model with transient heat transfer and quasi-steady transitional vapor transport that is for the first time applied to irregular porous structures that are obtained by reconstruction of X-ray tomography image data. In contrast to previous studies, the irregular pores are not approximated by spheres but implemented in their original shape. Secondly, instead of assuming cylindrical throats as pore connections, the actual distance between pore centers as well as the pore cross sections are used for the computation of the vapor transport coefficient. The control volume elements of the computational model are matched with the cells obtained by Voronoi tessellation. The improvements have clear advantages over former approaches where the reconstructed void space is usually strongly simplified by balls and sticks confined in a regular lattice structure. A freeze-dried sample of maltodextrin DE12 with 20% (w/w) solid content is used for benchmarking the new methodology. Its morphological and thermal properties are determined by the novel PN model. The simulation results of primary freeze-drying (FD) are compared to reference cases in two ways. First, the differences in heat and mass transfer kinetics as compared to regular PNs are emphasized. Secondly, the PN simulation results are confronted with a simple literature model that neglects pore size distribution (PSD) and transient heat transfer. It is shown that already in small domains with relatively narrow PSD, the variation of the mass transfer coefficient affects the computed sublimation fluxes and yields a significant deviation from the simpler literature model. Moreover, it is revealed in this study that the structure has a significant impact on the sublimation front temperature. This is demonstrated by the comparison of FD in the irregular PN to a regular PN with almost identical PSD but different porosity. The development, verification, and benchmarking of the new PN model can be seen as an important step for studies of the structure dependence of FD.

Cooperative folding as a molecular switch in an evolved antibody binder

Designing proteins with tunable activities from easily accessible external cues remains a biotechnological challenge. Here, we set out to create a small antibody-binding domain equipped with a molecular switch inspired by the allosteric response to calcium seen in naturally derived proteins like calmodulin. We have focused on one of the three domains of Protein G that show inherent affinity to antibodies. By combining a semi-rational protein design with directed evolution, we engineered novel variants containing a calcium-binding loop rendering the inherent antibody affinity calcium-dependent. The evolved variants resulted from a designed selection strategy subjecting them to negative and positive selection pressures focused on conditional antibody-binding. Hence, these variants contained molecular “on/off” switches, controlling the target affinity towards antibody fragments simply by the presence or absence of calcium. From NMR spectroscopy we found that the molecular mechanism underlying the evolved switching behavior was a coupled calcium-binding and folding event where the target binding surface was intact and functional only in the presence of bound calcium. Notably, it was observed that the response to the employed selection pressures gave rise to the evolution of a cooperative folding mechanism. This observation illustrates why the cooperative folding reaction is an effective solution seen repeatedly in the natural evolution of fine-tuned macromolecular recognition. Engineering binding moieties to confer conditional target interaction has great potential due to the exquisite interaction control that is tunable to application requirements. Improved understanding of the molecular mechanisms behind regulated interactions is crucial to unlock how to engineer switchable proteins useful in a variety of biotechnological applications.