Rational Design Approach Research Articles

Frequency and time domain 19F ENDOR spectroscopy: role of nuclear dipolar couplings to determine distance distributions.

19F electron-nuclear double resonance (ENDOR) spectroscopy is emerging as a method of choice to determine molecular distances in biomolecules in the angstrom to nanometer range. However, line broadening mechanisms in 19F ENDOR spectra can obscure the detected spin-dipolar coupling that encodes the distance information, thus limiting the resolution and accessible distance range. So far, the origin of these mechanisms has not been understood. Here, we employ a combined approach of rational molecular design, frequency and time domain ENDOR methods as well as quantum mechanical spin dynamics simulations to analyze these mechanisms. We present the first application of Fourier transform ENDOR to remove power broadening and measure T2n of the 19F nucleus. We identify nuclear dipolar couplings between the fluorine and protons up to 14 kHz as a major source of spectral broadening. When removing these interactions by H/D exchange, an unprecedented spectral width of 9 kHz was observed suggesting that, generally, the accessible distance range can be extended. In a spin labeled RNA duplex we were able to predict the spectral ENDOR line width, which in turn enabled us to extract a distance distribution. This study represents a first step towards a quantitative determination of distance distributions in biomolecules from 19F ENDOR.

Ion‐Selective Mobility Differential Amplifier: Enhancing Pressure‐Induced Voltage Response in Hydrogels

Piezoionics is an emerging mechanical‐electrical energy conversion paradigm that enables self‐powered sensing systems for next‐generation intelligent wearable electronics. However, there are currently no rational design approaches to enhance the stimulus response of piezoionic devices. Here, we present a strategy using crown ether as ion‐selective mobility differential amplifiers for enhancing the pressured‐induced voltage response in ionic polyvinyl alcohol (PVA) hydrogels. The crown ether grafted PVA (PVA‐CE) hydrogel prototype achieves a 30‐fold amplified piezoionic coefficient of 1490 nV Pa−1 within 0 – 1 kPa, compared to 49 nV Pa−1 of the unmodified PVA. The PVA‐CE exhibits an ultra‐low pressure detection limit of 0.2 Pa with a fast response time of 18.1 ms. Leveraging these properties, we further demonstrate a human somatosensory network analogous PVA‐CE piezoionic skin using arrayed pressure sensing. These capabilities hold great promise for emerging healthcare applications such as synthetic biology, soft robotics, and beyond.

Ion-Selective Mobility Differential Amplifier: Enhancing Pressure-Induced Voltage Response in Hydrogels.

Piezoionics is an emerging mechanical-electrical energy conversion paradigm that enables self-powered sensing systems for next-generation intelligent wearable electronics. However, there are currently no rational design approaches to enhance the stimulus response of piezoionic devices. Here, we present a strategy using crown ether as ion-selective mobility differential amplifiers for enhancing the pressured-induced voltage response in ionic polyvinyl alcohol (PVA) hydrogels. The crown ether grafted PVA (PVA-CE) hydrogel prototype achieves a 30-fold amplified piezoionic coefficient of 1490 nV Pa-1 within 0 - 1 kPa, compared to 49 nV Pa-1 of the unmodified PVA. The PVA-CE exhibits an ultra-low pressure detection limit of 0.2 Pa with a fast response time of 18.1 ms. Leveraging these properties, we further demonstrate a human somatosensory network analogous PVA-CE piezoionic skin using arrayed pressure sensing. These capabilities hold great promise for emerging healthcare applications such as synthetic biology, soft robotics, and beyond.

Molecular Evolution and Adaptation Strategies in Marine Ciliates: An Inspiration for Cold-Adapted Enzyme Engineering and Drug Binding Analysis.

In the present review, we summarize genome mining of genomic data obtained from the psychrophilic Antarctic marine ciliate Euplotes focardii and its evolutionary-close mesophilic cosmopolitan counterpart E. crassus. This analysis highlights adaptation strategies that are unique to the Antarctic ciliate, including antioxidant gene duplication and distinctive substitutions that may play roles in increased drug binding affinity and enzyme reaction rate in cold environments. Enzymes from psychrophiles are usually characterized by high activities and reaction rates at low temperatures compared with their counterparts from mesophiles and thermophiles. As a rule, catalyst cold activity derives from an increased structural flexibility that may lead to protein denaturation in response to temperature fluctuation. Molecular thermolability has been a major drawback of using macromolecules from psychrophiles in industrial applications. Here, we report a case study in which the role of peculiar amino acid substitution in cold adaptation is demonstrated by site-directed mutagenesis. Combined with a rational design approach, these substitutions can be used for site-directed mutagenesis to obtain cold-active catalysts that are structurally stable. Furthermore, molecular docking analysis of β-tubulin isotypes extrapolated from E. focardii and E. crassus genomes allowed us to obtain additional insight on the taxol binding site and drug affinity. E. focardii genome mining and the comparison with the mesophilic sibling counterpart can be used as an inspiration for molecular engineering for medical and industrial applications.

Rational design of a zinc-dependence secondary alcohol dehydrogenase to boost its oxidation activity for α-hydroxyketones biosynthesis

α-Hydroxyketones, which have significant industrial applications, can be sustainably synthesized through the oxidation of secondary alcohols using secondary alcohol dehydrogenase (SADH). However, the activity of the SADH oxidation reaction is generally low, making it unsuitable for large-scale production. In this study, a rational design approach was employed to computationally engineer SADH derived from Ogataea parapolymorpha (OpSADH), significantly enhancing its oxidation activity towards (R)-1,2-propanediol (PDO). The mutant M2 (S222T/S316A) exhibited a 14.2-fold increase in specific enzyme activity compared to the wild type (WT) and was employed as a catalyst for high-concentration hydroxyacetone production, facilitated by an NAD+ regeneration system. By applying an appropriate Zn2+ ion force field in molecular dynamics (MD) simulations, it was found that two mutation sites could stabilize the conformations of NAD+ and PDO, thereby revealing the molecular mechanism behind the enhanced activity of this metalloenzyme mutant. Notably, we first uncovered the dynamic mechanism by which four key residues (Cys39, His75, Glu76, and Glu175) and PDO within the active pocket contribute to the formation of coordination bonds with Zn2+. The findings of this study provide robust support for researching the catalytic mechanisms and dynamics processes of metalloenzymes.

Self-assembled Human Serum Protein-based Core-shell Nanoparticles to inhibit key oncogenic signalling in Drug-Resistant Leukemia

Simultaneous inhibition of multiple oncogenic signaling pathways is crucial for managing refractory cancers. This study introduces two unique core-shell nanoparticle (CS-NP) systems crafted from natural proteins that simultaneously target two crucial oncogenic pathways in refractory chronic myeloid leukemia (CML). Molecular analysis of approximately 14 refractory CML patients identified resistance to the standard treatment drug, imatinib, attributed to the overex-pression of the STAT5-transferrin pathway alongside the classic BCR-ABL fusion gene. To address this, we developed two dual-drug-loaded core-shell nanoparticles: (a) CS-NP1: Protamine sulfate nanocores carrying BCR-ABL siRNA and an albumin shell loaded with the STAT5 in-hibitor sorafenib, denoted as (PS-siRNA)-(Tf-Soraf) CS-NP; (b) CS-NP2: features a second-generation BCR-ABL inhibitor, dasatinib, in the albumin nanocore, and sorafenib in the transferrin nanoshell, labeled as (nAlb-Dasa)-(Tf-Soraf). We hypothesized that these dual-drug-loaded CS-NPs would effectively target both BCR-ABL and STAT5 pathways, with the transferrin nanoshell aiding in precise delivery to refractory CML cells overexpressing TfR1 due to STAT5 activity. Initial evaluations in drug resistant CML cell lines and patient-derived cells demonstrated significant cytotoxicity. Remarkably, even patients with BCR-ABL oncogene mutations displayed over 95% cytotoxicity with the CS-NPs. Furthermore, in vivo testing on a human xeno-graft model with a BCR-ABL+/+/STAT5+/+/TfR+/+ phenotype showcased a strong anti-tumor response. These results underscore the potential of a molecular-diagnosis-based rational design approach for protein-protein core-shell nanoparticles to simultaneously inhibit multiple oncogenic pathways, thereby overcoming resistance to targeted molecular therapies.

Naphthoindole-2-carboxamides as a lipophilic chemotype of hetarene-anthraquinones potent against P-gp resistant tumor cells

The acquisition of multidrug resistance (MDR) to chemotherapy is a major obstacle to successful cancer treatment. Aiming to improve the potency of anthraquinone-derived antitumor compounds against MDR cancer cells, we employed a rational design approach to develop new heteroarene-fused anthraquinones. Shifting the carboxamide group in the naphtho[2,3-f]indole scaffold from the 3-position to 2 increased the lipophilicity and P-glycoprotein (P-gp) binding of the derivatives, potentially enhancing their ability to circumvent P-gp-mediated MDR. To validate the computations, we developed a scheme for heterocyclization into esters of naphtho[2,3-f]indole-2-carboxylic acid, based on the 5-endo-dig cyclization of 2-alkynyl-3-amino-1,4-dimethoxyanthraquinone under mild basic conditions using tetra-n-butylammonium fluoride (TBAF). The synthesized naphthoindole-2-carboxamides, particularly compound 1a bearing (S)-3-aminopyrrolidine in the carboxamide fragment, demonstrated the highest antiproliferative activity. Most importantly, 1a suppressed the growth of the P-gp-positive K562/4 leukemia tumor cell line (resistance index = 2.4), while its 3-isomer LCTA-2640 and Dox did not (RI = 125 and 140, respectively). Studies of intracellular uptake and distribution showed that 1a, unlike its 3-substituted isomer, effectively accumulated in resistant tumor cells, confirming the correlation between in silico and experimental data. The lead compound 1a interacts with DNA duplex and inhibits topoisomerase 1 but does not induce oxidative stress. Treatment with 1a increases the population of apoptotic cells in both K562 and K562/4 sublines, regardless of the cell cycle phase. Taken together, this work provides an interesting example of how a little modification in chemical structure can lead to striking differences in antitumor properties. In conclusion, we have identified a potent class of compounds that offer distinct advantages in combating resistant tumor cells.

Challenges and perspectives in using unspecific peroxygenases for organic synthesis

In the past 20 years, unspecific peroxygenases (UPOs) have emerged as promising biocatalysts for various organic transformations. Particularly, we have witnessed great attention being paid to the screening of new enzymes and expansion of the substrates/products. However, challenges such as enzyme stability, low turnover numbers, and substrate specificity hinder their widespread utilization in practical organic synthesis. This review article provides a concrete and mini-overview of the challenges associated with using UPOs in organic synthesis and discusses strategies for enzyme engineering to overcome these limitations. The article highlights recent advancements in UPO research and presents potential solutions to enhance their catalytic efficiency, stability, substrate specificity, and regioselectivity. Additionally, the review outlines the current methodologies employed for directed evolution and protein engineering of UPOs, along with computational modeling approaches for rational enzyme design. By addressing the challenges and exploring avenues for enzyme engineering, this review aims to shed light on the prospects of UPOs in organic synthesis.

Leveraging Soft Acid-Base Interactions Alters the Pathway for Electrochemical Nitrogen Oxidation to Nitrate with High Faradaic Efficiency.

Electrocatalytic nitrogen oxidation reaction (N2OR) offers a sustainable alternative to the conventional methods such as the Haber-Bosch and Ostwald oxidation processes for converting nitrogen (N2) into high-value-added nitrate (NO3 -) under mild conditions. However, the concurrent oxygen evolution reaction (OER) and inefficient N2 absorption/activation led to slow N2OR kinetics, resulting in low Faradaic efficiencies and NO3 - yield rates. This study explored oxygen-vacancy induced tin oxide (SnO2-Ov) as an efficient N2OR electrocatalyst, achieving an impressive Faradaic efficiency (FE) of 54.2% and a notable NO3 - yield rate (22.05µg h-1 mgcat -1) at 1.7V versus reversible hydrogen electrode (RHE) in 0.1m Na2SO4. Experimental results indicate that SnO2-Ov possesses substantially more oxygen vacancies than SnO2, correlating with enhanced N2OR performance. Computational findings suggest that the superior performance of SnO2-Ov at a relatively low overpotential is due to reduced thermodynamic barrier for the oxidation of *N2 to *N2OH during the rate-determining step, making this step energetically favorable than the oxygen adsorption step for OER. This work demonstrates the feasibility of ambient nitrate synthesis on the soft acidic Sn active site and introduces a new approach for rational catalyst design.

Engineering Topological Spin Hall Effect in 2D Multiferroic Material.

Topological spin Hall effect (TSHE), promoted by coupling between noncoplanar spins and real-space topology, is a significant phenomenon in condensed matter physics. However, the control of TSHE characteristics is missing due to its intrinsic robustness, and such fundamental difficulty prevents it from being used for spintronics up to now. Here, a rational design approach is demonstrated to engineer TSHE in a controllable and reversible fashion. Through symmetry and model analysis, it is unveiled that antiferromagnetic topological charge, as well as Lorentz forces, acted on conduction electrons, can be coupled with Dzyaloshinskii-Moriya interaction chirality for antiferromagnetic bimerons in 2D multiferroic materials. Such coupling guarantees the ferroelectric control of TSHE. Using first-principles calculations and atomic spin model simulations, the validity of this mechanism is further demonstrated in multiferroic monolayer CuCr2Se4 with experimental feasibility. The alter-chirality of the Dzyaloshinskii-Moriya interaction is found to play a crucial role in realizing this mechanism. This results extend TSHE to be used in spintronics and open a new direction for spintronics research.

Bifunctional electrode materials: Enhancing microbial fuel cell efficiency with 3D hierarchical porous Fe3O4/Fe-N-C structures

The rational development of high-performance anode and cathode electrodes for microbial fuel cells (MFCs) is crucial for enhancing MFC performance. However, complex synthesis methods and single-performance electrode materials hinder their large-scale implementation. Here, three-dimensional hierarchical porous (3DHP) Fe3O4/Fe-N-C composites were prepared via the hard template method. Notably, Fe3O4/Fe-N-C-0.04-600 demonstrated uniformly dispersed Fe3O4 nanoparticles and abundant Fe-Nx and pyridinic nitrogen, showing excellent catalytic performance for oxygen reduction reaction (ORR) with a half-wave potential (E1/2) of 0.74 V (vs. RHE), surpassing Pt/C (0.66 V vs. RHE). Moreover, Fe3O4/Fe-N-C-0.04-600 demonstrated favorable biocompatibility as an anode material, enhancing anode biomass and extracellular electron transfer efficiency. Sequencing results confirmed its promotion of electrophilic microorganisms in the anode biofilm. MFCs employing Fe3O4/Fe-N-C-0.04-600 as both anode and cathode materials achieved a maximum power density of 831.8 ± 27.7 mW m−2, enduring operation for 38 days. This study presents a novel approach for rational MFC design, emphasizing bifunctional materials capable of serving as anode materials for microorganism growth and as cathode catalysts for ORR catalysis.

Integration of Open Metal Sites in an Amino-Functionalized Sm(III)-Organic Framework toward Enhanced Third-Order Nonlinear Optical Property.

A variety of new inorganic and organic materials have emerged to advance laser technologies and optical engineering. A rational design approach can contribute significantly to fabricating nonlinear optically active metal-organic frameworks (MOFs) by considering the underlying structure-property linkage. Here, it has been embarked on a study of novel samarium(III) MOF, ([Sm2(ata)3(DMF)4]·DMF (ata2-: 2-aminoterephthalate), abbreviated as NH2-Sm-MUM-4) with enhanced nonlinear optical (NLO) properties. The crystal structure of this MOF represents a 6-connected framework with a pcu topology and distinctive characteristics, including open metal sites, free amine groups, and great stability, making it suitable for third-order NLO activity. The nonlinear index of refraction (n2) revealed the self-focusing impacts of NH2-Sm-MUM-4 at different incident intensities. The highest value of n2 and β related to 10 mw power of incident intensity are 5.15 cm2/W and 2.65 cm/W, respectively. As far as the authors know, this is the first study examining the potential systematic structural-property associations in Sm-MOFs considering improved third-order NLO properties.

Computational Strategies to Enhance Cell-Free Protein Synthesis Efficiency

Cell-free protein synthesis (CFPS) has emerged as a powerful tool for protein production, with applications ranging from basic research to biotechnology and pharmaceutical development. However, enhancing the efficiency of CFPS systems remains a crucial challenge for realizing their full potential. Computational strategies offer promising avenues for optimizing CFPS efficiency by providing insights into complex biological processes and enabling rational design approaches. This review provides a comprehensive overview of the computational approaches aimed at enhancing CFPS efficiency. The introduction outlines the significance of CFPS and the role of computational methods in addressing efficiency limitations. It discusses mathematical modeling and simulation-based approaches for predicting protein synthesis kinetics and optimizing CFPS reactions. The review also delves into the design of DNA templates, including codon optimization strategies and mRNA secondary structure prediction tools, to improve protein synthesis efficiency. Furthermore, it explores computational techniques for engineering cell-free transcription and translation machinery, such as the rational design of expression systems and the predictive modeling of ribosome dynamics. The predictive modeling of metabolic pathways and the energy utilization in CFPS systems is also discussed, highlighting metabolic flux analysis and resource allocation strategies. Machine learning and artificial intelligence approaches are being increasingly employed for CFPS optimization, including neural network models, deep learning algorithms, and reinforcement learning for adaptive control. This review presents case studies showcasing successful CFPS optimization using computational methods and discusses applications in synthetic biology, biotechnology, and pharmaceuticals. The challenges and limitations of current computational approaches are addressed, along with future perspectives and emerging trends, such as the integration of multi-omics data and advances in high-throughput screening. The conclusion summarizes key findings, discusses implications for future research directions and applications, and emphasizes opportunities for interdisciplinary collaboration. This review offers valuable insights and prospects regarding computational strategies to enhance CFPS efficiency. It serves as a comprehensive resource, consolidating current knowledge in the field and guiding further advancements.

Integrating Deep Learning and Synthetic Biology: A Co-Design Approach for Enhancing Gene Expression via N-Terminal Coding Sequences.

N-terminal coding sequence (NCS) influences gene expression by impacting the translation initiation rate. The NCS optimization problem is to find an NCS that maximizes gene expression. The problem is important in genetic engineering. However, current methods for NCS optimization such as rational design and statistics-guided approaches are labor-intensive yield only relatively small improvements. This paper introduces a deep learning/synthetic biology codesigned few-shot training workflow for NCS optimization. Our method utilizes k-nearest encoding followed by word2vec to encode the NCS, then performs feature extraction using attention mechanisms, before constructing a time-series network for predicting gene expression intensity, and finally a direct search algorithm identifies the optimal NCS with limited training data. We took green fluorescent protein (GFP) expressed by Bacillus subtilis as a reporting protein of NCSs, and employed the fluorescence enhancement factor as the metric of NCS optimization. Within just six iterative experiments, our model generated an NCS (MLD62) that increased average GFP expression by 5.41-fold, outperforming the state-of-the-art NCS designs. Extending our findings beyond GFP, we showed that our engineered NCS (MLD62) can effectively boost the production of N-acetylneuraminic acid by enhancing the expression of the crucial rate-limiting GNA1 gene, demonstrating its practical utility. We have open-sourced our NCS expression database and experimental procedures for public use.

Integrating Computational Design and Experimental Approaches for Next-Generation Biologics.

Therapeutic protein engineering has revolutionized medicine by enabling the development of highly specific and potent treatments for a wide range of diseases. This review examines recent advances in computational and experimental approaches for engineering improved protein therapeutics. Key areas of focus include antibody engineering, enzyme replacement therapies, and cytokine-based drugs. Computational methods like structure-based design, machine learning integration, and protein language models have dramatically enhanced our ability to predict protein properties and guide engineering efforts. Experimental techniques such as directed evolution and rational design approaches continue to evolve, with high-throughput methods accelerating the discovery process. Applications of these methods have led to breakthroughs in affinity maturation, bispecific antibodies, enzyme stability enhancement, and the development of conditionally active cytokines. Emerging approaches like intracellular protein delivery, stimulus-responsive proteins, and de novo designed therapeutic proteins offer exciting new possibilities. However, challenges remain in predicting in vivo behavior, scalable manufacturing, immunogenicity mitigation, and targeted delivery. Addressing these challenges will require continued integration of computational and experimental methods, as well as a deeper understanding of protein behavior in complex physiological environments. As the field advances, we can anticipate increasingly sophisticated and effective protein therapeutics for treating human diseases.

Unveiling the Role of Dopants in the Electrochemical Ozone Production Reaction Using Tin Oxide Electrodes

Ozone is a strong oxidizer with promising environmentally friendly applications in water disinfection, air purification, and organic synthesis. The 6-e- electrochemical ozone production (EOP) reaction offers great potential for ozone generation while curbing the formation of harmful by-products compared to other ozone production methods. However, the development of electrochemical ozone production (EOP) catalysts is limited by significant hurdles dictated by thermodynamic limitations. In this work, we develop and validate a comprehensive guideline that outlines a strategic and rational design approach to induce EOP activity in tin oxide. We propose that two things are needed for tin oxide to produce ozone: increased conductivity, achieved with donor dopants, and first-row transition metal (TM) dopants to facilitate hydroperoxyl radical generation through Fenton-like processes. To validate our approach, we picked tantalum, antimony, and tungsten as donor dopants and nickel and cobalt as transition metals. Our results suggest that all combinations of TMs, oxidizable to a cationic state capable of producing hydroperoxyl radicals from hydrogen peroxide, and donor dopants lead to EOP activity in tin oxide.

Tailoring Co‐Free LiNi0.5Mn1.5O4 Material for High‐Voltage Lithium‐Ion Batteries: Particle Design & Grain Boundary Engineering

AbstractCobalt‐free LiNi0.5Mn1.5O4 (LNMO) is a promising cathode material for high‐energy and power‐density lithium‐ion batteries (LIBs). However, its commercial adoption is hindered by rapid capacity degradation due to the unstable LNMO/electrolyte interface caused by LNMO's high operating voltage. Structural degradation from Jahn–Teller distortion and metal‐ion dissolution also contributes to poor cycling stability. Additionally, producing industrial‐grade LNMO with high tap density, low surface area and reduced metal‐ion dissolution is challenging. This study addresses these challenges through a rational material design approach, synthesizing LNMO with large spherical secondary particles (>14.0 µm) and high tap density (>2.0 g cm−3). The primary particles (1.5–6.0 µm) exhibit a truncated‐octahedral shaped morphology that predominantly exposes (111) surface facets, with fewer (100) surfaces, stabilizing the LNMO/electrolyte interface, reducing metal dissolution, and enhancing lithium‐ion kinetics. Silicon infusion into grain boundaries further improves structural integrity by forming a silicon‐rich phase. The tailored LNMO demonstrates exceptional rate capability, cycling stability, and improved interfacial kinetics, significantly advancing the potential for cobalt‐free LNMO in high‐voltage LIBs. This work highlights the importance of tailored cathode material design for achieving the performance and stability required for emerging high‐voltage LIBs applications.

Rational design approach to improve the solubility of the β-sandwich domain 1 of a thermophilic protein

The beta-sandwich domain 1 (SD1) of islandisin is a stable thermophilic protein with surface loops that can be redesigned for specific target binding, architecturally comparable to the variable domain of immunoglobulin (IgG). SD1's propensity to aggregate due to incorrect folding and subsequent accumulation in E. coli inclusion bodies limits its use in biotechnological applications. We rationally designed SD1 for improved variants that were expressed in soluble forms in E. coli while maintaining the intrinsic thermal stability of the protein (melting temperature (Tm) = 73). We used FoldX's ΔΔG predictions to find beneficial mutations and aggregation-prone regions (APRs) using Tango. The S26K substitution within protein core residues did not affect protein stability. Among the soluble mutants studied, the S26K/Q91P combination significantly improved the expression and solubility of SD1. We also examined the effects of the surface residue, pH, and concentration on the solubility of SD1. We showed that the surface polarity of proteins had little or no effect on solubility, whereas surface charges played a substantial role. The storage stability of several SD1 variants was impaired at pH values near their pI, and pH levels resulting in highly charged groups. We observed that mutations that create an uneven distribution of charged groups on the SD1 surface could enhance protein solubility by eliminating favorable protein-protein surface charge interactions. Our findings suggest that SD1 is mutationally tolerant to new functionalities, thus providing a novel perspective for the application of rational design to improve the solubility of targeted proteins.

Protease-activated CendR peptides targeting tenascin-C: mitigating off-target tissue accumulation.

To achieve precision and selectivity, anticancer compounds and nanoparticles (NPs) can be targeted with affinity ligands that engage with malignancy-associated molecules in the blood vessels. While tumor-penetrating C-end Rule (CendR) peptides hold promise for precision tumor delivery, C-terminally exposed CendR peptides can accumulate undesirably in non-malignant tissues expressing neuropilin-1 (NRP-1), such as the lungs. One example of such promiscuous peptides is PL3 (sequence: AGRGRLVR), a peptide that engages with NRP-1 through its C-terminal CendR element, RLVR.Here, we report thedevelopment of PL3 derivatives that bind to NRP-1 only after proteolytic processing by urokinase-type plasminogen activator (uPA), while maintaining binding to the other receptor of the peptide, the C-domain of tenascin-C (TNC-C). Through a rational design approach and screening of a uPA-treated peptide-phage library (PL3 peptide followed by four random amino acids) on the recombinant NRP-1, derivatives of the PL3 peptide capable of binding to NRP-1 only post-uPA processing were successfully identified. In vitro cleavage, binding, and internalization assays, along with in vivo biodistribution studies in orthotopic glioblastoma-bearing mice, confirmed the efficacy of two novel peptides, PL3uCendR (AGRGRLVR↓SAGGSVA) and SKLG (AGRGRLVR↓SKLG), which exhibit uPA-dependent binding to NRP-1, reducing off-target binding to healthy NRP-1-expressing tissues. Our study not only unveils novel uPA-dependent TNC-C targeting CendR peptides but also introduces a broader paradigm and establishes a technology for screening proteolytically activated tumor-penetrating peptides.

Design of Linear-Polymer-Coated Graphene Nanosheets with π-Conjugated Structure and Multi-Active-Center for Long-Lifespan and High-Rate Li-Storage Performance.

Organic material holds immense potential for Li-ion batteries (LIBs) due to their eco-friendly nature, high structural designability, abundant sources, and high theoretical capacity. However, the limited redox-active sites, low electronic conductivity, sluggish ionic diffusion, and high solubility hinder their practical application. Here, we reported the use of a linear polymer called poly(naphthalenetetracarboxylic dianhydride-pyrene-4,5,9,10-tetraone)-coated graphene nanosheets (NPT/rGO) as a cathode material for LIBs. The NPT polymer has a rotation angle of approximately 63° between each plane, which helps in exposing the active sites and preventing structural pulverization during cycling. The highly conjugated skeleton of the polymer, along with graphene, forms a synergistic effect through a π-π interaction. This combination enhances the conductivity and restricts solubility. Additionally, the linear structure of NPT and the two-dimensional rGO substrates work together to enhance charge transfer and ion diffusion rates, resulting in faster reaction kinetics. Consequently, NPT/rGO exhibits excellent electrochemical performance in terms of high capacity, superior cyclic stability, and good rate capability for LIBs. Moreover, through the combination of experimental investigations and theoretical simulations, a multiple electron reaction mechanism, an efficient Li-ion storage behavior, and a reversible dynamic evolution have been revealed. This study introduces a rational molecular design approach to enhance the electrochemical performance of polyimide derivatives, thereby contributing to the advancement of cutting-edge organic electrode materials for LIBs.