In vitro selection of allosteric ribozymes has many challenges, such as complex and time-consuming experimental procedures, uncertain results, and the unwanted functionality of the enriched sequences. The precise computational design of allosteric ribozymes is achievable using RNA secondary structure folding principles. The computational design of allosteric ribozymes is based on experimentally validated EAs, random search algorithms, and a partition function for RNA folding. The in silico design achieves an accuracy exceeding 90%. Various algorithms with different logic gates have been automated via computer programs that can quickly create many allosteric sequences. This can eliminate the need for in vitro selection of allosteric ribozymes, thus vastly reducing the time and cost required.

Over the past two decades, therapeutic antibodies have emerged as a rapidly expanding domain within the field of biologics. In silico tools that can streamline the process of antibody discovery and optimization are critical to support a pipeline that is growing more numerous and complex every year. High-quality structural information remains critical for the antibody optimization process, but antibody-antigen complex structures are often unavailable and in silico antibody docking methods are still unreliable. In this study, DeepAb, a deep learning model for predicting antibody Fv structure directly from sequence, was used in conjunction with single-point experimental deep mutational scanning (DMS) enrichment data to design 200 potentially optimized variants of an anti-hen egg lysozyme (HEL) antibody. We sought to determine whether DeepAb-designed variants containing combinations of beneficial mutations from the DMS exhibit enhanced thermostability and whether this optimization affected their developability profile. The 200 variants were produced through a robust high-throughput method and tested for thermal and colloidal stability (Tonset, Tm, Tagg), affinity (KD) relative to the parental antibody, and for developability parameters (nonspecific binding, aggregation propensity, self-association). Of the designed clones, 91% and 94% exhibited increased thermal and colloidal stability and affinity, respectively. Of these, 10% showed a significantly increased affinity for HEL (5- to 21-fold increase) and thermostability (>2.5C increase in Tm1), with most clones retaining the favorable developability profile of the parental antibody. Additional in silico tests suggest that these methods would enrich for binding affinity even without first collecting experimental DMS measurements. These data open the possibility of in silico antibody optimization without the need to predict the antibody-antigen interface, which is notoriously difficult in the absence of crystal structures.

Converting CO2 into value-added chemicals still remains a grand challenge. Succinic acid has long been considered as one of the top building block chemicals. This study reported efficiently upcycling CO2 into succinic acid by combining between electrochemical and engineered Escherichia coli. In this process, the Cu-organic framework catalyst was synthesized for electrocatalytic CO2-to-ethanol conversion with high Faradaic efficiency (FE, 84.7 %) and relative purity (RP, 95 wt%). Subsequently, an engineered E. coli with efficiently assimilating CO2-derived ethanol to produce succinic acid was constructed by combining computational design and metabolic engineering, and the succinic acid titer reached 53.8 mM with the yield of 0.41 mol/mol, which is 82 % of the theoretical yield. This study effort to link the two processes of efficient ethanol synthesis by electrocatalytic CO2 and succinic acid production from CO2-derived ethanol, paving a way for the production of succinic acid and other value-added chemicals by converting CO2 into ethanol.

This study presented a new method to design a MIP-based electrochemical sensor that could improve the selective and sensitive detection of ipratropium bromide (IPR). The polymeric film was designed using 2-hydroxyethyl methacrylate (HEMA) as the basic monomer, 2-hydroxy-2-methylpropiophenone as the initiator, ethylene glycol dimethacrylate (EGDMA) as the crosslinking agent, and N-methacryloyl-L-aspartic acid (MAAsp) as the functional monomer. The presence of MAAsp results in the functional groups in imprinting binding sites, while the presence of poly(vinyl alcohol) (PVA) allows the generation of porous materials not only for sensitive sensing but also for avoiding electron transport limitations. Electrochemical characterizations of the changes at each stage of the MIP preparation process were confirmed using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). In addition, morphological characterizations of the developed sensor were performed using scanning electron microscopy (SEM), attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR), and contact angle measurements. Theoretical calculations were also performed to explain/confirm the experimental results better. It was found that the results of the calculations using the DFT approach agreed with the experimental data. The MAAsp-IPR@MIP/GCE sensor was developed using the photopolymerization method, and the sensor surface was obtained by exposure to UV lamp radiation at 365 nm. The improved MIP-based electrochemical sensor demonstrated the ability to measure IPR for standard solutions in the linear operating range of 1.0 × 10-12-1.0 × 10-11 M under optimized conditions. For standard solutions, the limit of detection (LOD) and limit of quantification (LOQ) were obtained as 2.78 × 10-13 and 9.27 × 10-13 M, respectively. The IPR recovery values for the inhalation form were calculated as 101.70 % and 100.34 %, and the mean relative standard deviations (RSD) were less than 0.76 % in both cases. In addition, the proposed modified sensor demonstrated remarkable sensitivity and selectivity for rapid assessment of IPR in inhalation forms. The sensor\'s unique selectivity is demonstrated by its successful performance even in the presence of IPR impurities.

In this study, the first nanomaterial-supported molecularly imprinted polymer (MIP)-based electrochemical approach was proposed to achieve the successful detection of cefdinir (CFD). Here, p-amino benzoic acid (p-ABA) was used as the monomer and the photopolymerization method was chosen to form MIP on a glassy carbon electrode (GCE). ZnO nanoparticles (ZnO NPs) were added to the MIP sensor to increase sensitivity and create high porosity. Through the use of cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS), characterization investigations confirmed the alterations at each stage of the MIP production process. Electrochemical (cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS)) and scanning electron microscopy (SEM) methods were used for study the characterization studies of the MIP-based nanocomposite sensor. The measurement of MIP parameters, such as the addition of nanoparticles, the removal procedure, the rebinding period, the monomer ratio, etc., was done using the differential pulse voltammetry (DPV). The findings showed that when ZnO NPs were added, the signal was three times higher than when MIPs were used alone. Under the optimized conditions, CFD/4-ABA@ZnONPs/MIP/GCE showed a linear response in the concentration range between 7.5 pM and 100 pM with LOD and LOQ values of 2.06 pM and 6.86 pM, respectively. Anions, cations, and substances including uric acid, ascorbic acid, paracetamol, and dopamine were all used in the selectivity test. In addition, the imprinting factor (IF) study was carried out using compounds such as cefuroxime, cefazolin, cefixime, ceftazidime, and ceftriaxone, which have structural similarities with CFD, as well as impurities such as thiazolylacetyl glycine oxime (IMP-A), thiazolylacetyl glycine oxime acetal (IMP-B), and cefdinir lactone (IMP-E). The results showed that the proposed sensor was selective for CFD, as evidenced by the relative IF values of these impurities. The recovery studies of CFD were successfully applied to tablet dosage form samples, and the developed sensor demonstrated significant sensitivity and selectivity for rapid detection of CFD in tablet dosage form.

The limited success of current targeted therapies for pancreatic cancer underscores an urgent demand for novel treatment modalities. The challenge in mitigating this malignancy can be attributed to the digestive organ expansion factor (DEF), a pivotal yet underexplored factor in pancreatic tumorigenesis. The study uses a blend of in vitro and in vivo approaches, complemented by the theoretical analyses, to propose DEF as a promising anti-tumor target. Analysis of clinical samples reveals that high expression of DEF is correlated with diminished survival in pancreatic cancer patients. Crucially, the depletion of DEF significantly impedes tumor growth. The study further discovers that DEF binds to p65, shielding it from degradation mediated by the ubiquitin-proteasome pathway in cancer cells. Based on these findings and computational approaches, the study formulates a DEF-mimicking peptide, peptide-031, designed to disrupt the DEF-p65 interaction. The effectiveness of peptide-031 in inhibiting tumor proliferation has been demonstrated both in vitro and in vivo. This study unveils the oncogenic role of DEF while highlighting its prognostic value and therapeutic potential in pancreatic cancer. In addition, peptide-031 is a promising therapeutic agent with potent anti-tumor effects.

Carbon disulfide (CS2) is an environmental contaminant, which is deadly hazardous to the workers under chronic or acute exposure. However, the toxicity mechanisms of CS2 are still unclear due to the scarcity of biocompatible donors, which can release CS2 in cells. Here we developed the first bioorthogonal CS2 delivery system based on the \"click-and-release\" reactions between mesoionic 1,3-thiazolium-5-thiolates (TATs) and strained cyclooctyne exo-BCN-OH. We successfully realized intracellular CS2 release and investigated the causes of CS2-induced hepatotoxicity, including oxidative stress, proteotoxic stress and copper-dependent cell death. It is found that CS2 can be copper vehicles bypassing copper transporters after reacting with nucleophiles in cytoplasm, and extra copper supplementation will exacerbate the loss of homeostasis of cells and ultimately cell death. These findings inspired us to explore the anticancer activity of CS2 in combination with copper by introducing a copper chelating group in our CS2 delivery system.

As the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues its global spread, the exploration of novel therapeutic and diagnostic strategies is still needed. The virus enters host cells by binding the angiotensin-converting enzyme 2 (ACE2) receptor through the spike protein. Here, we develop an engineered, small, stable, and catalytically inactive version of ACE2, termed miniature ACE2 (mACE2), designed to bind the spike protein with high affinity. Employing a magnetic nanoparticle-based assay, we harnessed the strong binding affinity of mACE2 to develop a sensitive and specific platform for the detection or neutralization of SARS-CoV-2. Our findings highlight the potential of engineered mACE2 as a valuable tool in the fight against SARS-CoV-2. The success of developing such a small reagent based on a piecewise molecular design serves as a proof-of-concept approach for the rapid deployment of such agents to diagnose and fight other viral diseases.

Stabilizing proteins without otherwise hampering their function is a central task in protein engineering and design. PYR1 is a plant hormone receptor that has been engineered to bind diverse small molecule ligands. We sought a set of generalized mutations that would provide stability without affecting functionality for PYR1 variants with diverse ligand-binding capabilities. To do this we used a global multi-mutant analysis (GMMA) approach, which can identify substitutions that have stabilizing effects and do not lower function. GMMA has the added benefit of finding substitutions that are stabilizing in different sequence contexts and we hypothesized that applying GMMA to PYR1 with different functionalities would identify this set of generalized mutations. Indeed, conducting FACS and deep sequencing of libraries for PYR1 variants with two different functionalities and applying a GMMA analysis identified 5 substitutions that, when inserted into four PYR1 variants that each bind a unique ligand, provided an increase of 2-6 °C in thermal inactivation temperature and no decrease in functionality.

Nicotinamide adenine dinucleotide phosphate (NADPH), as a well-known cofactor, is widely used in the most of enzymatic redox reactions, playing an important role in industrial catalysis. However, the absence of a comparable method for efficient NADP+ to NADPH cofactor regeneration radically impairs efficient green chemical synthesis. Alcohol dehydrogenase (ADH) enzymes, allowing the in situ regeneration of the redox cofactor NADPH with high specific activity and easy by-product separation process, are provided with great industrial application potential and research attention. Accordingly, herein a NADP+-specific ADH from Clostridium beijerinckii was selected to be engineered for cofactor recycle, using an automated algorithm named Protein Repair One-stop Shop (PROSS). The mutant CbADH-6M (S24P/G182A/G196A/H222D/S250E/S254R) exhibited a favorable soluble and highly active expression with an activity of 46.3 U/mL, which was 16 times higher than the wild type (2.9 U/mL), and a more stable protein conformation with an enhanced thermal stability: Δ T 1 / 2 60 min =  + 3.6 °C (temperature of 50% inactivation after incubation for 60 min). Furthermore, the activity of CbADH-6M was up-graded to 2401.8 U/mL by high cell density fermentation strategy using recombinant Escherichia coli, demonstrating its industrial potential. Finally, the superb efficiency for NADPH regeneration of the mutant enzyme was testified in the synthesis of some fine chiral aromatic alcohols coupling with another ADH from Lactobacillus kefir (LkADH).