Rapid SARS-CoV-2 Nucleic Acid Testing and Pooled Assay by Tetrahedral DNA Nanostructure Transistor.

Direct SARS-CoV-2 nucleic acid testing with fast speed and high frequency is crucial for controlling the COVID-19 pandemic. Here, direct testing of SARS-CoV-2 nucleic acid is realized by field-effect transistors (FETs) with an electro-enrichable liquid gate (LG) anchored by tetrahedral DNA nanostructures (TDNs). The applied gate bias electrostatically preconcentrates nucleic acids, while the liquid gate with TDNs provides efficient analyte recognition and signal transduction. The average diagnosis time is ∼80 s, and the limit of detection approaches 1-2 copies in 100 µL of clinical samples without nucleic acid extraction and amplification. As such, TDN-LG FETs solve the dilemma of COVID-19 testing on mass scale that diagnosis accuracy and speed undergo trade-off. In addition, TDN-LG FETs achieve unamplified 10-in-1 pooled nucleic acid testing for the first time, and the results are consistent with PCR. Thus, this technology promises on-site and wide population COVID-19 screening and ensures safe world-reopening.

A closed-loop catalytic nanoreactor system on a transistor.

Precision chemistry demands miniaturized catalytic systems for sophisticated reactions with well-defined pathways. An ideal solution is to construct a nanoreactor system functioning as a chemistry laboratory to execute a full chemical process with molecular precision. However, existing nanoscale catalytic systems fail to in situ control reaction kinetics in a closed-loop manner, lacking the precision toward ultimate reaction efficiency. We find an inter-electrochemical gating effect when operating DNA framework-constructed enzyme cascade nanoreactors on a transistor, enabling in situ closed-loop reaction monitoring and modulation electrically. Therefore, a comprehensive system is developed, encapsulating nanoreactors, analyzers, and modulators, where the gate potential modulates enzyme activity and switches cascade reaction "ON" or "OFF." Such electric field-effect property enhances catalytic efficiency of enzyme by 343.4-fold and enables sensitive sarcosine assay for prostate cancer diagnoses, with a limit of detection five orders of magnitude lower than methodologies in clinical laboratory. By coupling with solid-state electronics, this work provides a perspective to construct intelligent nano-systems for precision chemistry.

Combining mass spectrometry and machine learning to discover bioactive peptides.

Peptides play important roles in regulating biological processes and form the basis of a multiplicity of therapeutic drugs. To date, only about 300 peptides in human have confirmed bioactivity, although tens of thousands have been reported in the literature. The majority of these are inactive degradation products of endogenous proteins and peptides, presenting a needle-in-a-haystack problem of identifying the most promising candidate peptides from large-scale peptidomics experiments to test for bioactivity. To address this challenge, we conducted a comprehensive analysis of the mammalian peptidome across seven tissues in four different mouse strains and used the data to train a machine learning model that predicts hundreds of peptide candidates based on patterns in the mass spectrometry data. We provide in silico validation examples and experimental confirmation of bioactivity for two peptides, demonstrating the utility of this resource for discovering lead peptides for further characterization and therapeutic development.

Structure-based virtual screening for identification of novel 11beta-HSD1 inhibitors.

Structure-based pharmacophore models were built by using LigandScout and used for virtual screening of the SPECS database to identify new potential 11beta-HSD1 inhibitors. As a refinement of the results obtained from virtual 3D pharmacophore screening, the best fitting virtual hits were subjected to docking study. The resulting compounds were tested in an enzyme assay and revealed several compounds with novel scaffolds that show sub-micromolar activity and high selectivity for 11beta-HSD1 against 11beta-HSD2.

Identification of core functional region of murine IL-4 using peptide phage display and molecular modeling.

Murine IL-4 is a pleiotropic cytokine with undefined core functional region for eliciting downstream signaling. We used molecular modeling to predict the binding sites recognized by an anti-IL-4-neutralizing mAb (11B.11) and peptide phage display to delineate their makeup. The results of these approaches were confirmed by site-directed mutagenesis analysis. The results suggest that the amino acid residues spanning from 79 to 86 (QRLFRAFR) on IL-4 are of the major binding site for 11B.11. Furthermore, the functional experiments demonstrate that the residues R80, R83 and R86, which are located in the helix C of murine IL-4, play a crucial role in binding to the IL-4R alpha-chain. Taken together, a new core functional region of murine IL-4 is identified, which provides new insight into the interaction between IL-4 and IL-4Ralpha. In addition, the results demonstrate that 11B.11 binds to a core functional region of murine IL-4, which prevents this cytokine from interacting with its cognate receptor.