A small-molecule activation mechanism that directly opens the KCNQ2 channel.

Pharmacological activation of voltage-gated ion channels by ligands serves as the basis for therapy and mainly involves a classic gating mechanism that augments the native voltage-dependent open probability. Through structure-based virtual screening, we identified a new scaffold compound, Ebio1, serving as a potent and subtype-selective activator for the voltage-gated potassium channel KCNQ2 and featuring a new activation mechanism. Single-channel patch-clamp, cryogenic-electron microscopy and molecular dynamic simulations, along with chemical derivatives, reveal that Ebio1 engages the KCNQ2 activation by generating an extended channel gate with a larger conductance at the saturating voltage (+50 mV). This mechanism is different from the previously observed activation mechanism of ligands on voltage-gated ion channels. Ebio1 caused S6 helices from residues S303 and F305 to perform a twist-to-open movement, which was sufficient to open the KCNQ2 gate. Overall, our findings provide mechanistic insights into the activation of KCNQ2 channel by Ebio1 and lend support for KCNQ-related drug development.

DNA-framework-based multidimensional molecular classifiers for cancer diagnosis.

A molecular classification of diseases that accurately reflects clinical behaviour lays the foundation of precision medicine. The development of in silico classifiers coupled with molecular implementation based on DNA reactions marks a key advance in more powerful molecular classification, but it nevertheless remains a challenge to process multiple molecular datatypes. Here we introduce a DNA-encoded molecular classifier that can physically implement the computational classification of multidimensional molecular clinical data. To produce unified electrochemical sensing signals across heterogeneous molecular binding events, we exploit DNA-framework-based programmable atom-like nanoparticles with n valence to develop valence-encoded signal reporters that enable linearity in translating virtually any biomolecular binding events to signal gains. Multidimensional molecular information in computational classification is thus precisely assigned weights for bioanalysis. We demonstrate the implementation of a molecular classifier based on programmable atom-like nanoparticles to perform biomarker panel screening and analyse a panel of six biomarkers across three-dimensional datatypes for a near-deterministic molecular taxonomy of prostate cancer patients.

General Pharmacological Activation Mechanism of K+ Channels Bypassing Channel Gates.

Under the known pharmacological activation mechanisms, activators allosterically or directly open potassium channel gates. However, herein, molecular dynamics simulations on TREK-1, a member of the channel class gated at the filter, suggested that negatively charged activators act with a gate-independent mechanism where compounds increase currents by promoting ions passing through the central cavity. Then, based on studies of KCNQ2, we uncovered that this noncanonical activation mechanism is shared by the other channel class gated at the helix-bundle crossing. Rational drug design found a novel KCNQ2 agonist, CLE030, which stably binds to the central cavity. Functional analysis, molecular dynamics simulations, and calculations of the potential of mean force revealed that the carbonyl oxygen of CLE030 influences permeant ions in the central cavity to contribute to its activation effects. Together, this study discovered a ligand-to-ion activation mechanism for channels that bypasses their gates and thus is conserved across subfamilies with different gates.

Inhibiting Hv1 channel in peripheral sensory neurons attenuates chronic inflammatory pain and opioid side effects.

Both opioids and nonsteroidal anti-inflammatory drugs (NSAIDS) produce deleterious side effects and fail to provide sustained relief in patients with chronic inflammatory pain. Peripheral neuroinflammation (PN) is critical for initiation and development of inflammatory pain. A better understanding of molecular mechanisms underlying PN would facilitate the discovery of new analgesic targets and the development of new therapeutics. Emerging evidence suggests that peripheral sensory neurons are not only responders to painful stimuli, but are also actively engaged in inflammation and immunity, whereas the intrinsic regulatory mechanism is poorly understood. Here we report the expression of proton-selective ion channel Hv1 in peripheral sensory neurons in rodents and humans, which was previously shown as selectively expressed in microglia in mammalian central nervous system. Neuronal Hv1 was up-regulated by PN or depolarizing stimulation, which in turn aggravates inflammation and nociception. Inhibiting neuronal Hv1 genetically or by a newly discovered selective inhibitor YHV98-4 reduced intracellular alkalization and ROS production in inflammatory pain, mitigated the imbalance in downstream SHP-1-pAKT signaling, and also diminished pro-inflammatory chemokine release to alleviate nociception and morphine-induced hyperalgesia and tolerance. Thus, our data reveal neuronal Hv1 as a novel target in analgesia strategy and managing opioids-related side effects.

'C-type' closed state and gating mechanisms of K2P channels revealed by conformational changes of the TREK-1 channel.

Two-pore domain potassium (K2P) channels gate primarily within the selectivity filter, termed 'C-type' gating. Due to the lack of structural insights into the nonconductive (closed) state, 'C-type' gating mechanisms remain elusive. Here, molecular dynamics (MD) simulations on TREK-1, a K2P channel, revealed that M4 helix movements induce filter closing in a novel 'deeper-down' structure that represents a 'C-type' closed state. The 'down' structure does not represent the closed state as previously proposed and instead acts as an intermediate state in gating. The study identified the allosteric 'seesaw' mechanism of M4 helix movements in modulating filter closing. Finally, guided by this recognition of K2P gating mechanisms, MD simulations revealed that gain-of-function mutations and small-molecule activators activate TREK-1 by perturbing state transitions from open to closed states. Together, we reveal a 'C-type' closed state and provide mechanical insights into gating procedures and allosteric regulations for K2P channels.

Programming bulk enzyme heterojunctions for biosensor development with tetrahedral DNA framework.

Protein-protein interactions are spatially regulated in living cells to realize high reaction efficiency, as seen in naturally existing electron-transfer chains. Nevertheless, arrangement of chemical/biochemical components at the artificial device interfaces does not possess the same level of control. Here we report a tetrahedral DNA framework-enabled bulk enzyme heterojunction (BEH) strategy to program the multi-enzyme catalytic cascade at the interface of electrochemical biosensors. The construction of interpenetrating network of BEH at the millimeter-scale electrode interface brings enzyme pairs within the critical coupling length (CCL) of ~10 nm, which in turn greatly improve the overall catalytic cascade efficiency by ~10-fold. We demonstrate the BEH generality with a range of enzyme pairs for electrochemically detecting clinically relevant molecular targets. As a proof of concept, a BEH-based sarcosine sensor enables single-step detection of the metabolic biomarker of sarcosine with ultrasensitivity, which hold the potential for precision diagnosis of early-stage prostate cancer.

Valency-Controlled Framework Nucleic Acid Signal Amplifiers.

Weak ligand-receptor recognition events are often amplified by recruiting multiple regulatory biomolecules to the action site in biological systems. However, signal amplification in in vitro biomimetic systems generally lack the spatiotemporal regulation in vivo. Herein we report a framework nucleic acid (FNA)-programmed strategy to develop valence-controlled signal amplifiers with high modularity for ultrasensitive biosensing. We demonstrated that the FNA-programmed signal amplifiers could recruit nucleic acids, proteins, and inorganic nanoparticles in a stoichiometric manner. The valence-controlled signal amplifier enhanced the quantification ability of electrochemical biosensors, and enabled ultrasensitive detection of tumor-relevant circulating free DNA (cfDNA) with sensitivity enhancement of 3-5 orders of magnitude and improved dynamic range.

DNA Tetrahedral Nanostructure-Based Electrochemical miRNA Biosensor for Simultaneous Detection of Multiple miRNAs in Pancreatic Carcinoma.

Specific and sensitive biomarker detection is essential to early cancer diagnosis. In this study, we demonstrate an ultrasensitive electrochemical biosensor with the ability to detect multiple pancreatic carcinoma (PC)-related microRNA biomarkers. By employing DNA tetrahedral nanostructure capture probes to enhance the detection sensitivity as well as a disposable 16-channel screen-printed gold electrode (SPGE) detection platform to enhance the detection efficiency, we were able to simultaneously detect four PC-related miRNAs: miRNA21, miRNA155, miRNA196a, and miRNA210. The detection sensitivity reached to as low as 10 fM. We then profiled the serum levels of the four miRNAs for PC patients and healthy individuals with our multiplexing electrochemical biosensor. Through the combined analyses of the four miRNAs, our results showed that PC patients could be discriminated from healthy controls with fairly high sensitivity. This multiplexing PCR-free miRNA detection sensor shows promising applications in early diagnosis of PC disease.

Preservation of DNA Nanostructure Carriers: Effects of Freeze-Thawing and Ionic Strength during Lyophilization and Storage.

DNA nanostructures have attracted wide interest in biomedical applications, especially as nanocarriers for drug delivery. Therefore, it is important to ensure the structural integrity of DNA nanostructures under ambient temperature storage. In this study, we examined lyophilization-based preservation of DNA nanostructures by investigating the structural integrity of different DNA nanostructures reconstituted from lyophilization. We demonstrated that lyophilization under appropriate ionic strength is amenable to the storage of DNA nanostructures. Compared with that stored in liquid solution, DNA nanostructure carriers reconstituted from lyophilization showed significantly better structural integrity after an accelerated aging test equivalent to 100-day room-temperature storage.

Dynamic Modulation of DNA Hybridization Using Allosteric DNA Tetrahedral Nanostructures.

The fixed dynamic range of traditional biosensors limits their utility in several real applications. For example, viral load monitoring requires the dynamic range spans several orders of magnitude; whereas, monitoring of drugs requires extremely narrow dynamic range. To overcome this limitation, here, we devised tunable biosensing interface using allosteric DNA tetrahedral bioprobes to tune the dynamic range of DNA biosensors. Our strategy takes the advantage of the readily and flexible structure design and predictable geometric reconfiguration of DNA nanotechnology. We reconfigured the DNA tetrahedral bioprobes by inserting the effector sequence into the DNA tetrahedron, through which, the binding affinity of DNA tetrahedral bioprobes can be tuned. As a result, the detection limit of DNA biosensors can be programmably regulated. The dynamic range of DNA biosensors can be tuned (narrowed or extended) for up to 100-fold. Using the regulation of binding affinity, we realized the capture and release of biomolecules by tuning the binding behavior of DNA tetrahedral bioprobes.

PolyA-Mediated DNA Assembly on Gold Nanoparticles for Thermodynamically Favorable and Rapid Hybridization Analysis.

Understanding the behavior of biomolecules on nanointerface is critical in bioanalysis, which is great challenge due to the instability and the difficulty to control the orientation and loading density of biomolecules. Here, we investigated the thermodynamics and kinetics of DNA hybridization on gold nanoparticle, with the aim to improve the efficiency and speed of DNA analysis. We achieved precise and quantitative surface control by applying a recently developed poly adenines (polyA)-based assembly strategy on gold nanoparticles (DNA-AuNPs). PolyA served as an effective anchoring block based on the preferential binding with the AuNP surface and the appended recognition block adopted an upright conformation that favors DNA hybridization. The lateral spacing and surface density of DNA on AuNPs can be systematically modulated by adjusting the length of polyA block. We found the stability of duplex on AuNP was enhanced with the increasing length of polyA block. When the length of polyA block reached to 40 bases, the thermodynamic properties were more similar to that of duplex in solution. Fast hybridization rate was observed on the diblock DNA-AuNPs and was increased along with the length of polyA block. We consider the high stability and excellent hybridization performance come from the minimization of the DNA-DNA and DNA-AuNP interactions with the use of polyA block. This study provides better understanding of the behavior of biomolecules on the nanointerface and opens new opportunities to construct high-efficiency and high-speed biosensors for DNA analysis.

Personalized evaluation based on quantitative proteomics for drug-treated patients with chronic kidney disease.

The patient's response to drug treatment is usually systems-wide based on multi-spots through either direct or indirect targets. Thus, the evaluation of the treatment cannot rely on single targeted biomarker, especially for complex diseases such as chronic kidney disease. In the present study, we performed a systems-wide analysis using proteomic approach to quantify changes in the proteomic profiles of the plasma from IgA nephropathy (IgAN) patients before and after treatment. In particular, the patient-to-health distances based on global proteome quantification before and after treatment were calculated and considered as quantitative readouts to measure patient divergences from the healthy condition. We found that the patient-to-health distance nicely correlated with the patient's response to drug treatment and long-term prognosis, which created a self-tracking platform for personalized evaluation. In addition, the steroid treatment plays a role in immunosuppression, while the Chinese Traditional Medicine (TCM) can modulate whole-body systems. Our results indicated that STC therapy normalized the proteomic profile more significantly than SA therapy. This work provides an omics-based and systematic platform for personalized evaluation of disease treatment. This strategy could help us to evaluate treatment outcomes and predict prognosis in patients with IgAN and other complex diseases.

Predicting protein-protein interactions based only on sequences information.

Protein-protein interactions (PPIs) are central to most biological processes. Although efforts have been devoted to the development of methodology for predicting PPIs and protein interaction networks, the application of most existing methods is limited because they need information about protein homology or the interaction marks of the protein partners. In the present work, we propose a method for PPI prediction using only the information of protein sequences. This method was developed based on a learning algorithm-support vector machine combined with a kernel function and a conjoint triad feature for describing amino acids. More than 16,000 diverse PPI pairs were used to construct the universal model. The prediction ability of our approach is better than that of other sequence-based PPI prediction methods because it is able to predict PPI networks. Different types of PPI networks have been effectively mapped with our method, suggesting that, even with only sequence information, this method could be applied to the exploration of networks for any newly discovered protein with unknown biological relativity. In addition, such supplementary experimental information can enhance the prediction ability of the method.