Molecular basis of receptor binding and antibody neutralization of Omicron.

The SARS-CoV-2 Omicron variant exhibits striking immune evasion and is spreading rapidly worldwide. Understanding the structural basis of the high transmissibility and enhanced immune evasion of Omicron is of high importance. Here, using cryo-electron microscopy, we present both the closed and the open states of the Omicron spike (S) protein, which appear more compact than the counterparts of the G614 strain1, potentially related to enhanced inter-protomer and S1-S2 interactions induced by Omicron residue substitution. The closed state showing dominant population may indicate a conformational masking mechanism for the immune evasion of Omicron. Moreover, we captured three states for the Omicron S-ACE2 complex, revealing that the substitutions on the Omicron RBM result in new salt bridges and hydrogen bonds, more favourable electrostatic surface properties, and an overall strengthened S-ACE2 interaction, in line with the observed higher ACE2 affinity of Omicron S than of G614. Furthermore, we determined the structures of Omicron S in complex with the Fab of S3H3, an antibody that is able to cross-neutralize major variants of concern including Omicron, elucidating the structural basis for S3H3-mediated broad-spectrum neutralization. Our findings shed light on the receptor engagement and antibody neutralization or evasion of Omicron and may also inform the design of broadly effective vaccines against SARS-CoV-2.

Distinct architecture and composition of mouse axonemal radial spoke head revealed by cryo-EM.

The radial spoke (RS) heads of motile cilia and flagella contact projections of the central pair (CP) apparatus to coordinate motility, but the morphology is distinct for protozoa and metazoa. Here we show the murine RS head is compositionally distinct from that of Chlamydomonas Our reconstituted murine RS head core complex consists of Rsph1, Rsph3b, Rsph4a, and Rsph9, lacking Rsph6a and Rsph10b, whose orthologs exist in the protozoan RS head. We resolve its cryo-electron microscopy (cryo-EM) structure at 3.2-Å resolution. Our atomic model further reveals a twofold symmetric brake pad-shaped structure, in which Rsph4a and Rsph9 form a compact body extended laterally with two long arms of twisted Rsph1 ß-sheets and potentially connected dorsally via Rsph3b to the RS stalk. Furthermore, our modeling suggests that the core complex contacts the periodic CP projections either rigidly through its tooth-shaped Rsph4a regions or elastically through both arms for optimized RS-CP interactions and mechanosignal transduction.

Thermally activated upconversion luminescence and ratiometric temperature sensing under 1064 nm/808 nm excitation.

In this research, a thermally activated upconversion luminescence (UCL) probe with ratiometric temperature sensing under 1064 nm and 808 nm excitation was designed. Especially, Nd3+, Tm3+and Ce3+were doped in rare earth nanoparticles (RENPs) as UCL modulators. By optimizing the elements and ratios, the excitation wavelength is successfully modulated to 1064 nm excitation with UCL intensity enhanced. Additionally, the prepared RENPs have a significant temperature response at 1064 nm excitation and can be used for thermochromic coatings. The intensity ratio of three-photon UCL (1064 nm excitation) to two-photon UCL (808 nm excitation) as an exponential function of temperature can be used as a ratiometric temperature detector. Therefore, this designed thermochromic coatings may enable new applications in optoelectronic device and industrial sensor.

A mechanoluminescent material, ZnS:Mn,Li, with enhanced brightness for visualizing dental occlusion.

Mechanoluminescent materials are characterized by high luminescence intensity, high repeatability, no external voltage activation, and a good linear relationship between stress and mechanoluminescence intensity within a certain range. Therefore, mechanoluminescent materials have attracted increasing attention from researchers in the fields of stress sensing, encryption and anti-counterfeiting, structural health monitoring, energy-saving lighting, intelligent wearable devices, and other fields. In this study, ZnS:Mn powders with different Mn2+ ratios and different ion doping were synthesized by a high-temperature solid-phase reaction, and the synthesis of various materials was characterized. Then, the optimal mechanoluminescence effect of the ZnS:1%Mn,1%Li material was obtained. The photoluminescence intensity of ZnS:1%Mn,1%Li was 16.7 times higher than that of the sample without doping with Li+, and the mechanoluminescence intensity was 1.64 times higher. Finally, polyethylene terephthalate (PET) film was combined with ZnS:Mn,Li mechanoluminescent powders to prepare flexible three-layer composite film. Based on this, a feasible strategy for the detection of temporomandibular disorders was proposed. The composite film is easy to use, economical, and safe, and has good mechanoluminescent performance, which has potential application value in the field of occlusal force detection and visualization.

Genetic effect of an InDel in the promoter region of the NUDT15 and its effect on myoblast proliferation in chickens.

BACKGROUND: Molecular breeding accelerates the speed of animal breeding. Screening molecular markers that can affect economic traits through genome-wide association studies (GWAS) can provide a theoretical basis for molecular breeding. At present, a large number of molecular markers have been screened in poultry research, but few reports on how molecular markers affect economic traits exist. It is particularly important to reveal the action mechanisms of molecular markers, which can provide more accurate information for molecular breeding. RESULTS: The aim of this study was to investigate the relationships between two indels (NUDT15-indel-2777 and NUDT15-indel-1673) in the promoter region of NUDT15 and growth and carcass traits in chickens and to explore the regulatory mechanism of NUDT15. Significant differences were found in genotype and allele frequencies among commercial broilers, commercial laying hens and dual-purpose chickens. The results of association analyses showed that these two indel loci could significantly affect growth traits, such as body weight, and carcass traits. Tissue expression profiling at E12 showed that the expression of NUDT15 was significantly higher in skeletal muscle, and time-expression profiling of leg muscle showed that the expression of NUDT15 in myoblasts was significantly higher in the E10 and E12 proliferation stages than in other stages. Promoter activity analysis showed that pro-1673-I and pro-1673-D significantly inhibited promoter activity, and the promoter activity of pro-1673-D was significantly lower than that of pro-1673-I. In addition, when NUDT15 was overexpressed or underwent interference in chicken primary myoblasts (CPMs), NUDT15 could inhibit the proliferation of CPMs. CONCLUSION: The results suggest that the studied indels in the promoter region of NUDT15 may regulate the proliferation of CPMs by affecting NUDT15 expression, ultimately affecting the growth and carcass traits of chickens. These indel polymorphisms may be used together as molecular markers for improving economic traits in chickens.

Dual-molecular targeted NIR II probe with enhanced response for head and neck squamous cell carcinoma imaging.

In this research, a fluorescent probe of 7-(diethylamine) coumarin derivatives with multiple binding sites to detect biothiols in tumor cell with strong NIR II luminescencein vivowas synthesized. The biothiols include cysteine (Cys) and glutathione (GSH) in tumor cells, and the tumor-response luminescence was proved by the cell experiment. Importantly, the monolayer functional phospholipid (DSPE-PEG) coating and aggregation induced emission (AIE) dye of TPE modification made the probe have good stability and biocompatibility with little luminescence quenching in aqueous phase, which was proved byin vitroandin vivoexperiments. The final aqueous NIR II probe combined with bevacizumab (for VEGF recognition in the cancer cells) and Capmatinib (for Met protein recognition in the cancer cells) has stronger targeted imaging on head and neck squamous cell carcinoma (HNSCC) cancer with intravenous injection. This GSH/Cys detection in the tumor cell and strong dual-molecular NIR II bioimagingin vivomay provide new strategy to tumor detection.

An ensemble of cryo-EM structures of TRiC reveal its conformational landscape and subunit specificity.

TRiC/CCT assists the folding of ∼10% of cytosolic proteins through an ATP-driven conformational cycle and is essential in maintaining protein homeostasis. Here, we determined an ensemble of cryo-electron microscopy (cryo-EM) structures of yeast TRiC at various nucleotide concentrations, with 4 open-state maps resolved at near-atomic resolutions, and a closed-state map at atomic resolution, revealing an extra layer of an unforeseen N-terminal allosteric network. We found that, during TRiC ring closure, the CCT7 subunit moves first, responding to nucleotide binding; CCT4 is the last to bind ATP, serving as an ATP sensor; and CCT8 remains ADP-bound and is hardly involved in the ATPase-cycle in our experimental conditions; overall, yeast TRiC consumes nucleotide in a 2-ring positively coordinated manner. Our results depict a thorough picture of the TRiC conformational landscape and its allosteric transitions from the open to closed states in more structural detail and offer insights into TRiC subunit specificity in ATP consumption and ring closure, and potentially in substrate processing.

An Efficient Approach to Large-Scale Ab Initio Conformational Energy Profiles of Small Molecules.

Accurate conformational energetics of molecules are of great significance to understand maby chemical properties. They are also fundamental for high-quality parameterization of force fields. Traditionally, accurate conformational profiles are obtained with density functional theory (DFT) methods. However, obtaining a reliable energy profile can be time-consuming when the molecular sizes are relatively large or when there are many molecules of interest. Furthermore, incorporation of data-driven deep learning methods into force field development has great requirements for high-quality geometry and energy data. To this end, we compared several possible alternatives to the traditional DFT methods for conformational scans, including the semi-empirical method GFN2-xTB and the neural network potential ANI-2x. It was found that a sequential protocol of geometry optimization with the semi-empirical method and single-point energy calculation with high-level DFT methods can provide satisfactory conformational energy profiles hundreds of times faster in terms of optimization.

Targeted Luminescent Probes for Precise Upconversion/NIR II Luminescence Diagnosis of Lung Adenocarcinoma.

In this research, the antibody of the searched hub genes has been proposed to combine with a rare-earth composite for an upconversion luminescence (UCL) and downconversion (DCL) NIR-II imaging strategy for the diagnosis of lung adenocarcinoma (LUAD). Weighted gene co-expression network analysis is used to search the most relevant hub genes, and the required top genes that contribute to tumorigenesis (negative: CLEC3B, MFAP4, PECAM1, and FHL1; positive: CCNB2, CDCA5, HMMR, and TOP2A) are identified and validated by survival analysis and transcriptional and translational results. Meanwhile, fluorescence imaging probes (NaYF4:Yb,Er,Eu@NaYF4:Nd, denoted as NYF:Eu NPs) with multimodal optical imaging properties of downconversion and upconversion luminescence in the visible region and luminescence in the near infrared II region are designed with various uniform sizes and enhanced penetration and sensitivity. Finally, when the NYF:Eu NP probe is combined with antibodies of these chosen positive hub genes (such as, TOP2A and CCNB2), the in vitro and in vivo animal experiments (flow cytometry, cell counting kit-8 assay using A549 cells, and in vivo immunohistochemistry IHC microscopy images of LUAD from patient cases) indicate that the designed nanoprobes can be excellently used as a targeted optical probe for future accurate diagnosis and surgery navigation of LUAD in contrast with other cancer cells and normal cells. This strategy of antibodies combined with optical probes provides a dual-modal luminescence imaging method for precise medicine.

AIScaffold: A Web-Based Tool for Scaffold Diversification Using Deep Learning.

Molecular scaffolds are widely used in drug design. Many methods and tools have been developed to utilize the information in scaffolds. Scaffold diversification is frequently used by medicinal chemists in tasks such as lead compound optimization, but tools for scaffold diversification are still lacking. Here, we propose AIScaffold (https://iaidrug.stonewise.cn), a web-based tool for scaffold diversification using the deep generative model. This tool can perform large-scale (up to 500,000 molecules) diversification in several minutes and recommend the top 500 (top 0.1%) molecules. Features such as site-specific diversification are also supported. This tool can facilitate the scaffold diversification process for medicinal chemists, thereby accelerating drug design.

Lanthanide-Based Nanocomposites for Photothermal Therapy under Near-Infrared Laser: Relationship between Light and Heat, Biostability, and Reaction Temperature.

In this research, typical organic/inorganic photothermal therapy (PTT) agents were designed with a combination of upconversion luminescent (UCL) or near-infrared (NIR) II imaging rare-earth nanomaterials for photo-acoustic (PA)/UCL/NIR II imaging-guided PTT under NIR laser irradiation. The results show the following: (1) The PTT effect mainly comes from NIR absorption and partly from UCL light conversion. (2) Visible UCL emission is mainly quenched by NIR absorption of the coated PTT agent and partly quenched by visible absorption, indicating that excitation may play a more important role than in the UCL emission process. (3) The biostability of the composite might be decided by the synthesis reaction temperature. Among the five inorganic/organic nanocomposites, UCNP@MnO2 is the most suitable candidate for cancer diagnosis and treatment because of its stimuli-response ability to the micro-acid environment of tumor cells and highest biostability. The composites generate heat for PTT after entering the tumor cells, and then, the visible light emission gradually regains as MnO2 is reduced to colorless Mn2+ ions, thereby illuminating the cancer cells after the therapy.

DeepScaffold: A Comprehensive Tool for Scaffold-Based De Novo Drug Discovery Using Deep Learning.

The ultimate goal of drug design is to find novel compounds with desirable pharmacological properties. Designing molecules retaining particular scaffolds as their core structures is an efficient way to obtain potential drug candidates. We propose a scaffold-based molecular generative model for drug discovery, which performs molecule generation based on a wide spectrum of scaffold definitions, including Bemis-Murcko scaffolds, cyclic skeletons, and scaffolds with specifications on side-chain properties. The model can generalize the learned chemical rules of adding atoms and bonds to a given scaffold. The generated compounds were evaluated by molecular docking in DRD2 targets, and the results demonstrated that this approach can be effectively applied to solve several drug design problems, including the generation of compounds containing a given scaffold and de novo drug design of potential drug candidates with specific docking scores.

TF3P: Three-Dimensional Force Fields Fingerprint Learned by Deep Capsular Network.

Molecular fingerprints are the workhorse in ligand-based drug discovery. In recent years, an increasing number of research papers reported fascinating results on using deep neural networks to learn 2D molecular representations as fingerprints. It is anticipated that the integration of deep learning would also contribute to the prosperity of 3D fingerprints. Here, we unprecedentedly introduce deep learning into 3D small molecule fingerprints, presenting a new one we termed as the three-dimensional force fields fingerprint (TF3P). TF3P is learned by a deep capsular network whose training is in no need of labeled data sets for specific predictive tasks. TF3P can encode the 3D force fields information of molecules and demonstrates the stronger ability to capture 3D structural changes, to recognize molecules alike in 3D but not in 2D, and to identify similar targets inaccessible by other 2D or 3D fingerprints based on only ligands similarity. Furthermore, TF3P is compatible with both statistical models (e.g., similarity ensemble approach) and machine learning models. Altogether, we report TF3P as a new 3D small molecule fingerprint with a promising future in ligand-based drug discovery. All codes are written in Python and available at https://github.com/canisw/tf3p.

Searching for the Optimized Luminescent Lanthanide Phosphor Using Heuristic Algorithms.

In this research, four heuristic algorithms (HAs), including simulated annealing (SA), improved annealing with a harmony search algorithm (HSA), particle swarm optimization (PSO), and genetic algorithm (GA), were used to optimize the luminescent intensity of phosphor. Among the four HAs, the improved algorithm HSA got better phosphors than SA (without using the known coded concentration). The PSO algorithm got gradually better results with increased generation, and the GA could find the best local phosphors with shorter time. After further analysis of the 340 phosphors, we found that the final brightness has an optimized activator concentration (Tb: 0.21-0.26), and the results were further proved by another uniform host of NaGdF4:Ce,Tb nanoparticles. The HA was proper to find the optimal concentration of the activator of Tb. Furthermore, the optimal phosphor could be used as a bioimaging agent and improved QR code.

Graph-based generative models for de Novo drug design.

The discovery of new chemical entities is a crucial part of drug discovery, which requires the lead compounds to have desired properties to be pharmaceutically active. De novo drug design aims to generate and optimize novel ligands for macromolecular targets from scratch. The development of graph-based deep generative neural networks has provided a new method. In this review, we gave a brief introduction to graph representation and graph-based generative models for de novo drug design, summarized them as four architectures, and concluded each's characteristics. We also discussed generative models for scaffold- and fragment-based design and graph-based generative models' future directions.

Discovery of new GSK-3ß inhibitors through structure-based virtual screening.

Glycogen synthase kinase-3ß (GSK-3ß) is an attractive therapeutic target for human diseases, such as diabetes, cancer, neurodegenerative diseases, and inflammation. Thus, structure-based virtual screening was performed to identify novel scaffolds of GSK-3ß inhibitors, and we observed that conserved water molecules of GSK-3ß were suitable for virtual screening. We found 14 hits and D1 (IC50 of 0.71 µM) were identified. Furthermore, the neuroprotection activity of D1-D3 was validated on a cellular level. 2D similarity searches were used to find derivatives of high inhibitory compounds and an enriched structure-activity relationship suggested that these skeletons were worthy of study as potent GSK-3ß inhibitors.

Yeast 3',5'-bisphosphate nucleotidase: an affinity tag for protein purification.

Affinity chromatography is one of the most popular methods for protein purification. Each tag method has its advantages and disadvantages, and combination of different tags and developing of new tags had been proposed and performed. Yeast 3',5'-bisphosphate nucleotidase, also known as HAL2, hydrolyzes 3'-phosphoadenosine 5'-phosphate (PAP) with submicromolar Km, which indicated the tight interactions between HAL2 and PAP. In order to explore the feasibility of HAL2 as a protein purification affinity tag, HAL2 was further characterized with PAP as substrate. Results demonstrated that KmPAP and kcatPAP were ∼0.3µM and ∼11s(-)(1), respectively. Kd for PAP was 0.008µM in the presence of Ca(2+). pH was also found to affect interactions between HAL2 and PAP, with tightest binding (Kd∼8nM) at pH 7.5 and 8. The purification protocol was rationally designed based on nanomolar affinity to PAP agarose in the presence of Ca(2+), which could satisfy the metal requirement for PAP binding, prevent hydrolysis of immobilized PAP and could be chelated by ethylene glycol tetraacetic acid (EGTA) for elution. A series of expression vectors were further constructed and Escherichia coli adenosine 5'-phosphosulfate kinase (APSK) was prokaryotically expressed, purified and characterized. Ready to use expression vector with eight commonly used restriction enzyme recognition sites in multiple cloning site was subsequently constructed. By comparing with current popular tags, HAL2 was found to be an efficient and economical tag for prokaryotic protein expression and purification.

Incorporating Neural Networks into the AMOEBA Polarizable Force Field.

Neural network potentials (NNPs) offer significant promise to bridge the gap between the accuracy of quantum mechanics and the efficiency of molecular mechanics in molecular simulation. Most NNPs rely on the locality assumption that ensures the model's transferability and scalability and thus lack the treatment of long-range interactions, which are essential for molecular systems in the condensed phase. Here we present an integrated hybrid model, AMOEBA+NN, which combines the AMOEBA potential for the short- and long-range noncovalent atomic interactions and an NNP to capture the remaining local covalent contributions. The AMOEBA+NN model was trained on the conformational energy of the ANI-1x data set and tested on several external data sets ranging from small molecules to tetrapeptides. The hybrid model demonstrated substantial improvements over the baseline models in term of accuracy as the molecule size increased, suggesting its potential as a next-generation approach for chemically accurate molecular simulations.

Whole transcriptome profiling reveals a lncMDP1 that regulates myogenesis by adsorbing miR-301a-5p targeting CHAC1.

Myoblast proliferation and differentiation are essential for skeletal muscle development. In this study, we generated the expression profiles of mRNAs, long noncoding RNAs (lncRNAs), and microRNAs (miRNAs) in different developmental stages of chicken primary myoblasts (CPMs) using RNA sequencing (RNA-seq) technology. The dual luciferase reporter system was performed using chicken embryonic fibroblast cells (DF-1), and functional studies quantitative real-time polymerase chain reaction (qPCR), cell counting kit-8 (CCK-8), 5-Ethynyl-2'-deoxyuridine (EdU), flow cytometry cycle, RNA fluorescence in situ hybridization (RNA-FISH), immunofluorescence, and western blotting assay. Our research demonstrated that miR-301a-5p had a targeted binding ability to lncMDP1 and ChaC glutathione-specific gamma-glutamylcyclotransferase 1 (CHAC1). The results revealed that lncMDP1 regulated the proliferation and differentiation of myoblasts via regulating the miR-301a-5p/CHAC1 axis, and CHAC1 promotes muscle regeneration. This study fulfilled the molecular regulatory network of skeletal muscle development and providing an important theoretical reference for the future improvement of chicken meat performance and meat quality.

The long noncoding RNA lncMPD2 inhibits myogenesis by targeting the miR-34a-5p/THBS1 axis.

Long noncoding RNAs (lncRNAs) participate in regulating skeletal muscle development. However, little is known about their role in regulating chicken myogenesis. In this study, we identified a novel lncRNA, lncMPD2, through transcriptome sequencing of chicken myoblasts at different developmental stages. Functionally, gain- and loss-of-function experiments showed that lncMPD2 inhibited myoblast proliferation and differentiation. Mechanistically, lncMPD2 directly bound to miR-34a-5p, and miR-34a-5p promoted myoblasts proliferation and differentiation and inhibited the mRNA and protein expression of its target gene THBS1. THBS1 inhibited myoblast proliferation and differentiation in vitro and delayed muscle regeneration in vivo. Furthermore, rescue experiments showed that lncMPD2 counteracted the inhibitory effects of miR-34a-5p on THBS1 and myogenesis-related gene mRNA and protein expression. In conclusion, lncMPD2 regulates the miR-34a-5p/THBS1 axis to inhibit the proliferation and differentiation of myoblasts and skeletal muscle regeneration. This study provides more insight into the molecular regulatory network of skeletal muscle development, identifying novel potential biomarkers for improving chicken quality and increasing chicken yield. In addition, this study provides a potential goal for breeding strategies that minimize muscle damage in chickens.