3D molecular generation models expand chemical space exploration in drug design.

Drug discovery is essential in human diseases but faces challenges because of the vast chemical space. Molecular generation models have become powerful tools to accelerate drug design by efficiently exploring chemical space. 3D molecular generation has gained popularity for explicitly incorporating spatial structural information to generate rational molecules.

Quaternized Molecular Brush-Grafted Injectable Microgel with Anti-Inflammatory and Drainage Properties for Efficient Therapy of Anal Fistula.

Anal fistula is a common disease with recurrent inflammation and accumulated exudate. Traditional treatments often fail to effectively eliminate inflammation and ensure adequate drainage, leading to prolonged healing time and a high recurrence rate. Herein, a new class of quaternized molecular brush-grafted injectable microgel (denoted as GAA@CNT-g-PVBTMA) is developed through thermal polymerization and mechanical fragmentation to promote the healing process of anal fistula.

Cryo-EM Structures Reveal the Unique Binding Modes of Metyltetraprole in Yeast and Porcine Cytochrome Complex Enabling Rational Design of Inhibitors.

Cytochrome (complex III) represents a significant target for the discovery of both drugs and fungicides. Metyltetraprole (MET) is commonly classified as a quinone site inhibitor (QI) that combats the G143A mutated isolate, which confers high resistance to strobilurin fungicides such as pyraclostrobin (PYR). The binding mode and antiresistance mechanism of MET remain unclear.

Starch-calcium inclusion complexes: Optimizing transparency, anti-fogging, and fluorescence in thermoplastic starch.

With the increasing demand for anti-fogging transparent material and environmental concern, developing sustainable intrinsically hydrophilic and anti-fogging thermoplastic material is important. In this work, thermoplastic starch (TPS) films with good anti-fogging and optical properties were prepared via coordinative interactions with calcium chloride (CaCl), zinc chloride (ZnCl) and magnesium chloride (MgCl). Among them, TPS with the incorporation of CaCl exhibited excellent anti-fogging and high optical transparency.

AquaticTox: A Web-Based Tool for Aquatic Toxicity Evaluation Based on Ensemble Learning to Facilitate the Screening of Green Chemicals.

The widespread use of chemical products inevitably brings many side effects as environmental pollutants. Toxicological assessment of compounds to aquatic life plays an important role in protecting the environment from their hazards. However, animal testing approaches for aquatic toxicity evaluation are time-consuming, expensive, and ethically limited, especially when there are a great number of compounds.

Boosting the Electrical Performance of PLA-Based Triboelectric Nanogenerators for Sustainable Power Sources and Self-Powered Sensing.

Triboelectric nanogenerators (TENGs) have emerged as a promising technology for harvesting mechanical energy from the ambient environment. However, developing tribopositive materials with strong piezoelectric effects and high electron-donating ability still remains a challenge. Herein, poly(ethylene glycol) monomethyl ether (mPEG) to soft poly(lactic acid) (PLA) is adopted, then PLA/mPEG nanofibers are fabricated under electrospinning and used as the tribopositive material for fabricating robust power density TENGs.

Glycosylation of Secondary Metabolites: A Multifunctional UDP-Glycosyltransferase, CsUGT74Y1, Promotes the Growth of Plants.

contains numerous glycosylated secondary metabolites that provide various benefits to plants and humans. However, the genes that catalyze the glycosylation of multitype metabolites in tea plants remain unclear. Here, 180 uridine diphosphate-dependent glycosyltransferases that may be involved in the biosynthesis of glycosylated secondary metabolites were identified from the National Center for Biotechnology Information public databases.

ACFIS 2.0: an improved web-server for fragment-based drug discovery via a dynamic screening strategy.

Drug discovery, which plays a vital role in maintaining human health, is a persistent challenge. Fragment-based drug discovery (FBDD) is one of the strategies for the discovery of novel candidate compounds. Computational tools in FBDD could help to identify potential drug leads in a cost-efficient and time-saving manner.

Structure-Based Design of 4-Hydroxyphenylpyruvate Dioxygenase Inhibitor as a Potential Herbicide for Cotton Fields.

4-Hydroxyphenylpyruvate dioxygenase (HPPD, EC 1.13.11.

Fragment-based drug discovery supports drugging 'undruggable' protein-protein interactions.

Protein-protein interactions (PPIs) have important roles in various cellular processes, but are commonly described as 'undruggable' therapeutic targets due to their large, flat, featureless interfaces. Fragment-based drug discovery (FBDD) has achieved great success in modulating PPIs, with more than ten compounds in clinical trials. Here, we highlight the progress of FBDD in modulating PPIs for therapeutic development.

Unveiling toxicity profile for food risk components: A manually curated toxicological databank of food-relevant chemicals.

Rigorous risk assessment of chemicals in food and feed is essential to address the growing worldwide concerns about food safety. High-quality toxicological data on food-relevant chemicals are fundamental for risk modeling and assessment in the food safety area. The organization and analysis of substantial toxicity information can positively support decision-making by providing insight into toxicity trends.

miR-155-1 as a positive factor for novel duck reovirus replication by regulating SOCS5-mediated interferons.

Diseases caused by novel duck reovirus (NDRV) have brought considerable economic losses to the poultry industry. MicroRNAs (miRNAs) have an impact on virus replication and antiviral immunity. However, the miRNA profile upon NDRV infection in duck embryo fibroblasts (DEFs) remains to be discovered.

Determination of Characteristic Volatile Component Fingerprint of Peucedanum Praeruptorum Dunn at Different Harvest Periods Based on HS-GC-IMS.

Background: Peucedanum praeruptorum Dunn (PPD) is a Chinese herbal medicine with medicinal value. Clinical studies have shown that PPD has protective effects against wind-heat, cough, asthma, cardiovascular diseases, and cancer. Therefore, cultivation of PPD is becoming more common.

Distribution- and Metabolism-Based Drug Discovery: A Potassium-Competitive Acid Blocker as a Proof of Concept.

Conventional methods of drug design require compromise in the form of side effects to achieve sufficient efficacy because targeting drugs to specific organs remains challenging. Thus, new strategies to design organ-specific drugs that induce little toxicity are needed. Based on characteristic tissue niche-mediated drug distribution (TNMDD) and patterns of drug metabolism into specific intermediates, we propose a strategy of distribution- and metabolism-based drug design (DMBDD); through a physicochemical property-driven distribution optimization cooperated with a well-designed metabolism pathway, SH-337, a candidate potassium-competitive acid blocker (P-CAB), was designed.

Functional analysis of the dihydroflavonol 4-reductase family of : exploiting key amino acids to reconstruct reduction activity.

Anthocyanins and proanthocyanidins (PAs) are important types of flavonoids, plant secondary metabolites with a wide range of industrial and pharmaceutical applications. DFR (dihydroflavonol 4-reductase) is a pivotal enzyme that plays an important role in the flavonoid pathway. Here, four genes were isolated from , and their overexpression was analyzed and Based on transcription and metabolic analyses, expression was closely consistent with catechins and PAs accumulation.

Exploring the kinase-inhibitor fragment interaction space facilitates the discovery of kinase inhibitor overcoming resistance by mutations.

Protein kinases play crucial roles in many cellular signaling processes, making them become important targets for drug discovery. But drug resistance mediated by mutation puts a barrier to the therapeutic effect of kinase inhibitors. Fragment-based drug discovery has been successfully applied to overcome such resistance.

Two UDP-Glycosyltransferases Catalyze the Biosynthesis of Bitter Flavonoid 7--Neohesperidoside through Sequential Glycosylation in Tea Plants.

Flavonoid glycosides are typical bitter and astringent tasting compounds that contribute to the taste of tea beverages. However, the genes that contribute to the biosynthesis of bitter compounds (, flavanone 7--neohesperidoside) in tea plants have yet to be identified. In this study, we identified 194 UDP-glycosyltransferases (UGTs) from the tea transcriptome database.

Ultrasound-activable piezoelectric membranes for accelerating wound healing.

Ultrasonic energy harvesting technologies have gained much attention for biomedical applications due to their several desirable features including low-energy attenuation and strong penetration capability. In this work, flexible piezoelectric poly(vinylidenefluoride--trifluoroethylene) (P(VDF-TrFE))/barium titanate (BaTiO, BT) membranes, capable of converting ultrasound energy to electric energy, were fabricated by an electrospinning process and their effects on the wound healing behaviors with/without ultrasonic stimulation were investigated. The piezoelectric membranes showed excellent electric outputs and can be used as a sustainable power source to quickly charge LEDs and capacitors.

PTMdyna: exploring the influence of post-translation modifications on protein conformational dynamics.

Protein post-translational modifications (PTM) play vital roles in cellular regulation, modulating functions by driving changes in protein structure and dynamics. Exploring comprehensively the influence of PTM on conformational dynamics can facilitate the understanding of the related biological function and molecular mechanism. Currently, a series of excellent computation tools have been designed to analyze the time-dependent structural properties of proteins.

Web-Based Quantitative Structure-Activity Relationship Resources Facilitate Effective Drug Discovery.

Traditional drug discovery effectively contributes to the treatment of many diseases but is limited by high costs and long cycles. Quantitative structure-activity relationship (QSAR) methods were introduced to evaluate the activity of compounds virtually, which saves the significant cost of determining the activities of the compounds experimentally. Over the past two decades, many web tools for QSAR modeling with various features have been developed to facilitate the usage of QSAR methods.

Fragment-based drug design facilitates selective kinase inhibitor discovery.

Protein kinases (PKs) are important drug targets, but kinases selectivity poses a challenge to protein kinase inhibitors (PKIs) design. Fragment-based drug discovery (FBDD) has achieved great success in the discovery of highly specific PKIs. It makes full use of kinase-fragment interaction in target kinase subpockets to obtain promising selectivity.

Precisely Engineered Photoreactive Titanium Nanoarray Coating to Mitigate Biofouling in Ultrafiltration.

To combat biofouling on membranes, diverse nanostructures of titanium dioxide (TiO) have emerged as effective antimicrobial coatings due to TiO's abilities to transport charge and photoinduce oxidation. However, TiO composite polymeric membranes synthesized using traditional methods of growing crystals have proven chemically unstable, with loss of coating and diminishing antimicrobial performance. Thus, new fabrication methods to enhance durability and efficacy should be considered.

Cloud 3D-QSAR: a web tool for the development of quantitative structure-activity relationship models in drug discovery.

Effective drug discovery contributes to the treatment of numerous diseases but is limited by high costs and long cycles. The Quantitative Structure-Activity Relationship (QSAR) method was introduced to evaluate the activity of a large number of compounds virtually, reducing the time and labor costs required for chemical synthesis and experimental determination. Hence, this method increases the efficiency of drug discovery.

Graph attention convolutional neural network model for chemical poisoning of honey bees' prediction.

The impact of pesticides on insect pollinators has caused worldwide concern. Both global bee decline and stopping the use of pesticides may have serious consequences for food security. Automated and accurate prediction of chemical poisoning of honey bees is a challenging task owing to a lack of understanding of chemical toxicity and introspection.