INTRODUCTION:Phosphoinositide-3-kinase gamma (PI3Kγ) has emerged as a valuable therapeutic target for various diseases. However, there is a notable scarcity of inhibitors that have advanced to clinical studies, highlighting the urgent need for the development of novel PI3Kγ inhibitors. METHODS:A three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis was conducted to investigate the structure-activity relationships of PI3Kγ inhibitors. A scaffold growth strategy was employed to design novel compounds. Furthermore, a virtual screening workflow integrating drug-likeness filtering, 3D-QSAR predictions, and molecular docking was established. RESULTS:An optimal CoMFA model was developed with q² = 0.752, r² = 0.995, and r²pred = 0.736, revealing key structural features and interactions crucial for selective PI3Kγ inhibition. Using the N-phenyl isoquinolinone core of IPI-549 as a template, new compounds were generated via a reaction-based scaffold growth approach. Following drug-likeness evaluation, 3DQSAR predictions, and molecular docking, nine compounds demonstrated superior predicted activity compared to IPI-549. Three top-ranked hits were subsequently subjected to molecular dynamics simulations and binding free energy calculations, providing insights into the PI3Kγ/Hit binding mechanism and identifying critical residues governing selectivity, including MET804, TRP812, ILE831, VAL882, and MET953. DISCUSSION:Developing selective PI3Kγ inhibitors is challenging due to the high homology among kinase structures. IPI-549, the first PI3Kγ inhibitor to enter clinical trials, served as a suitable template for designing novel selective inhibitors. This study applied computer-aided drug design strategies to formulate promising new PI3Kγ inhibitors. CONCLUSION:The present workflow provides an effective and precise approach for identifying novel PI3Kγ inhibitors and offers valuable guidance for the rational design of selective PI3Kγ- targeted therapeutics.

The phosphatidylinositol 3-kinase (PI3K) pathway is a vital intracellular signaling cascade that plays a key role in cancer cell survival, angiogenesis, and metastasis. Consequently, PI3K has been a primary target for therapeutic inhibition in the treatment of various malignancies. Accumulating studies indicate that targeting multiple isoforms of PI3K may enhance antitumor activity. The advancement of pan-PI3K inhibitors for cancer treatment offers a promising research and development opportunity. This study introduces a machine learning-based virtual screening (VS) method that combines a Naïve Bayesian classification model employing molecular fingerprints and descriptors, alongside a pharmacophore model and consensus scoring-based molecular docking, to discover new pan-PI3K inhibitors. The VS method was validated for its strong predictive accuracy by successfully identifying the commercially available pan-PI3K inhibitor copanlisib. The hybrid VS strategy was applied to the SPECS database, leading to the discovery of several promising PI3K inhibitor compounds. The machine learning-based VS approach is expected to offer meaningful insights and a practical framework for discovering novel PI3K inhibitors.

PI3Kγ is a lipid kinase that is expressed primarily in leukocytes and plays a significant role in tumors, inflammation, and autoimmune diseases. Consequently, considerable attention has been given to the development of pharmacological inhibitors of PI3Kγ. Recently, machine learning-based virtual screening approaches have been increasingly applied in new drug discovery research, potentially providing innovative strategies for the development of PI3Kγ inhibitors. Thus, in this study, we developed a naïve Bayesian classification (NBC) model that integrates molecular descriptors, molecular fingerprints, molecular docking, and pharmacophore models for virtual screening of the PI3Kγ protein. The validation results indicated that the optimal model demonstrated significant potential for differentiating between active and inactive compounds, as well as a reliable ability to identify true PI3Kγ inhibitors with defined biological activity. Additionally, the optimal NBC model provided favorable and unfavorable fragments for PI3Kγ inhibitors, which will help guide the design and discovery of novel PI3Kγ inhibitors. Finally, the optimal NBC model was employed to perform virtual screening on the ChEMBL database, resulting in the identification of several compounds with high potential as PI3Kγ inhibitors. We anticipate that the developed machine learning-based virtual screening approach will offer valuable insights and guidance for the development of novel PI3Kγ inhibitors.

The distinct interactions of D/L-glucose with cells and biological systems have garnered significant attention. However, the impact of chiral glucose-modified nanomaterials on cancer diagnosis and treatment remains largely unexplored. Here, based on the host-guest interaction between D-/L-glucose-modified pillar[5]arene (D-/L-CP5) serving as the host molecule and Fe-porphyrin derivatives (FeTPPNHC) acting as the guest, an acid-responsive chiral supramolecular vesicle was constructed for transporting lactate oxidases (LOx) (denoted as LOx@D-/L-CP5⊃FeTPPNHC), aiming to enhance chirality-mediated tumor-specific cascade chemodynamic therapy (CDT) and photodynamic therapy (PDT) through the depletion of lactic acid (LA). Surprisingly, the L-glucose-mediated chiral vesicles exhibit remarkable chirality recognition and lactate depletion capabilities, which were higher than the D-glucose-mediated chiral vesicles. Once internalized by cancer cells, L-supramolecular nanomicelles can directly consume LA to generate a considerable amount of H2O2, which can then be converted into ˙OH and 1O2. In vitro and in vivo studies demonstrate the high tumor specificity and therapeutic efficacy of LOx@LCP5⊃FeTPPNHC. The findings suggest that chiral glucose-modified nanomaterials hold great potential in targeted cancer treatment, paving the way for the development of innovative cancer therapeutics based on their unique interactions with biological systems.

L-asparaginase (L-ASNase) can hydrolyze L-asparagine, a precursor to acrylamide, thereby reducing toxic acrylamide formation in fried foods. Currently, commercial L-ASNases are primarily produced by wild-type (WT) filamentous fungi; however, these enzymes often exhibit rapid activity loss during high-temperature processing due to limited thermal stability. In this study, we screened a thermostable L-ASNase gene from thermophile bacteria and expressed it in Aspergillus niger to reduce acrylamide content in French fries. Initially, four genes encoding thermostable L-ASNases were selected and integrated into the A. niger genome via non-homologous end joining. Among these, the L-ASNase gene tzi from Thermococcus zilligii was successfully expressed in A. niger, yielding an extracellular activity of 114 U center dot mg-1. The recombinant enzyme (An-Tzi) displayed the same optimal temperature and pH as its WT counterpart but exhibited superior catalytic efficiency, likely due to the efficient post-translational modifications in A. niger. To further enhance expression, the tzi gene was integrated into the amylase ( amyA ) locus of the A. niger genome using the CRISPR-Cas9 system, resulting in increased activity of 128 U center dot mg-1. Additionally, various lengths of the highly expressed glucoamylase (glaA) protein from A. niger AG11 were fused to the N-terminus of the Tzi. Notably, fusing the 500-amino-acid catalytic domain of glaA led to a substantial 3.3-fold increase in enzyme activity. Despite the metabolic stress induced by high-level expression of glaA, supplementing the culture medium with metal ions and sophorose resulted in an extracellular activity of 486.74 U center dot mg-1, the highest reported yield of L-ASNase in shake flasks. Finally, applying the An-Tzi to French fries achieved a 32 % greater reduction in acrylamide compared to the commercial enzyme. Overall, the recombinant A. niger strain expressing thermostable An-Tzi demonstrates significant potential for industrial applications targeting acrylamide reduction in fried and baked foods.

Accumulated research strongly indicates that Janus kinase 3 (JAK3) is intricately involved in the initiation and advancement of a diverse range of human diseases, underscoring JAK3 as a promising target for therapeutic intervention. However, JAK3 shows significant homology with other JAK family isoforms, posing substantial challenges in the development of JAK3 inhibitors. To address these limitations, one strategy is to design selective covalent JAK3 inhibitors. Therefore, this study introduces a virtual screening approach that combines common feature pharmacophore modeling, covalent docking, and consensus scoring to identify novel inhibitors for JAK3. First, common feature pharmacophore models were constructed based on a selection of representative covalent JAK3 inhibitors. The optimal qualitative pharmacophore model proved highly effective in distinguishing active and inactive compounds. Second, 14 crystal structures of the JAK3-covalent inhibitor complex were chosen for the covalent docking studies. Following validation of the screening performance, 5TTU was identified as the most suitable candidate for screening potential JAK3 inhibitors due to its higher predictive accuracy. Finally, a virtual screening protocol based on consensus scoring was conducted, integrating pharmacophore mapping and covalent docking. This approach resulted in the discovery of multiple compounds with notable potential as effective JAK3 inhibitors. We hope that the developed virtual screening strategy will provide valuable guidance in the discovery of novel covalent JAK3 inhibitors.

The phosphatidylinositol-3 kinase (PI3K) pathway is a crucial intracellular signaling pathway within living cells. The hyperactivation of PI3K signaling cascades is a common occurrence in human cancers, rendering PI3K a promising therapeutic target. Although several PI3K inhibitors are already available on the market, the adverse side effects of current therapies continue to highlight the necessity for the development of novel PI3K inhibitors. In this study, a virtual screening strategy employing na & iuml;ve Bayesian classification (NBC) models, based on multicomplex-based molecular docking and pharmacophore modeling, is developed. First, the docking accuracy and scoring reliability of four docking software are assessed, and Glide demonstrated higher predictability for PI3K inhibitors. Second, pharmacophore models are generated based on the current reported PI3K-inhibitor interactions, and five pharmacophore hypotheses displayed significant capability in discriminating active PI3K molecules from inactive ones. Subsequently, three NBC models are constructed based on molecular docking and/or pharmacophore models, and the validation results showed that the NBC model, combining multicomplex-based molecular docking and pharmacophore, significantly improved the hit rate of virtual screening against PI3K. Finally, the optimal NBC model is employed for virtual screening against the ChEMBL database, leading to the identification of multiple molecules with high potential as active PI3K inhibitors. Integrating multiple PI3K conformations, whether through molecular docking or pharmacophore, yields higher prediction accuracy. The na & iuml;ve Bayesian classification model has the potential to enhance the enrichment of virtual screening. A virtual screening strategy, utilizing multiple protein structures and integrating molecular docking and pharmacophore, is developed to identify novel PI3K inhibitors. image

Extensive research has accumulated which suggests that phosphatidylinositol 3-kinase delta (PI3Kδ) is closely related to the occurrence and development of various human diseases, making PI3Kδ a highly promising drug target. However, PI3Kδ exhibits high homology with other members of the PI3K family, which poses significant challenges to the development of PI3Kδ inhibitors. Therefore, in the present study, a hybrid virtual screening (VS) approach based on a ligand-based pharmacophore model and multicomplex-based molecular docking was developed to find novel PI3Kδ inhibitors. 13 crystal structures of the human PI3Kδ-inhibitor complex were collected to establish models. The inhibitors were extracted from the crystal structures to generate the common feature pharmacophore. The crystallographic protein structures were used to construct a naïve Bayesian classification model that integrates molecular docking based on multiple PI3Kδ conformations. Subsequently, three VS protocols involving sequential or parallel molecular docking and pharmacophore approaches were employed. External predictions demonstrated that the protocol combining molecular docking and pharmacophore resulted in a significant improvement in the enrichment of active PI3Kδ inhibitors. Finally, the optimal VS method was utilized for virtual screening against a large chemical database, and some potential hit compounds were identified. We hope that the developed VS strategy will provide valuable guidance for the discovery of novel PI3Kδ inhibitors.

Numerous research studies have demonstrated the significant correlation of phosphatidylinositol-3 kinase gamma (PI3K gamma) with the onset and progression of various human diseases, highlighting PI3K gamma as a promising therapeutic target. However, PI3K gamma demonstrates considerable similarity with other isoforms in the PI3K family, presenting significant challenges in the creation of PI3K gamma inhibitors. This study presents an ensemble-based virtual screening approach to discover novel inhibitors targeting PI3K gamma. Eganelisib (IPI-549) is the sole selective PI3K gamma inhibitor that has progressed to clinical trials, making it a significant model for the advancement of novel PI3K gamma inhibitors. Initially, common feature pharmacophore and receptor-ligand pharmacophore models were independently developed using IPI-549 and its potent derivatives, in conjunction with the crystal complex of PI3K gamma/IPI-549. Both qualitative pharmacophore models proved highly effective at distinguishing between active and inactive compounds. Then, four widely utilized docking programs were chosen for assessment, where the Glide_SP mode demonstrated superior predictive accuracy in sampling ligand conformations during binding, effectively distinguishing between PI3K gamma inhibitors and noninhibitors. Finally, a virtual screening protocol was conducted to screen the ChEMBL database, utilizing similarity search, consensus-based pharmacophore mapping, and sequential molecular docking. This process resulted in the identification of multiple molecules exhibiting notable promise as potent PI3K gamma inhibitors.

Sialyllactose is one of the most abundant sialylated oligosaccharides in human milk oligosaccharides (HMOs), which plays an important role in the healthy development of infants and young children. However, its efficient and cheap production technology is still lacking presently. This study developed a two-step process employing multiple-strains for the production of sialyllactose. In the first step, two engineered strains, E. coli JM109(DE3)/ pET28a-BT0453 and JM109(DE3)/pET28a-nanA, were constructed to synthesize the intermediate N-acetylneuraminic acid. When the ratio of the biomass of the two engineered strains was 1:1 and the reaction time was 32 hours, the maximum yield of N-acetylneuraminic acid was 20.4 g/L. In the second step, E. coli JM109(DE3)/ pET28a-neuA, JM109(DE3)/ pET28a-nst and Baker's yeast were added to the above fermentation broth to synthesize 3'-sialyllactose (3'-SL). Using optimal conditions including 200 mmol/L N-acetyl-glucosamine and lactose, 150 g/L Baker's yeast, 20 mmol/L Mg2+, the maximum yield of 3'-SL in the fermentation broth reached 55.04 g/L after 24 hours of fermentation and the conversion rate of the substrate N-acetyl-glucosamine was 43.47%. This research provides an alternative technical route for economical production of 3'-SL.

Since dysregulation of the phosphatidylinositol 3-kinase (PI3K) signaling pathway is associated with the pathogenesis of cancer, inflammation, and autoimmunity, PI3K has emerged as an attractive target for drug development. Although copanlisib is the first pan-PI3K inhibitor to be approved for clinical use, the precise mechanism by which it acts on PI3K has not been fully elucidated. To reveal the binding mechanisms and structure-activity relationship between PI3K and copanlisib, a comprehensive modeling approach that combines 3D-quantitative structure-activity relationship (3D-QSAR), pharmacophore model, and molecular dynamics (MD) simulation was utilized. Initially, the structure-activity relationship of copanlisib and its derivatives were explored by constructing a 3D-QSAR. Then, the key chemical characteristics were identified by building common feature pharmacophore models. Finally, MD simulations were performed to elucidate the important interactions between copanlisib and different PI3K subtypes, and highlight the key residues for tight-binding inhibitors. The present study uncovered the principal mechanism of copanlisib's action on PI3K at the theoretical level, and these findings might provide guidance for the rational design of pan-PI3K inhibitors.Communicated by Ramaswamy H. Sarma

The optical properties of food packaging frequently influence product appearance and consumer preference. As a novel food packaging strategy, starch-based coating, has demonstrated the ability to maintain quality and extend the shelf life of food, but its transparency has not been upgraded. The light-induced food oxidation caused by the enhancement of coating transparency also requires to be addressed. Herein, based on the screening results of five common commercial starches, phosphorylation and oxidation treatments were simultaneously administered on cassava starch to increase phosphorus content (0.287%) and reduce molecular weight (0.78 x 106 g/mol) and relative crystallinity (12.79%), resulting in a highly transparent dual modified starch-based coating. Ferulic acid was introduced to reduce UV transmission. The physicochemical properties of dual modified starch and its coating were comprehensively investigated using various methods. Compared with native starch-based coating, the as-obtained coating possessed relatively higher anti-wettability, mechanical strength, and thermal stability. More importantly, it exhibited high visible-light (87.06% at 600 nm wavelength) and extremely low UV trans-mittance (only 7.70% at 280 nm wavelength). The high transparency and photo-oxidation mitigation of the coating were also confirmed in actual fruits (e.g., strawberry and fresh-cut apples). This work provides a novel highly transparent coating that can preserve quality when used as a food packaging material.

Perishability caused by natural plant hormone ethylene has attracted great attention in the field of fruit and vegetable (F&V) preservation. Various physical and chemical methods have been applied to remove ethylene, but the eco-unfriendliness and toxicity of these methods limit their application. Herein, a novel starch-based ethylene scavenger was developed by introducing TiO2 nanoparticles into starch cryogel and applying ultrasonic treat-ment to further improve ethylene removal efficiency. As a porous carrier, the pore wall of cryogel provided dispersion space, which increased the area of TiO2 exposed to UV light, thereby endowing starch cryogel with ethylene removal capacity. The photocatalytic performance of scavenger reached the maximum ethylene degradation efficiency of 89.60 % when the TiO2 loading was 3 %. Ultrasonic treatment interrupted starch molecular chains and then promoted their rearrangement, increasing the material specific surface area from 54.6 m2/g to 225.15 m2/g and improving the ethylene degradation efficiency by 63.23 % compared with the non-sonicated cryogel. Furthermore, the scavenger exhibits good practicability for removing ethylene as a banana package. This work provides a new carbohydrate-based ethylene scavenger, utilizing as a non-food contact inner filler of F&V packaging in practical applications, which exhibits great potential in F&V preservation and broadens the application fields of starch.

Since dysregulation of the phosphatidylinositol 3-kinase gamma (PI3Kγ) signaling pathway is associated with the pathogenesis of cancer, inflammation, and autoimmunity, PI3Kγ has emerged as an attractive target for drug development. IPI-549 is the only selective PI3Kγ inhibitor that has advanced to clinical trials, thus, IPI-549 could serve as a promising template for designing novel PI3Kγ inhibitors. In this present study, a modeling strategy consisting of common feature pharmacophore modeling, receptor-ligand pharmacophore modeling, and molecular dynamics simulation was utilized to identify the key pharmacodynamic characteristic elements of the target compound and the key residue information of the PI3Kγ interaction with the inhibitors. Then, 10 molecules were designed based on the structure-activity relationships, and some of them exhibited satisfactory predicted binding affinities to PI3Kγ. Finally, a hierarchical multistage virtual screening method, involving the developed common feature and receptor-ligand pharmacophore model and molecular docking, was constructed for screening the potential PI3Kγ inhibitors. Overall, we hope these findings would provide some guidance for the development of novel PI3Kγ inhibitors.

大量研究表明磷脂酰肌醇3-激酶δ(PI3Kδ)与多种恶性肿瘤及免疫疾病的发生、发展密切相关,因此成为一个备受关注的药物靶点.伊德利塞(Idelalisib),PI3Kδ抑制剂,是首个被FDA批准上市的PI3K抑制剂,以此开启了PI3 Kδ选择性抑制剂开发的热潮,但是严重的毒副作用阻碍了该类化合物的使用.随后,度维利塞(Duvelisib,IPI-145)于2018年被批准上市,度维利塞是PI3 Kδ/γ选择性抑制剂,然而目前关于度维利塞的选择性PI3K抑制分子机制报道较少,且目前尚无度维利塞/PI3K复合物晶体结构报道.因此本文采用整合的计算机模拟策略来揭示度维利塞的选择性抑制机制:通过分子对接获得度维利塞与PI3K各亚型的合理结合构象;分子动力学模拟结合自由能计算揭示选择性产生的关键位点及热点氨基酸.目前,因与其他亚型之间高度的同源性与结构保守性,使得PI3 Kδ选择性抑制剂开发受到极大挑战,本文以上市药物度维利塞为研究主体,有望为新型PI3 Kδ选择性抑制剂的开发及合理药物设计提供一定的指导意义.

Sphingolipids (SLs) are vital for cells as forming membrane and transducing signals. The first step for de novo biosynthesis of SLs is catalyzed by the pyridoxal-5'-phosphate (PLP)-dependent enzyme serine palmitoyltransferase (SPT), which has been proven to be a promising drug target for treating various diseases. However, there are few SPT-specific inhibitors have been identified so far. Myriocin, a natural fungal product, is confirmed as the most potent inhibitor of SPT and has been widely used, but studies of its molecular mechanism are still underway. Besides, there is no intact co-crystal structure of SPT-binding myriocin until now. Aiming to uncover the interaction mechanism between SPT- and PLP-binding myriocin at the molecular level, a systematic computational strategy was performed in this present study. Firstly, covalent docking was implemented to preliminarily predict the binding pose SPT/PLP-myriocin aldimine and its structurally similar intermediate SPT/PLP-β-ketoacid aldimine. Secondly, two binding complexes were treated as initial structures to perform molecular dynamics simulations and binding free energy calculations. The calculated docking scores and predicted binding energies were consistent with the reported bioactivities. Finally, the binding mechanism of myriocin binding with SPT was meticulously described, and the key residues making favorable contributions were highlighted. Taken together, the current study could provide some important information and valuable guidance for further rational screening, design, and modification of potent specific SPT inhibitors.

In this study, an acidic hetero-exopolysaccharide, designated as BMPS, was isolated from the culture supernatant of bacteria Bacillus mucilaginosus SM-01 by ion-exchange and size-exclusion chromatography. The molecular weight of BMPS was measured to be 2.67×10(6)Da. To analyze the structure of the polysaccharide, the low-molecular weight fragment (BMPS-H) of BMPS was obtained under mild hydrolysis. BMPS-H was determined to be a liner neutral fraction with an average molecular weight of 1621Da. Monosaccharide analysis indicated that BMPS-H contained glucose and mannose in a molar ratio of 1.5:1. Based on methylation analysis and NMR spectroscopy data, the following structure of BMPS-H was established: In addition, MALDI-TOF-MS analysis showed the hydroxyl group on C-2 of 1,4-linked-glucosyl residues was partially acetylated.

The chain conformation and rheological behavior of an acidic hetero-exopolysaccharide from Bacillus mucilaginosus (BMPS) in aqueous solution were evaluated by using static and dynamic light scattering, viscometry and atomic force microscopy (AFM). BMPS displayed typical polyelectrolyte behavior in pure water and the intrinsic viscosity dramatically decreased with the addition of NaNO3. The Huggins constants k′ of 0.303 and the positive second virial coefficient A2 of BMPS in 0.1 M NaNO3 aqueous solution at 25 °C suggested that 0.1 M NaNO3 aqueous solution was a good solvent for BMPS. The relative stiffness parameter (B-value) was estimated to be 0.018, indicating the semi-flexibility of the BMPS backbone. The dependences among the intrinsic viscosity ([η]) and the radius of gyration (1/2) on molecular weight (Mw) in the range of Mw from 265 × 104 to 37.3 × 104 g mol−1, as well as the ratio of geometric to hydrodynamic radius revealed that BMPS exhibited an extended coil geometry in 0.1 M NaNO3 aqueous solution. The molecular size and shape of BMPS was further characterized by a wormlike cylinder model and observed directly by using AFM. The rheological results indicated that BMPS in pure water exhibited strong shear thinning property, and viscoelastic behavior was observed with solutions within 1.4–2.7% (w/v) consistent with the formation of entangled macromolecules in solution.

A water-soluble polysaccharide named DI was extracted from the fruiting bodies of gastroid mushroom Dictyophora indusiata with boiling water. The chemical and physical characteristics of DI were investigated by a combination of chemical and instrumental analysis methods. The immunomodulatory activities on RAW 264.7 macrophage of DI in vitro were also studied. The results showed that DI is a β-(1→3)-glucan with side branches of β-(1→6)-glucosyl units, and it has triple-helical structure. DI has no toxic effect on cells, but can promote macrophage multiplication. DI significantly affects the immune function by promoting the production of nitric oxide and cytokines, such as tumor necrosis factor-α, interleukin-1, -6, and -12, showing an obvious dose-effect relationship. This work extends the application scope of the polysaccharide from D. indusiata in the biomedical field.