Discovery of novel selective PI3Kγ inhibitors through combining machine learning-based virtual screening with multiple protein structures and bio-evaluation

Enhancing PI3Kγ inhibitor discovery: a machine learning-based virtual screening approach integrating pharmacophores, docking, and molecular descriptors

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.

Identification of novel potential hypoxia-inducible factor-1α inhibitors through machine learning and computational simulations

Introduction

Hypoxia-inducible factor-1α (HIF-1α) has become a significant therapeutic target for breast cancer and other cancers by regulating the expression of downstream genes such as erythropoietin, thereby improving cell survival in hypoxic conditions.

Methods

We jointly applied a multistage screening system encompassing machine learning, molecular docking, and molecular dynamics simulations to conduct virtual screening of the "Traditional Chinese Medicine Monomer Library" for potential HIF-1α inhibitors. The virtual screening was conducted in three sequential stages, applying the following selection criteria sequentially: an activity prediction score greater than or equal to 0.8, a stronger binding affinity, and an MM-PBSA binding free energy lower than the reference compound.

Results and Discussion

We retrieved 361 compounds with HIF-1α inhibitory activity data from the ChEMBL database for the construction and evaluation of machine learning models. Among the six constructed models, the random forest model based on RDKit molecular descriptor with the optimal comprehensive performance was employed for virtual screening. Ultimately, four compounds were selected for binding mode analyses and 100 ns molecular dynamics simulations. The results showed that the compounds Arnidiol and Epifriedelanol exhibit the most stable interactions with the HIF-1α protein, which can serve as potential HIF-1α inhibitors for future investigations.

Identification of novel covalent JAK3 inhibitors through consensus scoring virtual screening: integration of common feature pharmacophore and covalent docking

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.

In silico discovery of a novel potential allosteric PI3Kα inhibitor incorporating 2-oxopropyl urea targeting head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is the most common head and neck cancer and highly aggressive and heterogeneous. Targeted therapy is still the main treatment method used in clinic due to lower side effect and personalized medication. In order to discover novel and effective drugs with low side effect against HNSCC, we analyzed the genes related to HNSCC, and found that PIK3CA was highly expressed in tumor tissues and often experienced mutations, leading to excessive activation of phosphoinositide 3-kinase alpha (PI3Kα), promoting the development of HNSCC. The allosteric PI3Kα inhibitor STX-478 inhibits the growth of tumor with hotspot mutations in PI3Kα and shows prominent efficacy on the treatment of human HNSCC xenografts without displaying the metabolic dysfunction observed in Alpelisib. These mutations open the allosteric site more readily, increasing the selectivity of STX-478 for mutant PI3Kα. STX-478 cleverly avoids the side effect of ATP competitive PI3Kα inhibitors. So, the structure of STX-478 was optimized based on the interaction mechanism between STX-478 and PI3Kα. Then, virtual screening, binding mode research, target verification, physical and chemical properties, pharmacokinetic properties and stabilities of ligand-PI3Kα complexes were evaluated by computer technologies (scaffold hopping, cdocker, SuperPred, SwissTarget prediction, Lipinski's rule of five, ADMET and MD simulation). Finally, J-53 (2-oxopropyl urea compound) with excellent properties was selected. J-53 not only formed H-bonds with key amino acids, but its unique -C(O)CH3 could also form H-bonds with ILE1019, making it more stably bound to PI3Kα and contributing to its activity. After the SciFinder verification, J-53 with novel structure had the value of further study. This study suggested that J-53 could be used as potential inhibitors of PI3Kα, and provides valuable information for the subsequent drug discovery of allosteric PI3Kα inhibitors.

Evaluating the Anti-inflammatory Potential of JN-KI3: The Therapeutic Role of PI3Kγ-Selective Inhibitors in Asthma Treatment

Asthma is a chronic airway inflammatory disease of the airways characterized by the involvement of numerous inflammatory cells and factors. Therefore, targeting airway inflammation is one of the crucial strategies for developing novel drugs in the treatment of asthma. Phosphoinositide 3-kinase gamma (PI3Kγ) has been demonstrated to have a significant impact on inflammation and immune responses, thus emerging as a promising therapeutic target for airway inflammatory disease, including asthma. There are few studies reporting on the therapeutic effects of PI3Kγ-selective inhibitors in asthma disease. In this study, we investigated the anti-inflammatory and therapeutic effects of PI3Kγ-selective inhibitor JN-KI3 for treating asthma by utilizing both in vivo and in vitro approaches, thereby proving that PI3Kγ-selective inhibitors could be valuable in the treatment of asthma. In RAW264.7 macrophages, JN-KI3 effectively suppressed C5a-induced Akt phosphorylation in a concentration-dependent manner, with no discernible toxicity observed in RAW264.7 cells. Furthermore, JN-KI3 can inhibit the PI3K/Akt signaling pathway in lipopolysaccharide-induced RAW264.7 cells, leading to the suppression of transcription and expression of the classical inflammatory cytokines in a concentration-dependent manner. Finally, an ovalbumin-induced murine asthma model was constructed to evaluate the initial therapeutic effect of JN-KI3 for treating asthma. Oral administration of JN-KI3 inhibited the infiltration of inflammatory cells and the expression of T-helper type 2 cytokines in bronchoalveolar lavage fluid, which was associated with the suppression of the PI3K signaling pathway. Lung tissue and immunohistochemical studies demonstrated that JN-KI3 inhibited the accumulation of inflammatory cells around the bronchus and blood vessels, as well as the secretion of mucus and excessive deposition of collagen around the airway. In addition, it reduced the infiltration of white blood cells into the lungs. In summary, JN-KI3 shows promise as a candidate for the treatment of asthma. Our study also suggests that the inhibitory effects of PI3Kγ on inflammation could offer an additional therapeutic strategy for pulmonary inflammatory diseases.

Efficacy of Oroxylin A in ameliorating renal fibrosis with emphasis on Sirt1 activation and TGF-β/Smad3 pathway modulation

Introduction

Renal fibrosis poses a serious threat to human health. At present, there are few types of traditional Chinese medicine used to treat this disease, and Oroxylin A (OA), as a natural product with multiple biological activities, is expected to be used for the treatment of renal fibrosis.

Methods

The tolerance of osteoarthritis and its impact on renal fibrosis were studied through ADMET, Lipinski's filter, establishment of a unilateral ureteral obstruction (UUO) model, and molecular docking.

Results

OA has good drug tolerance. Compared with the sham group, UUO mice that did not receive OA treatment showed severe tubular dilation and atrophy, extracellular matrix (ECM) deposition, and inflammatory cell infiltration in their kidneys, while OA-treated mice showed significant improvement in these symptoms. OA treatment remarkably restrained the accumulation of fibronectin and α-SMA. Moreover, OA treatment remarkably decreased the abnormal upregulation of inflammatory factors (IL-1β, IL-6, and TNF-α) in the obstructed kidney of UUO mice. Sirtuin1 (Sirt1) expression was markedly diminished in the kidneys of UUO mice and TGF-β1-induced HK-2 cells, whereas this reduction was largely reversed after OA treatment. The results support that OA exerts antifibrotic effects partly through the promotion of the activity of Sirt1. In in vitro results, OA treatment markedly inhibited the activation of Smad3 in UUO mice, thereby ameliorating renal fibrosis. OA could form hydrogen bonds with key the amino acid ASN226 in Sirt1, thereby activating Sirt1, which might also be the reason why OA could resist renal fibrosis.

Discussion

Our study indicated that OA might exert anti-renal fibrosis effects through the activation of Sirt1 and the suppression of the TGF-β/Smad3 signaling pathway.

Chinese medicine in the treatment of chronic hepatitis B: The mechanisms of signal pathway regulation

Chronic hepatitis B (CHB) is a chronic inflammatory disease of the liver caused by infection with the hepatitis B virus (HBV), which in later stages can lead to the development of end-stage liver diseases such as cirrhosis and hepatocellular carcinoma in severe cases, jeopardizing long-term quality of life, with a poor prognosis, and placing a serious financial burden on many families around the world. The pathogenesis of the disease is complex and closely related to the immune function of the body, which has not yet been fully elucidated. The development of chronic hepatitis B is closely related to the involvement of various signaling pathways, such as JAK/STAT, PI3K/Akt, Toll-like receptor, NF-κB and MAPK signaling pathways. A large number of studies have shown that Chinese medicine has obvious advantages in anti-hepatitis B virus, and it can effectively treat the disease by modulating relevant signaling pathways, strengthening immune resistance and defense, and inhibiting inflammatory responses, and certain research progress has been made, but there is still a lack of a comprehensive review on the modulation of relevant signaling pathways in Chinese medicine for the treatment of CHB. Therefore, this article systematically combed and elaborated the relevant literature on the modulation of relevant signaling pathways by traditional Chinese medicine in recent years, with a view to providing new ideas for the treatment of CHB and further drug development.

Machine learning models to identify lead compound and substitution optimization to have derived energetics and conformational stability through docking and MD simulations for sphingosine kinase 1

Sphingosine kinases (SphKs) are a group of important enzymes that circulate at low micromolar concentrations in mammals and have received considerable attention due to the roles they play in a broad array of biological processes including apoptosis, mutagenesis, lymphocyte migration, radio- and chemo-sensitization, and angiogenesis. In the present study, we constructed three classification models by four machine learning (ML) algorithms including naive bayes (NB), support vector machine (SVM), logistic regression, and random forest from 395 compounds. The generated ML models were validated by fivefold cross validation. Five different scaffold hit fragments resulted from SVM model-based virtual screening and docking results indicate that all the five fragments exhibit common hydrogen bond interaction a catalytic residue of SphK1. Further, molecular dynamics (MD) simulations and binding free energy calculation had been carried out with the identified five fragment leads and three cocrystal inhibitors. The best 15 fragments were selected. Molecular dynamics (MD) simulations showed that among these compounds, 7 compounds have favorable binding energy compared with cocrystal inhibitors. Hence, the study showed that the present lead fragments could act as potential inhibitors against therapeutic target of cancers and neurodegenerative disorders.

Molecular modeling strategy for detailing the primary mechanism of action of copanlisib to PI3K: combined ligand-based and target-based approach

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.

Discovery of novel ULK1 inhibitors through machine learning-guided virtual screening and biological evaluation

Aim: Build a virtual screening model for ULK1 inhibitors based on artificial intelligence.Materials & methods: Build machine learning and deep learning classification models and combine molecular docking and biological evaluation to screen ULK1 inhibitors from 13 million compounds. And molecular dynamics was used to explore the binding mechanism of active compounds.Results & conclusion: Possibly due to less available training data, machine learning models significantly outperform deep learning models. Among them, the Naive Bayes model has the best performance. Through virtual screening, we obtained three inhibitors with IC50 of μM level and they all bind well to ULK1. This study provides an efficient virtual screening model and three promising compounds for the study of ULK1 inhibitors.

Designing Small Molecule PI3Kγ Inhibitors: A Review of Structure-Based Methods and Computational Approaches

The PI3K/AKT/mTOR pathway plays critical roles in a wide array of biological processes. Phosphatidylinositol 3-kinase gamma (PI3Kγ), a class IB PI3K family member, represents a potential therapeutic opportunity for the treatment of cancer, inflammation, and autoimmunity. In this Perspective, we provide a comprehensive overview of the structure, biological function, and regulation of PI3Kγ. We also focus on the development of PI3Kγ inhibitors over the past decade and emphasize their binding modes, structure-activity relationships, and pharmacological activities. The application of computational technologies and artificial intelligence in the discovery of novel PI3Kγ inhibitors is also introduced. This review aims to provide a timely and updated overview on the strategies for targeting PI3Kγ.

Gingerenone A Attenuates Ulcerative Colitis via Targeting IL-17RA to Inhibit Inflammation and Restore Intestinal Barrier Function

Ulcerative colitis (UC) is a complicated and recurrent intestinal disease. Currently available drugs for UC treatment are scarce, therefore, novel therapeutic drugs for the UC are urgently to be developed. Gingerenone A (GA) is a phenolic compound known for its anti-inflammatory effect, but its effect on UC remains unknown. Here, it is shown that GA protects mice against UC, which is closely associated with inhibiting intestinal mucosal inflammation and enhancing intestinal barrier integrity in vivo and in vitro. Of note, RNA sequencing analysis demonstrates an evident correlation with IL-17 signaling pathway after GA treatment, and this effect is further corroborated by Western blot. Mechanistically, GA directly interacts with IL-17RA protein through pull-down, surface plasmon resonance analysis and molecular dynamics simulation. Importantly, lentivirus-mediated IL-17RA/Act1 knock-down or GA co-treatment with brodalumab/ixekizumab significantly impairs the protective effects of GA against DSS-induced inflammation and barrier dysfunction, suggesting a critical role of IL-17RA signaling for GA-mediated protection against UC. Overall, these results indicate that GA is an effective agent against UC mainly through the direct binding of IL-17RA to inhibit inflammatory signaling activation.

Isovaleryl Sucrose Esters from Atractylodes japonica and Their Cytotoxic Activity

Cancer represents one of the most significant health challenges currently facing humanity, and plant-derived antitumour drugs represent a prominent class of anticancer medications in clinical practice. Isovaleryl sucrose esters, which are natural constituents, have been identified as having potential antitumour effects. However, the mechanism of action remains unclear. In this study, 12 isovaleryl sucrose ester components, including five new (1-5) and seven known compounds (6-12), were isolated from the roots of Atractylodes japonica. The structures of the compounds were elucidated using 1D and 2D-NMR spectroscopy, complemented by HR-ESI-MS mass spectrometry. The cytotoxic activities of all the compounds against human colon cancer cells (HCT-116) and human lung adenocarcinoma cells (A549) were also evaluated using the CCK8 assay. The results demonstrated that compounds 2, 4, and 6 were moderately inhibitory to HCT-116 cells, with IC50 values of 7.49 ± 0.48, 9.03 ± 0.21, and 13.49 ± 1.45 μM, respectively. Compounds 1 and 6 were moderately inhibitory to A549, with IC50 values of 8.36 ± 0.77 and 7.10 ± 0.52 μM, respectively. Molecular docking revealed that compounds 1-9 exhibited a stronger affinity for FGFR3 and BRAF, with binding energies below -7 kcal/mol. Compound 2 exhibited the lowest binding energy of -10.63 kcal/mol to FGFR3. We screened the compounds with lower binding energies, and the protein-ligand complexes already obtained after molecular docking were subjected to exhaustive molecular dynamics simulation experiments, which simulated the dynamic behaviour of the molecules in close proximity to the actual biological environment, thus providing a deeper understanding of their functions and interaction mechanisms. The present study provides a reference for the development and use of iso-valeryl sucrose esters in the antitumour field.

Optimization of virtual screening against phosphoinositide 3-kinase delta: Integration of common feature pharmacophore and multicomplex-based molecular docking

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.

Evaluation of the anti-inflammatory effects of PI3Kδ/γ inhibitors for treating acute lung injury

Phosphatidylinositol 3-kinase delta (PI3Kδ) and gamma (PI3Kγ) are predominantly located in immune and hematopoietic cells. It is well-established that PI3Kδ/γ plays important roles in the immune system and participates in inflammation; hence, it could be a potential target for anti-inflammatory therapy. Currently, several PI3K inhibitors are used clinically to treat cancers with aberrant PI3K signaling; however, their role in treating acute respiratory inflammatory diseases has rarely been explored. Herein, we investigated the potential anti-inflammatory activities of several pharmacological PI3K inhibitors, including marketed drugs idelalisib (PI3Kδ), duvelisib (PI3Kδ/γ), and copanlisib (pan-PI3K with preferential α/δ) and the clinical drug eganelisib (PI3Kγ), for treating acute lung injury (ALI). In the lipopolysaccharide-induced RAW264.7 macrophage inflammatory model, the four inhibitors significantly suppressed proinflammatory cytokine expression by inhibiting the PI3K signaling pathway. Oral administration of PI3K inhibitors markedly improved lung injury in a murine model of ALI. PI3K pathway inhibition decreased inflammatory cell infiltration and totalprotein levels, as well as reduced the expression of associated lung inflammatory factors. Collectively, all four representative PI3K inhibitors exerted prominent anti-inflammatory properties, indicating that PI3K δ and/or γ inhibition could be ideal targets to treat respiratory inflammatory diseases by reducing the inflammatory response. The findings of the current study provide a new basis for utilizing PI3K inhibitors to treat acute respiratory inflammatory diseases.

LRFN5 and OLFM4 as novel potential biomarkers for major depressive disorder: a pilot study

Evidences have shown that both LRFN5 and OLFM4 can regulate neural development and synaptic function. Recent genome-wide association studies on major depressive disorder (MDD) have implicated LRFN5 and OLFM4, but their expressions and roles in MDD are still completely unclear. Here, we examined serum concentrations of LRFN5 and OLFM4 in 99 drug-naive MDD patients, 90 drug-treatment MDD patients, and 81 healthy controls (HCs) using ELISA methods. The results showed that both LRFN5 and OLFM4 levels were considerably higher in MDD patients compared to HCs, and were significantly lower in drug-treatment MDD patients than in drug-naive MDD patients. However, there were no significant differences between MDD patients who received a single antidepressant and a combination of antidepressants. Pearson correlation analysis showed that they were associated with the clinical data, including Hamilton Depression Scale score, age, duration of illness, fasting blood glucose, serum lipids, and hepatic, renal, or thyroid function. Moreover, these two molecules both yielded fairly excellent diagnostic performance in diagnosing MDD. In addition, a combination of LRFN5 and OLFM4 demonstrated a better diagnostic effectiveness, with an area under curve of 0.974 in the training set and 0.975 in the testing set. Taken together, our data suggest that LRFN5 and OLFM4 may be implicated in the pathophysiology of MDD and the combination of LRFN5 and OLFM4 may offer a diagnostic biomarker panel for MDD.

Developing new PI3Kγ inhibitors by combining pharmacophore modeling, molecular dynamic simulation, molecular docking, fragment-based drug design, and virtual screening

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.

Binding and selectivity studies of phosphatidylinositol 3-kinase (PI3K) inhibitors

Overexpression of the Phosphatidylinositol 3-kinase (PI3K) proteins have been observed in cancer cells. Targeting the phosphatidylinositol 3-kinase (PI3K) signaling transduction pathway by inhibition of the PI3K substrate recognition sites has been proved to be an effective approach to block cancer progression. Many PI3K inhibitors have been developed. Seven drugs have been approved by the US FDA with a mechanism of targeting the phosphatidylinositol 3-kinase/protein kinase-B/mammalian target of rapamycin (PI3K/AKT/mTOR) signaling pathway. In this study, we used docking tools to investigate selective binding of ligands toward four different subtypes of PI3Ks (PI3Kα, PI3Kβ, PI3Kγ and PI3Kδ). The affinity predicted from both the Glide dock and the Movable-Type (MT)-based free energy calculations agreed well with the experimental data. The validation of our predicted methods with a large dataset of 147 ligands showed very small mean errors. We identified residues that may dictate the subtype-specific binding. Particularly, residues Asp964, Ser806, Lys890 and Thr886 of PI3Kγ might be utilized for PI3Kγ-selective inhibitor design. Residues Val828, Trp760, Glu826 and Tyr813 may be important for PI3Kδ-selective inhibitor binding.

Investigation into the anti-airway inflammatory role of the PI3Kγ inhibitor JN-PK1: An in vitro and in vivo study

Phosphatidylinositol 3-kinase gamma (PI3Kγ) has been proven to be a potential target for the treatment of inflammatory diseases of the airway; however, there are few reports of selective PI3Kγ inhibitors being used in the field of airway inflammation thus far. Herein, a study employing in vitro and in vivo methodologies was carried out to assess the anti-airway inflammatory effects of JN-PK1, a selective PI3Kγ inhibitor. In RAW264.7 macrophages, JN-PK1 inhibited PI3Kγ-dependent, cellular C5a-induced AKT Ser473 phosphorylation in a concentration- and time-dependent manner and had no significant effect on cell viability.Furthermore, JN-PK1 significantly suppressed LPS-induced, proinflammatory cytokine expression and nitric oxide production through inhibition of the PI3K signaling pathway in RAW264.7 cells. Then, a murine asthma model was established to evaluate the anti-airway inflammation effect of JN-PK1. BALB/c mice were sensitized and challenged with ovalbumin (OVA) to develop an inflammatory response, fibrosis formation, and other airway changes similar to the symptomatology of asthma in humans. Oral administration of JN-PK1 remarkably attenuated OVA-induced asthma in association with the inhibition of the PI3K signaling pathway. That is to say, the oral administration significantly inhibited increases in inflammatory cell counts and reduced T-helper type 2 cytokine production in bronchoalveolar lavage fluid. Pulmonary histological studies showed that oral administration of JN-PK1 not only reduced the infiltration of inflammatory cells but also retarded airway inflammation and fibration. Taken together, JN-PK1 could be developed as a promising candidate for inflammation therapy, and our findings support some potential for therapeutic inhibition of PI3Kγ to treat inflammatory airway diseases.

Target-Based Small Molecule Drug Discovery for Colorectal Cancer: A Review of Molecular Pathways and In Silico Studies

Colorectal cancer is one of the most prevalent cancer types. Although there have been breakthroughs in its treatments, a better understanding of the molecular mechanisms and genetic involvement in colorectal cancer will have a substantial role in producing novel and targeted treatments with better safety profiles. In this review, the main molecular pathways and driver genes that are responsible for initiating and propagating the cascade of signaling molecules reaching carcinoma and the aggressive metastatic stages of colorectal cancer were presented. Protein kinases involved in colorectal cancer, as much as other cancers, have seen much focus and committed efforts due to their crucial role in subsidizing, inhibiting, or changing the disease course. Moreover, notable improvements in colorectal cancer treatments with in silico studies and the enhanced selectivity on specific macromolecular targets were discussed. Besides, the selective multi-target agents have been made easier by employing in silico methods in molecular de novo synthesis or target identification and drug repurposing.