Exploring PI3Kγ binding preference with Eganelisib, Duvelisib, and Idelalisib via energetic, pharmacophore and dissociation pathway analyses

Jia, Lei; Wang, Lingling; Jiang, Yingmin; Xu, Lei; Cai, Yanfei; Chen, Yun; Jin, Jian; Sun, Huiyong; Zhu, Jingyu

doi:10.1016/j.compbiomed.2022.105642

Cited by 9 publications

(3 citation statements)

References 60 publications

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“…Then, the Receptor-Ligand Pharmacophore Generation (RLPG) protocol in DS2017 was employed to directly generate pharmacophore models from the receptor-ligand interactions as revealed in the 3D structures. [61] The RLPG protocol considers six predefined pharmacophore feature types, including HBA, HBD, positive ionizable (PI), negative ionizable (NI), HY, and RA. [62,63] For each complex, the maximum number of pharmacophores was set to 10, and the minimum and maximum features of pharmacophores were set to three and six, respectively.…”

Section: Methodsmentioning

confidence: 99%

Integration of Multicomplex‐Based Pharmacophore Modeling and Molecular Docking in Machine Learning‐Based Virtual Screening: Toward the Discovery of Novel PI3K Inhibitors

Qiu,

Jia,

Yuan

et al. 2024

Advcd Theory and Sims

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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 naïve 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.

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Section: Methodsmentioning

confidence: 99%

Integration of Multicomplex‐Based Pharmacophore Modeling and Molecular Docking in Machine Learning‐Based Virtual Screening: Toward the Discovery of Novel PI3K Inhibitors

Qiu,

Jia,

Yuan

et al. 2024

Advcd Theory and Sims

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“…They reported that among all the drugs, Eganelisib binds most strongly to PI3Kg. 16 However, the mechanistic and molecular details of the action of these cancer drugs against the different COVID-19 targets are still unknown. Our hunch is that any of these drugs inhibiting SARS-CoV-2 could simultaneously treat cancer and COVID-19, i.e., act as multitarget drugs.…”

Section: Introductionmentioning

confidence: 99%

Can Duvelisib and Eganelisib work for both cancer and COVID-19? Molecular-level insights from MD simulations and enhanced samplings

Panda,

Karmakar,

Sen Gupta

et al. 2024

Phys. Chem. Chem. Phys.

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“…PI3Ks can be categorized into class I, II, and III according to their substrates [3]. Class I PI3Ks, which have attracted significant attention, are further divided into class IA (α, β, and δ) and IB (γ) based on their regulatory proteins and tissue specificity [4,5]. Class IA PI3Ks are triggered by a cascade of receptor tyrosine kinases (RTK), while class IB PI3K is activated by G protein-coupled receptors (GPCR) such as C5a, initiating downstream signaling pathways [6].…”

Section: Introductionmentioning

confidence: 99%

Evaluating the anti-inflammatory potential of JN-KI3: the therapeutic role of PI3Kγ- selective inhibitors in asthma treatment

Jia,

Ma,

Xiong

et al. 2024

Preprint

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Introduction 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. Objective and method 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. Results 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. Conclusion 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.

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Exploring PI3Kγ binding preference with Eganelisib, Duvelisib, and Idelalisib via energetic, pharmacophore and dissociation pathway analyses

Cited by 9 publications

References 60 publications

Integration of Multicomplex‐Based Pharmacophore Modeling and Molecular Docking in Machine Learning‐Based Virtual Screening: Toward the Discovery of Novel PI3K Inhibitors

Integration of Multicomplex‐Based Pharmacophore Modeling and Molecular Docking in Machine Learning‐Based Virtual Screening: Toward the Discovery of Novel PI3K Inhibitors

Can Duvelisib and Eganelisib work for both cancer and COVID-19? Molecular-level insights from MD simulations and enhanced samplings

Evaluating the anti-inflammatory potential of JN-KI3: the therapeutic role of PI3Kγ- selective inhibitors in asthma treatment

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