Rational Design of Novel Phosphoinositide 3-Kinase Gamma (PI3Kγ) Selective Inhibitors: A Computational Investigation Integrating 3D-QSAR, Molecular Docking and Molecular Dynamics Simulation

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.

Drug conjugates for the treatment of lung cancer: from drug discovery to clinical practice

A drug conjugate consists of a cytotoxic drug bound via a linker to a targeted ligand, allowing the targeted delivery of the drug to one or more tumor sites. This approach simultaneously reduces drug toxicity and increases efficacy, with a powerful combination of efficient killing and precise targeting. Antibody‒drug conjugates (ADCs) are the best-known type of drug conjugate, combining the specificity of antibodies with the cytotoxicity of chemotherapeutic drugs to reduce adverse reactions by preferentially targeting the payload to the tumor. The structure of ADCs has also provided inspiration for the development of additional drug conjugates. In recent years, drug conjugates such as ADCs, peptide‒drug conjugates (PDCs) and radionuclide drug conjugates (RDCs) have been approved by the Food and Drug Administration (FDA). The scope and application of drug conjugates have been expanding, including combination therapy and precise drug delivery, and a variety of new conjugation technology concepts have emerged. Additionally, new conjugation technology-based drugs have been developed in industry. In addition to chemotherapy, targeted therapy and immunotherapy, drug conjugate therapy has undergone continuous development and made significant progress in treating lung cancer in recent years, offering a promising strategy for the treatment of this disease. In this review, we discuss recent advances in the use of drug conjugates for lung cancer treatment, including structure-based drug design, mechanisms of action, clinical trials, and side effects. Furthermore, challenges, potential approaches and future prospects are presented.

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.

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.

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

Introduction

Phosphoinositide 3-kinase gamma (PI3Kγ) has been regarded as a promising drug target for the treatment of various diseases, and the diverse physiological roles of class I PI3K isoforms (α, β, δ, and γ) highlight the importance of isoform selectivity in the development of PI3Kγ inhibitors. However, the high structural conservation among the PI3K family makes it a big challenge to develop selective PI3Kγ inhibitors.

Objectives

A novel machine learning-based virtual screening with multiple PI3Kγ protein structures was developed to discover novel PI3Kγ inhibitors.

Methods

A large chemical database was screened using the virtual screening model, the top-ranked compounds were then subjected to a series of bio-evaluations, which led to the discovery of JN-KI3. The selective inhibition mechanism of JN-KI3 against PI3Kγ was uncovered by a theoretical study.

Results

49 hits were identified through virtual screening, and the cell-free enzymatic studies found that JN-KI3 selectively inhibited PI3Kγ at a concentration as low as 3,873 nM but had no inhibitory effect on Class IA PI3Ks, leading to the selective cytotoxicity on hematologic cancer cells. Meanwhile, JN-KI3 potently blocked the PI3K signaling, finally led to distinct apoptosis of hematologic cell lines at a low concentration. Lastly, the key residues of PI3Kγ and the structural characteristics of JN-KI3, which both would influence γ isoform-selective inhibition, were highlighted by systematic theoretical studies.

Conclusion

The developed virtual screening model strongly manifests the robustness to find novel PI3Kγ inhibitors. JN-KI3 displays a specific cytotoxicity on hematologic tumor cells, and significantly promotes apoptosis associated with the inhibition of the PI3K signaling, which depicts PI3Kγ as a potential target for the hematologic tumor therapy. The theoretical results reveal that those key residues interacting with JN-KI3 are less common compared to most of the reported PI3Kγ inhibitors, indicating that JN-KI3 has novel structural characteristics as a selective PIK3γ inhibitor.

Theoretical study of myriocin-binding mechanism targeting serine palmitoyltransferase

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.

Tailored Parameterization of the LIE Method for Calculating the Binding Free Energy of Vps34-Inhibitor Complexes

Vps34 is the only isoform of the PI3K family in fungi, making this protein an attractive target to develop new treatments against pathogenic fungi. The high structural similarity between the active sites of the human and fungal Vps34 makes repurposing of human Vps34 inhibitors an appealing strategy. Nonetheless, while some of the cross-reactive inhibitors might have the potential to treat fungal infections, a safer approach to prevent undesired side effects would be to identify molecules that specifically inhibit the fungal Vps34. This study presents the parameterization of four LIE models for estimating the binding free energy of Vps34-inhibitor complexes. Two models are parameterized using a multiparametric linear regression leaving one or more free parameters, while the other two are based on the LIE-D model. All of the models show good predictive capacity (R ² > 0.7, r > 0.85) and a low mean absolute error (MAE < 0.71 kcal/mol). The current study highlights the advantages of LIE-D-derived models when predicting the weight of the different contributions to the binding free energy. It is expected that this study will provide researchers with a valuable tool to identify new Vps34 inhibitors for relevant applications such as cancer treatment and the development of new antimicrobial agents.

Discovery of potential inhibitors targeting the kinase domain of polynucleotide kinase/phosphatase (PNKP): Homology modeling, virtual screening based on multiple conformations, and molecular dynamics simulation

In recent years, the level of interest has been increased in developing the DNA-repair inhibitors, to enhance the cytotoxic effects in the treatment of cancers. Polynucleotide kinase/phosphatase (PNKP) is a critical human DNA repair enzyme that repairs DNA strand breaks by catalyzing the restoration of 5'-phosphate and 3'-hydroxyl termini that are required for subsequent processing by DNA ligases and polymerases. PNKP is the only protein that repairs the 3'-hydroxyl group and 5'-phosphate group, which depicts PNKP as a potential therapeutic target. Besides, PNKP is the only DNA-repair enzyme that contains the 5'-kinase activity, therefore, targeting this kinase domain would motivate the development of novel PNKP-specific inhibitors. However, there are neither crystal structures of human PNKP nor the kinase inhibitors reported so far. Thus, in this present study, a sequential molecular docking-based virtual screening with multiple PNKP conformations integrating homology modeling, molecular dynamics simulation, and binding free energy calculation was developed to discover novel PNKP kinase inhibitors, and the top-scored molecule was finally submitted to molecular dynamics simulation to reveal the binding mechanism between the inhibitor and PNKP. Taken together, the current study could provide some guidance for the molecular docking based-virtual screening of novel PNKP kinase inhibitors.

Molecular Dynamics Simulations in Designing DARPins as Phosphorylation-Specific Protein Binders of ERK2

Extracellular signal-regulated kinases 1 and 2 (ERK1/2) play key roles in promoting cell survival and proliferation through the phosphorylation of various substrates. Remarkable antitumour activity is found in many inhibitors that act upstream of the ERK pathway. However, drug-resistant tumour cells invariably emerge after their use due to the reactivation of ERK1/2 signalling. ERK1/2 inhibitors have shown clinical efficacy as a therapeutic strategy for the treatment of tumours with mitogen-activated protein kinase (MAPK) upstream target mutations. These inhibitors may be used as a possible strategy to overcome acquired resistance to MAPK inhibitors. Here, we report a class of repeat proteins-designed ankyrin repeat protein (DARPin) macromolecules targeting ERK2 as inhibitors. The structural basis of ERK2-DARPin interactions based on molecular dynamics (MD) simulations was studied. The information was then used to predict stabilizing mutations employing a web-based algorithm, MAESTRO. To evaluate whether these design strategies were successfully deployed, we performed all-atom, explicit-solvent molecular dynamics (MD) simulations. Two mutations, Ala → Asp and Ser → Leu, were found to perform better than the original sequence (DARPin E40) based on the associated energy and key residues involved in protein-protein interaction. MD simulations and analysis of the data obtained on these mutations supported our predictions.

A multi-conformational virtual screening approach based on machine learning targeting PI3Kγ

Nowadays, more and more attention has been attracted to develop selective PI3Kγ inhibitors, but the unique structural features of PI3Kγ protein make it a very big challenge. In the present study, a virtual screening strategy based on machine learning with multiple PI3Kγ protein structures was developed to screen novel PI3Kγ inhibitors. First, six mainstream docking programs were chosen to evaluate their scoring power and screening power; CDOCKER and Glide show satisfactory reliability and accuracy against the PI3Kγ system. Next, virtual screening integrating multiple PI3Kγ protein structures was demonstrated to significantly improve the screening enrichment rate comparing to that with an individual protein structure. Last, a multi-conformational Naïve Bayesian Classification model with the optimal docking programs was constructed, and it performed a true capability in the screening of PI3Kγ inhibitors. Taken together, the current study could provide some guidance for the docking-based virtual screening to discover novel PI3Kγ inhibitors.

A Multi-target Drug Designing for BTK, MMP9, Proteasome and TAK1 for the Clinical Treatment of Mantle Cell Lymphoma

BACKGROUND

Mantle cell lymphoma (MCL) is a type of non-Hodgkin lymphoma characterized by the mutation and overexpression of the cyclin D1 protein by the reciprocal chromosomal translocation t(11;14)(q13:q32).

AIM

The present study aims to identify potential inhibition of MMP9, Proteasome, BTK, and TAK1 and determine the most suitable and effective protein target for the MCL.

METHODOLOGY

Nine known inhibitors for MMP9, 24 for proteasome, 15 for BTK and 14 for TAK1 were screened. SB-3CT (PubChem ID: 9883002), oprozomib (PubChem ID: 25067547), zanubrutinib (PubChem ID: 135565884) and TAK1 inhibitor (PubChem ID: 66760355) were recognized as drugs with high binding capacity with their respective protein receptors. 41, 72, 102 and 3 virtual screened compounds were obtained after the similarity search with compound (PubChem ID:102173753), PubChem compound SCHEMBL15569297 (PubChem ID:72374403), PubChem compound SCHEMBL17075298 (PubChem ID:136970120) and compound CID: 71814473 with best virtual screened compounds.

RESULT

MMP9 inhibitors show commendable affinity and good interaction profile of compound holding PubChem ID:102173753 over the most effective established inhibitor SB-3CT. The pharmacophore study of the best virtual screened compound reveals its high efficacy based on various interactions. The virtual screened compound's better affinity with the target MMP9 protein was deduced using toxicity and integration profile studies.

CONCLUSION

Based on the ADMET profile, the compound (PubChem ID: 102173753) could be a potent drug for MCL treatment. Similar to the established SB-3CT, the compound was non-toxic with LD50 values for both the compounds lying in the same range.

Phosphatidylinositol 3-kinase (PI3K) inhibitors: a recent update on inhibitor design and clinical trials (2016-2020)

Introduction: The phosphatidylinositol 3-kinase/protein kinase-B/mammalian target of rapamycin (PI3K/AKT/mTOR) signaling pathway plays a central role in regulating cell growth and proliferation and thus has been considered as effective anticancer drug targets. Many PI3K inhibitors have been developed and progressed to various stages of clinical trials, and some have been approved as anticancer treatment. In this review, we discuss the drug design and clinical development of PI3K inhibitors over the past 4 years. We review the selectivity and potency of 47 PI3K inhibitors. Structural determinants for increasing selectivity toward PI3K subtype-selectivity or mutant selectivity are discussed. Future research direction and current clinical development in combination therapy of inhibitors involved in PI3Ks are also discussed.Area covered: This review covers clinical trial reports and patent literature on PI3K inhibitors and their selectivity published between 2016 and 2020.Expert opinion: To PI3Kα mutants (E542K, E545K, and H1047R), it is highly desirable to design and develop mutant-specific PI3K inhibitors. It is also necessary to develop subtype-selective PI3Kα inhibitors to minimize toxicity. To reduce drug resistance and to improve efficacy, future studies should include combination therapy of PI3K inhibitors with existing anticancer drugs from different pathways.

Integrated molecular modeling techniques to reveal selective mechanisms of inhibitors to PI3Kδ with marketed Idelalisib

Phosphatidylinositol-3-kinase (PI3K) is important for cell proliferation, differentiation, and apoptosis, and the diverse physiological roles of different PI3K isoforms have highlighted the significance of the development of PI3Kδ inhibitors. A large number of PI3Kδ inhibitors have been reported after the FDA approval of Idelalisib, but the clinical use of Idelalisib was limited because of its serious side effects. Therefore, great efforts have been made on the development of PI3Kδ inhibitors with higher selectivity and lower toxicity, but there is no new PI3Kδ inhibitor coming into the market so far. Even so, as the first listed PI3K inhibitor, Idelalisib could be used as an effective tool to investigate the selective inhibition mechanism of PI3Kδ. Thus, in this study, a modeling strategy integrated 3D-QSAR, pharmacophore model, and molecular dynamics simulation was employed to reveal the key chemical characteristics of Idelalisib analogs and the binding pattern between the inhibitors and PI3Kδ. First, the CoMFA model with high statistical significance was built to reveal the general structure-activity relationships. And then, a reliable pharmacophore model with a robust discrimination capability was constructed to expound the main chemical characteristics of the PI3Kδ inhibitors. Finally, molecular dynamics simulation was conducted to explore the binding modes and some key residues refer to δ-selective binding were highlighted with binding-free energy calculation. In summary, these models and results would provide some effective help for the discovery or the rational design of novel PI3Kδ inhibitors.

Targeting phosphatidylinositol 3-kinase gamma (PI3Kγ): Discovery and development of its selective inhibitors

Phosphatidylinositol 3-kinase gamma (PI3Kγ) has been regarded as a promising drug target for the treatment of advanced solid tumors, leukemia, lymphoma, and inflammatory and autoimmune diseases. However, the high level of structural conservation among the members of the PI3K family and the diverse physiological roles of Class I PI3K isoforms (α, β, δ, and γ) highlight the importance of isoform selectivity in the development of PI3Kγ inhibitors. In this review, we provide an overview of the structural features of PI3Kγ that influence γ-isoform selectivity and discuss the structure-selectivity-activity relationship of existing clinical PI3Kγ inhibitors. Additionally, we summarize the experimental and computational techniques utilized to identify PI3Kγ inhibitors. The insights gained so far could be used to overcome the main challenges in development and accelerate the discovery of PI3Kγ-selective inhibitors.

Theoretical Exploring Selective-Binding Mechanisms of JAK3 by 3D-QSAR, Molecular Dynamics Simulation and Free Energy Calculation

Janus kinase 3 (JAK3) plays a critical role in the JAK/STAT signaling pathway and has become an attractive selective target for the treatment of immune-mediated disorders. Therefore, great efforts have been made for the development of JAK3 inhibitors, but developing selective JAK3 inhibitors remains a great challenge because of the high sequence homology with other kinases. In order to reveal the selective-binding mechanisms of JAK3 and to find the key structural features that refer to specific JAK3 inhibition, a systematic computational method, including 3D-QSAR, molecular dynamics simulation, and free energy calculations, was carried out on a series of JAK3 isoform-selective inhibitors. Necessary pharmacodynamic structures and key residues involved in efficient JAK3-inhibition were then highlighted. Finally, 10 novel JAK3 inhibitors were designed, the satisfactory predicted binding affinity to JAK3 of these analogous demonstrated that this study may facilitate the rational design of novel and selective JAK3 inhibitors.

Identification of potential leukocyte antigen-related protein (PTP-LAR) inhibitors through 3D QSAR pharmacophore-based virtual screening and molecular dynamics simulation

Owing to its negative regulatory role in insulin signaling, protein tyrosine phosphatase of leukocyte antigen-related protein (PTP-LAR) was widely thought as a potential drug target for diabetes. Now, it was urgent to search for potential LAR inhibitors targeting diabetes. Initially, the pharmacophore models of LAR inhibitors were established with the application of the HypoGen module. The cost analysis, test set validation, as well as Fischer's test was used to verify the efficiency of pharmacophore model. Then, the best pharmacophore model (Hypo-1-LAR) was applied for the virtual screening of the ZINC database. And 30 compounds met the Lipinski's rule of five. Among them, 10 compounds with better binding affinity than the known LAR inhibitor (BDBM50296375) were discovered by docking studies. Finally, molecular dynamics simulations and post-analysis experiments (RMSD, RMSF, PCA, DCCM and RIN) were conducted to explore the effect of ligands (ZINC97018474 and Compound 1) on LAR and preliminary understand why ZINC97018474 had better inhibitory activity than Compound 1 (BDBM50296375). Communicated by Ramaswamy H. Sarma.

Virtual identification of novel peroxisome proliferator-activated receptor (PPAR) α/δ dual antagonist by 3D-QSAR, molecule docking, and molecule dynamics simulation

The therapeutic potential of PPARs antagonists extends beyond diabetes. PPARs antagonists represent a new drug class that holds promise as a broadly applicable therapeutic approach for cancer treatment. Thus, there is a strong need to develop a rational design strategy for creating PPARs antagonists. In this study, three-dimensional quantitative structure-activity relationship (3D-QSAR) models of PPARα receptor (CoMFA-1, q ² = 0.636, r ² = 0.953; CoMSIA-1, q ² = 0.779, r ² = 0.999) and PPARδ receptor (CoMFA-2, q ² = 0.624, r ² = 0.906; CoMSIA-2, q ² = 0.627, r ² = 0.959) were successfully constructed using 35 triazolone ring derivatives. Contour map analysis revealed that the electrostatic and hydrophobic fields played vital roles in the bioactivity of dual antagonists. Molecular docking studies suggested that the hydrogen bonding, electrostatic and hydrophobic interactions all influenced the binding of receptor-ligand complex. Based on the information obtained above, we designed a series of compounds. The docking results were mutually validated with 3D-QSAR results. Three-dimensional-QSAR and absorption, distribution, metabolism, excretion and toxicity (ADMET) predictions indicated that 19 newly designed compounds possessed excellent biological activity and physicochemical properties. In summary, this research could provide theoretical guidance for the structural optimization of novel PPARα and δ dual antagonists. Communicated by Ramaswamy H. Sarma.