Theoretical studies on the selectivity mechanisms of PI3Kδ inhibition with marketed idelalisib and its derivatives by 3D-QSAR, molecular docking, and molecular dynamics simulation

Chemical analogue based drug design for cancer treatment targeting PI3K: integrating machine learning and molecular modeling

Cancer is a generic term for a group of disorders defined by uncontrolled cell growth and the potential to invade or spread to other parts of the body. Gene and epigenetic alterations disrupt normal cellular control, leading to abnormal cell proliferation, resistance to cell death, blood vessel development, and metastasis (spread to other organs). One of the several routes that play an important role in the development and progression of cancer is the phosphoinositide 3-kinase (PI3K) signaling pathway. Moreover, the gene PIK3CG encodes the catalytic subunit gamma (p110γ) of phosphoinositide 3-kinase (PI3Kγ), a member of the PI3K family. Therefore, in this study, PIK3CG was targeted to inhibit cancer by identifying a novel inhibitor through computational methods. The study screened 1015 chemical fragments against PIK3CG using machine learning-based binding estimation and docking to select the potential compounds. Later, the analogues were generated from the selected hits, and 414 analogues were selected, which were further screened, and as most potential candidates, three compounds were obtained: (a) 84,332, 190,213, and 885,387. The protein-ligand complex's stability and flexibility were then investigated by dynamic modeling. The 100 ns simulation revealed that 885,387 exhibited the steadiest deviation and constant creation of hydrogen bonds. Compared to the other compounds, 885,387 demonstrated a superior binding free energy (ΔG = -18.80 kcal/mol) with the protein when the MM/GBSA technique was used. The study determined that 885,387 showed significant therapeutic potential and justifies further experimental investigation as a possible inhibitor of the PIK3CG target implicated in cancer.

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.

Design of Novel Phosphatidylinositol 3-Kinase Inhibitors for Non-Hodgkin's Lymphoma: Molecular Docking, Molecular Dynamics, and Density Functional Theory Studies on Gold Nanoparticles

Non-Hodgkin's lymphomas are a diverse collection of lymphoproliferative cancers that are much less predictable than Hodgkin's lymphomas with a far greater tendency to metastasize to extranodal sites. A quarter of non-Hodgkin's lymphoma cases develop at extranodal sites and the majority of them involve nodal and extranodal sites. The most common subtypes include follicular lymphoma, chronic/small lymphocytic leukaemia, mantel cell lymphoma, and marginal zone lymphoma. Umbralisib is one of the latest PI3Kδ inhibitors in clinical trials for several hematologic cancer indications. In this study, new umbralisib analogues were designed and docked to the active site of PI3Kδ, the main target of the phosphoinositol-3-kinase/Akt/mammalian target of the rapamycin pathway (PI3K/AKT/mTOR). This study resulted in eleven candidates, with strong binding to PI3Kδ with a docking score between -7.66 and -8.42 Kcal/mol. The docking analysis of ligand-receptor interactions between umbralisib analogues bound to PI3K showed that their interactions were mainly controlled by hydrophobic interactions and, to a lesser extent, by hydrogen bonding. In addition, the MM-GBSA binding free energy was calculated. Analogue 306 showed the highest free energy of binding with -52.22 Kcal/mol. To identify the structural changes and the complexes' stability of proposed ligands, molecular dynamic simulation was used. Based on this research finding, the best-designed analogue, analogue 306, formed a stable ligand-protein complex. In addition, pharmacokinetics and toxicity analysis using the QikProp tool demonstrated that analogue 306 had good absorption, distribution, metabolism, and excretion properties. Additionally, it has a promising predicted profile in immune toxicity, carcinogenicity, and cytotoxicity. In addition, analogue 306 had stable interactions with gold nanoparticles that have been studied using density functional theory calculations. The best interaction with gold was observed at the oxygen atom number 5 with -29.42 Kcal/mol. Further in vitro and in vivo investigations are recommended to be carried out to verify the anticancer activity of this analogue.

Turning down PI3K/AKT/mTOR signalling pathway by natural products: an in silico multi-target approach

The PI3K/AKT/mTOR pathway is a significant target for cancer drug discovery. Many efforts have focused on discovering new inhibitors against key kinase proteins involved in this pathway for cancer treatment. PI3K/mTOR dual inhibitors, such as PKI-179, have been reported to be more effective than agents that act only on a single protein target. The present computational study aimed to discover triple target inhibitors against PI3K, AKT, and mTOR proteins. Accordingly, the PI3K protein bound with the ligand was used as input for e-pharmacophore modelling to generate the pharmacophore hypothesis and then screened for a library of 270,540 natural products from the Zinc database resulting in 57,220 compounds that matched the hypothesis. These compounds were then docked into the active site of PI3K, resulting in 292 compounds with better docking scores than the co-crystallized ligand. These compounds were re-docked into AKT and mTOR proteins. Besides, MM-GBSA binding free energy calculations, MD simulations, and ADMET prediction were carried out, leading to 5 potential triple-target inhibitors namely, ZINC000014644152, ZINC000014760695, ZINC000014644839, ZINC000095099451, and ZINC000005998557. In conclusion, these inhibitors may be possible leads for inhibiting PI3K/AKT/mTOR pathway, and they may be further evaluated in vitro and clinically as anticancer agents.

Computational study reveals substituted benzimidazole derivatives' binding selectivity to PI3Kδ and PI3Kγ

Phosphatidylinositol 3-kinase (PI3K) is a key regulatory kinase in the PI3K/AKT/mTOR signaling pathway, which is involved in the regulation of cell proliferation, differentiation, apoptosis, and angiogenesis. Class IA PI3K isoforms γ and δ share a highly homologous ATP binding site and are distinguished by only a few residues around the binding site. Subtype-selective inhibitors have been proven to have great advantages in tumor treatment. Preliminary studies have obtained PI3K inhibitors bearing a benzimidazole structural motif with a certain selectivity for PI3Kδ and PI3Kγ subtypes. On this basis, we investigated the selective inhibitory mechanism of PI3Kδ and PI3Kγ using four developed inhibitors via molecular docking, molecular dynamics, binding free energy calculations, and residue energy decomposition. This study could provide references for the further development of PI3K-isoform-selective inhibitors.

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.

DFT based QSAR study on quinolone-triazole derivatives as antibacterial agents

QSAR modeling was performed on 39 quinolone-triazole derivatives against gram-positive Staphylococcus aureus and gram-negative Pseudomonas aeruginosa bacteria. The molecular structures were optimized using the DFT/B3LYP method and 6-31 G basis set. Molecular descriptors were extracted using quantum mechanical calculations. The hierarchical cluster analysis was performed for a rational subset division. The initial dataset was divided into calibration and validation sets, and modeling was done by stepwise MLR method for each of the two bacteria. Internal and external validation methods confirmed the robustness and predictability of the obtained models. According to the obtained model for S. aureus (R² = 0.889, R²_ext = 0.938, Q²_LOO = 0.853), the four descriptors- partial atomic charges for the N1 atom in triazole and C7 of the quinolone nucleus, 4-carbonyl bond length, and ¹³C-NMR chemical shift of 3-carboxylic acid- were found to be the descriptors controlling the activity. According to the obtained model for P. aeruginosa (R² = 0.957, R²_ext = 0.923, Q²_LOO = 0.909), the O atom's partial charge in carbonyl, LUMO-HOMO energy gap, and logP were found to be the descriptors having the highest correlation with the antibacterial activity. Finally, some new compounds with higher activities were designed and proposed.

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.

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.

QSAR Modeling, Molecular Docking and Molecular Dynamics Simulations Studies of Lysine-Specific Demethylase 1 (LSD1) Inhibitors as Anticancer Agents

BACKGROUND

Histone Lysine Demetylases1 (LSD1) is a promising medication to treat cancer, which plays a crucial role in epigenetic modulation of gene expression. Inhibition of LSD1with small molecules has emerged as a vital mechanism to treat cancer.

OBJECTIVE

In the present research, molecular modeling investigations, such as CoMFA, CoMFA-RF, CoMSIA and HQSAR, molecular docking and Molecular Dynamics (MD) simulations were carried out on some tranylcypromine derivatives as LSD1 inhibitors.

METHODS

The QSAR models were carried out on a series of Tranylcypromine derivatives as data set via the SYBYL-X2.1.1 program. Molecular docking and MD simulations were carried out by the MOE software and the SYBYL program, respectively. The internal and external predictability performances related to the generated models for these LSD1 inhibitors were justified by evaluating cross-validated correlation coefficient (q²), noncross- validated correlation coefficient (r²_ncv) and predicted correlation coefficient (r²_pred) of the training and test set molecules, respectively.

RESULTS

The CoMFA (q², 0.670; r²_ncv, 0.930; r²_pred, 0.968), CoMFA-RF (q², 0.694; r²_ncr, 0.926; r²_pred, 0.927), CoMSIA (q², 0.834; r²_ncv, 0.956; r²_pred, 0.958) and HQSAR models (q², 0.854; r²_ncv, 0.900; r²_pred, 0.728) for training as well as the test set of LSD1 inhibition resulted in significant findings.

CONCLUSION

These QSAR models were found to be perfect and strong with better predictability. Contour maps of all models were generated and it was proven by molecular docking studies and molecular dynamics simulation that the hydrophobic, electrostatic and hydrogen bonding fields are crucial in these models for improving the binding affinity and determining the structure-activity relationship. These theoretical results are possibly beneficial to design new strong LSD1 inhibitors with enhanced activity to treat cancer.

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.

Molecular modelling of quinoline derivatives as telomerase inhibitors through 3D-QSAR, molecular dynamics simulation, and molecular docking techniques

Rising mortality due to cancer has led to the development and identification of newer targets and molecules to cure the disease. Telomerase is one of the attractive targets for design of many chemotherapeutic drugs. This research highlights the designing of novel telomerase inhibitors using ligand-based (3D-QSAR) and structure-based (molecular docking and molecular dynamics simulation) approaches. For the development of the 3D-QSAR model, 37 synthetic molecules reported earlier as telomerase inhibitors were selected from diversified literature. Three different alignment methods were explored; among them, distill alignment was found to be the best method with good statistical results and was used for the generation of QSAR model. Statistically significant CoMSIA model with a correlation coefficient (r²_ncv) value of 0.974, leave one out (q²) value of 0.662 and predicted correlation coefficient (r²_pred) value of 0.560 was used for the analysis of QSAR. For the MDS study, A-chain of telomerase was stabilised for 50 ns with respect to 1-atm pressure, with an average temperature of 299.98 k and with potential energy of 1,145,336 kJ/m converged in 997 steps. Furthermore, the behaviour study of variants towards the target revealed that active variable gave better affinity without affecting amino acid sequences and dimensions of protein which was accomplished through RMSD, RMSF and Rg analysis. Results of molecular docking study supported the outcomes of QSAR contour maps as ligand showed similar interactions with surrounded amino acids which were identified in contour map analysis. The results of the comprehensive study might be proved valuable for the development of potent telomerase 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.