Combination of pharmacophore hypothesis, genetic function approximation model, and molecular docking to identify novel inhibitors of S6K1

A General Model of Impact Sensitivity for Nitrogen-Rich Energetic Materials: A Combined Incremental Theory and Genetic Function Approximation Study

In this paper, we report the first example of impact sensitivity prediction based on the genetic function approximation (GFA) as a regression method. The prediction is applicable for a wide variety of chemical families, which include nitro compounds, peroxides, nitrogen-rich salts, heterocycles, etc. Within this work, we have obtained 7 empirical models (with 27-32 basis functions), which all provide 0.80≤R2≤0.83 and 7.2 J≤RMSE≤7.8 J (for 450 training set compounds) and 0.64≤R2≤0.70 and 11.2 J≤RMSE≤12.4 J (for 170 test set compounds). The models were developed using Friedman Lack-of-Fit as a scoring function, which allows avoiding an overfitting. All the models have simple descriptors as basis functions and include linear splines. Furthermore, the applied descriptors do not require expensive calculation procedures, namely, non-empirical quantum-chemical calculations, complex iterative procedures, real space electron density analysis, etc. Most descriptors are based on structural and topological analysis and a part of them require very cheap semi-empirical PM6 calculations. The prediction takes a few minutes as an average, and most of the time is for the structure preparation and manual calculation of the descriptor "Increment", which is based on our recent incremental theory.

p70 S6 kinase as a therapeutic target in cancers: More than just an mTOR effector

p70 S6 kinase (p70^S6K) is best-known for its regulatory roles in protein synthesis and cell growth by phosphorylating its primary substrate, ribosomal protein S6, upon mitogen stimulation. The enhanced expression/activation of p70^S6K has been correlated with poor prognosis in some cancer types, suggesting that it may serve as a biomarker for disease monitoring. p70^S6K is a critical downstream effector of the oncogenic PI3K/Akt/mTOR pathway and its activation is tightly regulated by an ordered cascade of Ser/Thr phosphorylation events. Nonetheless, it should be noted that other upstream mechanisms regulating p70^S6K at both the post-translational and post-transcriptional levels also exist. Activated p70^S6K could promote various aspects of cancer progression such as epithelial-mesenchymal transition, cancer stemness and drug resistance. Importantly, novel evidence showing that p70^S6K may also regulate different cellular components in the tumor microenvironment will be discussed. Therapeutic targeting of p70^S6K alone or in combination with traditional chemotherapies or other microenvironmental-based drugs such as immunotherapy may represent promising approaches against cancers with aberrant p70^S6K signaling. Currently, the only clinically available p70^S6K inhibitors are rapamycin analogs (rapalogs) which target mTOR. However, there are emerging p70^S6K-selective drugs which are going through active preclinical or clinical trial phases. Moreover, various screening strategies have been used for the discovery of novel p70^S6K inhibitors, hence bringing new insights for p70^S6K-targeted therapy.

Computer-aided discovery of phenylpyrazole based amides as potent S6K1 inhibitors

Ribosomal protein S6 kinase beta-1 (S6K1) is an attractive therapeutic target. In this study, computational analysis of five thiophene urea-based S6K1 inhibitors was performed. Molecular docking showed that the five compounds formed hydrogen bonds with residues Glu173 and Leu175 of S6K1 and hydrophobic interactions with residues Val105, Leu97 and Met225, and these interactions were key elements for the inhibitory potency of the compounds. Binding free energy (ΔG _bind) decomposition analysis showed that Leu97, Glu173, Val 105, Leu175, Leu97 and Met225 contribute the most to ΔG _bind. Based on the computer results, phenylpyrazole based amides (D1-D3) were designed and synthesized. Biological evaluation revealed that D2 exhibited 15.9 nM S6K1 inhibition, medium microsomal stability and desirable bioavailability.

Molecular Dynamics Studies on COX-2 Protein-tyrosine Analogue Complex and Ligand-based Computational Analysis of Halo-substituted Tyrosine Analogues

Background:

The quest for new drug entities and novel structural fragments with applications in therapeutic areas is always at the core of medicinal chemistry.

Methods:

As part of our efforts to develop novel selective cyclooxygenase-2 (COX-2) inhibitors containing tyrosine scaffold. The objective of this study was to identify potent COX-2 inhibitors by dynamic simulation, pharmacophore and 3D-QSAR methodologies. Dynamics simulation was performed for COX-2/tyrosine derivatives complex to characterise structure validation and binding stability. Certainly, Arg120 and Tyr355 residue of COX-2 protein formed a constant interaction with tyrosine inhibitor throughout the dynamic simulation phase. A four-point pharmacophore with one hydrogen bond acceptor, two hydrophobic and one aromatic ring was developed using the HypoGen algorithm. The generated, statistically significant pharmacophore model, Hypo 1 with a correlation coefficient of r2, 0.941, root mean square deviation, 1.15 and total cost value of 96.85.

Results:

The QSAR results exhibited good internal (r2, 0.992) and external predictions (r2pred, 0.814). The results of this study concluded the COX-2 docked complex was stable and interactive like experimental protein structure. Also, it offered vital chemical features with geometric constraints responsible for the inhibition of the selective COX-2 enzyme by tyrosine derivatives.

Conclusion:

In principle, this work offers significant structural understandings to design and develop novel COX-2 inhibitors.

Pharmacophore modeling, multiple docking, and molecular dynamics studies on Wee1 kinase inhibitors

Wee1-like protein kinase (Wee1) is a tyrosine kinase that regulates the G₂ checkpoint and prevents entry into mitosis in response to DNA damage. Based on a series of signaling pathways initiated by Wee1, Wee1 has been recognized as a potential target for cancer therapy. To discover potent Wee1 inhibitors with novel scaffolds, ligand-based pharmacophore model has been built based on 101 known Wee1 inhibitors. Then the best pharmacophore model, AADRRR.340, with good partial least square (PLS) statistics (R² = 0.9212, Q² = 0.7457), was selected and validated. The validated model was used as a three-dimensional (3D) search query for databases virtual screening. The filtered molecules were further analyzed and refined by Lipinski's rule of 5, multiple docking procedures (high throughput virtual screening (HTVS), standard precision (SP), genetic optimization for ligand docking (GOLD), extra precision (XP), and unique quantum polarized ligand docking (QPLD)); absorption, distribution, metabolism, excretion, and toxicity (ADMET) screening; and the Prime/molecular mechanics generalized born surface area (MM-GBSA) method binding free energy calculations. Eight leads were identified as potential Wee1 inhibitors, and a 50 ns molecular dynamics (MD) simulation was carried out for top four inhibitors to predict the stability of ligand-protein complex. Molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) based on MD simulation and the energy contribution per residue to the binding energy were calculated. In the end, three hits with good stabilization and affinity to protein were identified. Communicated by Ramaswamy H. Sarma.

Identification of novel potent human testis-specific and bromodomain-containing protein (BRDT) inhibitors using crystal structure-based virtual screening

Human testis-specific and bromodomain-containing protein (hBRDT) is essential for chromatin remodeling during spermatogenesis and is therefore an attractive target for the discovery of male contraceptive drugs. In this study, pharmacophore modeling was carried out based on the crystal structure of hBRDT in complex with the inhibitor, JQ1. The established pharmacophore model was used as a 3D search query to identify potent hBRDT inhibitors from an in-house chemical database. A molecular docking analysis was carried out to filter the obtained hit compounds. A total of 125 compounds was finally selected based on the ranking order and visual examination. These compounds were further evaluated by a protein-based in vitro assay. Four compounds with new chemical scaffolds were identified to be hBRDT inhibitors. The most active of these compounds, T480, had a half maximal inhibitory concentration (IC50) of 9.02 µM. The detailed analysis of the binding mode of compound T480 provides important information for the further development of novel BRDT inhibitors.