Pharmacophore Modeling and Hybrid Virtual Screening for the Discovery of Novel IκB Kinase 2 (IKK2) Inhibitors

The discovery of a novel IκB kinase β inhibitor based on pharmacophore modeling, virtual screening and biological evaluation

Background: IκB kinase β (IKKβ) plays a pivotal role in the NF-κB signaling pathway and is considered a promising therapeutic target for various diseases. Materials & methods: The authors developed and validated a 3D pharmacophore model of IKKβ inhibitors via the HypoGen algorithm in Discovery Studio 2019, then performed virtual screening, molecular docking and kinase assays to identify hit compounds from the ChemDiv database. The compound with the highest inhibitory activity was further evaluated in adjuvant-induced arthritis rat models. Results: Among the four hit compounds, Hit 4 had the highest IKKβ inhibitory activity (IC50 = 30.4 ± 3.8), and it could significantly ameliorate joint inflammation and damage in vivo. Conclusion: The identified compound, Hit 4, can be optimized as a therapeutic agent for inflammatory diseases.

Discovery of specific HDAC6 inhibitor with anti-metastatic effects in pancreatic cancer cells through virtual screening and biological evaluation

Histone deacetylase 6 (HDAC6) has been demonstrated to play a major role in cell motility and aggresome formation, and HDAC6 inhibition is therefore considered as a promising epigenetic strategy for cancer treatment. At present, only a minority of compounds have been reported as HDAC6 inhibitors, so specific HDAC6 inhibitors with safety profile need to be discovered urgently. In this paper, HDAC6 inhibitors with diverse structures were used to generate the pharmacophore model by ligand-based method, which contained two hydrogen bond acceptors and two hydrophobic groups. A combined virtual screening based on pharmacophore model and molecular docking was adopted to screen potential HDAC6 inhibitors. Subsequently, the HDAC6 inhibitory activity of the hit compounds were evaluated using an in vitro enzyme binding inhibition assay. The experimental results illustrated that cefoperazone sodium had the strongest inhibitory effect on HDAC6 among the six screened compounds, and its IC₅₀ value was 8.59 ± 1.06 μM. Cefoperazone sodium significantly catalyzed the hyperacetylation of α-tubulin but not histone H3, proving that cefoperazone sodium was a selective inhibitor of HDAC6. Since the expression of HDAC6 plays an important role in cancer metastasis, the effects of cefoperazone sodium on migration and invasion of human pancreatic cancer PANC-1 cells were further investigated by wound healing and transwell chamber assays. It was found that cefoperazone sodium could evidently inhibit the migration and invasion of PANC-1 cells. Furthermore, the binding pattern of inhibitor at the active site of the crystal structure was revealed by molecular docking, providing a reference value for the structural design and optimization of HDAC6 inhibitors. This study provides a systematic virtual screening approach for discovering HDAC6 active inhibitors, and by which the specific effect of cefoperazone sodium against HDAC6 was found, suggesting its potential application on cancer therapy.

Multiple receptor-ligand based pharmacophore modeling and molecular docking to screen the selective inhibitors of matrix metalloproteinase-9 from natural products

Matrix metalloproteinase-9 (MMP-9) is an attractive target for cancer therapy. In this study, the pharmacophore model of MMP-9 inhibitors is built based on the experimental binding structures of multiple receptor-ligand complexes. It is found that the pharmacophore model consists of six chemical features, including two hydrogen bond acceptors, one hydrogen bond donor, one ring aromatic regions, and two hydrophobic (HY) features. Among them, the two HY features are especially important because they can enter the S1' pocket of MMP-9 which determines the selectivity of MMP-9 inhibitors. The reliability of pharmacophore model is validated based on the two different decoy sets and relevant experimental data. The virtual screening, combining pharmacophore model with molecular docking, is performed to identify the selective MMP-9 inhibitors from a database of natural products. The four novel MMP-9 inhibitors of natural products, NP-000686, NP-001752, NP-014331, and NP-015905, are found; one of them, NP-000686, is used to perform the experiment of in vitro bioassay inhibiting MMP-9, and the IC₅₀ value was estimated to be only 13.4 µM, showing the strongly inhibitory activity of NP-000686 against MMP-9, which suggests that our screening results should be reliable. The binding modes of screened inhibitors with MMP-9 active sites were discussed. In addition, the ADMET properties and physicochemical properties of screened four compounds were assessed. The found MMP-9 inhibitors of natural products could serve as the lead compounds for designing the new MMP-9 inhibitors by carrying out structural modifications in the future.

Human microtubule affinity-regulating kinase 4 is stable at extremes of pH

MAP/microtubule affinity-regulating kinase 4 (MARK4) is a member of adenosine monophosphate-activated protein kinases, directly associated with cancer and neurodegenerative diseases. Here, we have cloned, expressed, and purified two variants of MARK4 [the kinase domain (MARK4-F2), and kinase domain along with 59 N-terminal residues (MARK4-F1)] and compared their stability at varying pH range. Structural and functional changes were observed by incubating both forms of MARK4 in buffers of different pH. We measured the secondary structure of MARK4 using circular dichroism and tertiary structure by measuring intrinsic fluorescence and absorbance properties along with the size of proteins by dynamic light scattering. We observed that at extremes of pH (below pH 3.5 and above pH 9.0), MARK4 is quite stable. However, a remarkable aggregate formation was observed at intermediate pH (between pH 3.5 and 9.0). To further validate this result, we have modeled both forms of MARK4 and performed molecular dynamics simulation for 15 ns. The spectroscopic observations are in excellent agreement with the findings of molecular dynamics simulation. We also performed ATPase activity at varying pH and found a significant correlation of structure of MARK4 with its enzyme activity. It is interesting to note that both forms of MARK4 are showing a similar pattern of structure changes with reference to pH.

Metrics and the effective computational scientist: process, quality and communication

Recent treatments of computational knowledge worker productivity have focused upon the value the discipline brings to drug discovery using positive anecdotes. While this big picture approach provides important validation of the contributions of these knowledge workers, the impact accounts do not provide the granular detail that can help individuals and teams perform better. I suggest balancing the impact-focus with quantitative measures that can inform the development of scientists. Measuring the quality of work, analyzing and improving processes, and the critical evaluation of communication can provide immediate performance feedback. The introduction of quantitative measures can complement the longer term reporting of impacts on drug discovery. These metric data can document effectiveness trends and can provide a stronger foundation for the impact dialogue.