High-throughput screening against $$\sim $$ ∼ 6.1 million structurally diverse, lead-like compounds to discover novel ROCK inhibitors for cerebral injury recovery

Discovery of ROCK2 inhibitors through computational screening of ZINC database: Integrating pharmacophore modeling, molecular docking, and MD simulations

Rho-associated protein kinase 2 (ROCK2) is a serine/threonine kinase that is crucial for regulating various physiological processes and is part of the Rho-associated coiled-coil kinase family. The dysregulation of ROCK2 has been associated with a range of diseases, making it a promising target for therapy. In this study, a chemical feature-based pharmacophore model was developed on the co-crystal ligand (5YS) of ROCK2 to conduct the virtual screening of ZINC database, resulting in 4809 hits that were further subjected to molecular docking to find the binding affinities with ROCK2 protein. The binding affinities of the hits were analyzed and compounds in the range of -11.55 to -9.91 kcal/mol were selected for further analysis. The ADMET analysis identified two promising compounds, whose binding stability with the ROCK2 protein was further evaluated using molecular dynamics (MD) simulations. Simulation results revealed that the selected compounds remained closely bound to protein indicating that they can act as lead compounds to control the biological activity of ROCK2. However, further in vitro investigation is required to test the biological efficacy of the reported compounds.

Fragment-Based Dynamic Combinatorial Chemistry for Identification of Selective α-Glucosidase Inhibitors

Efforts to combine advantages of fragment-based drug design (FBDD) and dynamic combinatorial chemistry (DCC) for the development of selective α-glucosidase inhibitors were described. Starting from 5 rationally designed fragments, two iterative dynamic combinatorial libraries (DCLs) comprising 29 acylhydrazone products were generated and screened using α-glucosidase and α-amylase as the templates. The optimal ligand identified showed substantial α-glucosidase inhibition with high selectivity over α-amylase as well as low cytotoxicity. Furthermore, inhibition type and detailed ligand/enzyme binding interactions were elucidated by the binding kinetic study and docking simulation, respectively.

Development of urease inhibitors by fragment-based dynamic combinatorial chemistry

In this study, fragment-based dynamic combinatorial chemistry (DCC) was explored for the development of novel urease inhibitors. Based on a rationally designed fragment, two iteratively evolved dynamic combinatorial libraries (DCLs) were generated and screened in the presence of urease template. The best ligand identified revealed not only strong urease inhibition but also low cytotoxicity. Additionally, possible inhibitory mechanism was elucidated in the binding kinetic study and docking simulation.

Integration of virtual screening and susceptibility test to discover active-site subpocket-specific biogenic inhibitors of Helicobacter pylori shikimate dehydrogenase

Shikimate dehydrogenase (HpSDH) (EC 1.1.1.25) is a key enzyme in the shikimate pathway of Helicobacter pylori (H. pylori), which catalyzes the NADPH-dependent reversible reduction of 3-dehydroshikimate to shikimate. Targeting HpSDH has been recognized as an attractive therapeutic strategy against H. pylori infection. Here, the catalytic active site in the crystal structure of HpSDH in complex with its substrate NADPH and product shikimate was examined in detail; the site can be divided into three spatially separated subpockets that separately correspond to the binding regions of shikimate, NADPH dihydronicotinamide moiety, and NADPH adenine moiety. Subsequently, a cascading protocol that integrated virtual screening and antibacterial test was performed against a biogenic compound library to identify biologically active, subpocket-specific inhibitors. Consequently, five, eight, and six promising compounds for, respectively, subpockets 1, 2, and 3 were selected from the top-100 docking-ranked hits, from which 11 compounds were determined to have high or moderate antibacterial potencies against two reference H. pylori strains, with MIC range between 8 and 93 μg/mL. It is found that the HpSDH active site prefers to accommodate amphipathic and polar inhibitors that consist of an aromatic core as well as a number of oxygen-rich polar/charged substituents such as hydroxyl, carbonyl, and carboxyl groups. Subpockets 1- and 2-specific inhibitors exhibit a generally higher activity than subpocket 3-specific inhibitors. Molecular dynamics simulations revealed an intense nonbonded network of hydrogen bonds, π-π stacking, and van der Waals contacts at the tightly packed complex interfaces of active-site subpockets with their cognate inhibitors, conferring strong stability and specificity to these complex systems. Binding energetic analysis demonstrated that the identified potent inhibitors can target their cognate subpockets with an effective selectivity over noncognate ones.

Rational screening of peroxisome proliferator-activated receptor-γ agonists from natural products: potential therapeutics for heart failure

CONTEXT

Peroxisome proliferator-activated receptor-γ (PPARγ) is a member of the nuclear hormone receptor superfamily of ligand-activated transcription factors. Activation of PPARγ pathway has been shown to enhance fatty acid oxidation, improve endothelial cell function, and decrease myocardial fibrosis in heart failure. Thus, the protein has been raised as an attractive target for heart failure therapy.

OBJECTIVE

This work attempted to discover new and potent PPARγ agonists from natural products using a synthetic strategy of computer virtual screening and transactivation reporter assay.

MATERIALS AND METHODS

A large library of structurally diverse, drug-like natural products was compiled, from which those with unsatisfactory pharmacokinetic profile and/or structurally redundant compounds were excluded. The binding mode of remaining candidates to PPARγ ligand-binding domain (LBD) was computationally modelled using molecular docking and their relative binding potency was ranked by an empirical scoring scheme. Consequently, eight commercially available hits with top scores were selected and their biological activity was determined using a cell-based reporter-gene assay.

RESULTS

Four natural product compounds, namely ZINC13408172, ZINC4292805, ZINC44179 and ZINC901461, were identified to have high or moderate agonistic potency against human PPARγ with EC₅₀ values of 0.084, 2.1, 0.35 and 5.6 μM, respectively, which are comparable to or even better than that of the approved PPARγ full agonists pioglitazone (EC₅₀=0.16 μM) and rosiglitazone (EC₅₀=0.034 μM). Hydrophobic interactions and van der Waals contacts are the primary chemical forces to stabilize the complex architecture of PPARγ LBD domain with these agonist ligands, while few hydrogen bonds, salt bridges and/or π-π stacking at the complex interfaces confer selectivity and specificity for the domain-agonist recognition.

DISCUSSION AND CONCLUSION

The integrated in vitro-in silico screening strategy can be successfully applied to rational discovery of biologically active compounds. The newly identified natural products with PPARγ agonistic potency are considered as promising lead scaffolds to develop novel chemical therapeutics for heart failure.

Combined QSAR-based virtual screening and fluorescence binding assay to identify natural product mediators of Interferon Regulatory Factor 7 (IRF-7) in pulmonary infection

Interferon regulatory factor-7 (IRF-7) is involved in pulmonary infection and pneumonia. Here, a synthetic strategy that combined quantitative structure-activity relationship (QSAR)-based virtual screening and in vitro binding assay was described to identify new and potent mediator ligands of IRF-7 from natural products. In the procedure, a QSAR scoring function was developed and validated using Gaussian process (GP) regression and a structure-based set of protein-ligand affinity data. By integrating hotspot pocket prediction, pharmacokinetics profile analysis and molecular docking calculations, the scoring function was successfully applied to virtual screening against a large library of structurally diverse, drug-like natural products. With the method we were able to identify a number of potential hits, from which several compounds were found to have moderate or high affinity to IRF-7 using fluorescence binding assays, with dissociation constants K_d at micromolar level. We have also examined the structural basis and noncovalent interactions of computationally modelled IRF-7 complex with its potent ligands. It is revealed that hydrophobic forces and van der Waals contacts play a central role in stabilization of the complex architecture, while few hydrogen bonds confer additional specificity for the protein-ligand recognition.