Computational investigation of the antagonism effect towards GluN2B-Containing NMDA receptor: Combined ligand-based and target-based approach

Identification and in silicon binding study of a novel NR2B selective NMDAR antagonist

Alzheimer's disease (AD) is a major group of diseases that threaten human health, and the search for drugs and treatments for it has never stopped. Research and development of NMDA receptor antagonists as potential therapeutic targets have also been ongoing. Our group designed and synthesized 22 new tetrahydropyrrolo[2,1-b]quinazolines based on NR2B-NMDARs targets and evaluated them for their neuroprotective activity against NMDA-induced cytotoxicity in vitro, A21 exhibited excellent neuroprotective activity. Subsequently, the structure-activity relationships and inhibitor binding modes of the tetrahydropyrrolo[2,1-b]quinazolines were further analyzed by molecular docking, molecular dynamics (MD) simulations and binding free energy calculations. The results showed that A21 could match the two binding pockets of NR2B-NMDARs. The research results of this project will lay a certain foundation for the research of novel NR2B-NMDA receptor antagonists and also provide new ideas for the subsequent research and development of this target.

Computer-aided discovery of pleiotropic effects: Anti-inflammatory action of dithioloquinolinethiones as a case study

Most of pharmaceutical agents exhibit several or even many biological activities. It is clear that testing even one compound for thousands of biological activities is a practically not feasible task. Therefore, computer-aided prediction is the method-of-the-choice to select the most promising bioassays for particular compounds. Using PASS Online software, we determined the likely anti-inflammatory action of the 13 dithioloquinolinethione derivatives with antimicrobial activities. Chemical similarity search in the Cortellis Drug Discovery Intelligence database did not reveal close structural analogues with anti-inflammatory action. Experimental testing of anti-inflammatory activity of the synthesized compounds in carrageenan-induced inflammation mouse model confirmed the computational predictions. The anti-inflammatory activity of the studied compounds was comparable with or higher than the reference drug Indomethacin. Thus, based on the in silico predictions, novel class of the anti-inflammatory agents was discovered.

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.

Repurposing of cefpodoxime proxetil as potent neuroprotective agent through computational prediction and in vitro validation

In recent reports, NR2B-NMDA receptor antagonists showed more research value because of its strong targeting ability and less side effects potential. In 2016, EVT-101 was reported to bind in an almost entirely new binding region of this target. Whether strikingly different binding modes can improve targeting and reduce side effects is worth studying. In our preliminary work, we explored the binding patterns of ifenprodil and EVT-101, found the key amino acids and summarized the pharmacophores, hoping to find such antagonists that target the two binding modes simultaneously. In this study, we developed a scalable virtual screening workflow in the FDA-approved drugs library to identify novel NR2B-NMDAR antagonists based on the combination of two pharmacophores. Cefpodoxime proxetil (5) was identified as the hit compound, and it was found for the first time that 5 might have neuroprotective activity as a NR2B-NMDAR antagonist. This result interested us to make further study, the ligand-receptor interactions modeled by molecular docking studies showed that the compound could perfectly merge both the pharmacophore characteristics of ifenprodil and EVT-101 at the binding cavity between the ATDs of GluN1 and GluN2B. The accuracy of molecular docking results and binding stability of ligand-receptor complexes were validated through 100 ns molecular dynamics simulation and binding free energy calculation. Afterwards, MTT assay (49.8%±0.1%, 5 μM) on NMDA injured SH-SY5Y cells and evidence of the effect on attenuating Ca2+ influx induced by NMDA were applied to validate the computational results, further investigation showed that 5 could suppress the NR2B upregulation induced by NMDA. [Formula: see text] Communicated by Ramaswamy H. Sarma.