Novel pyrrolopyridinone derivatives as anticancer inhibitors towards Cdc7: QSAR studies based on dockings by solvation score approach

Computational and pharmacokinetics studies of 1,3-dimethylbenzimidazolinone analogues of new proposed agent against Alzheimer's disease

Background

Alzheimer's disease (AD) is a multifactorial disorder that gradually destroys wisdom and memory skills. Currently, this disease can only be treated palliatively. However, the molecular mechanisms underlying this condition remain elusive. Therefore, these treatments are inadequate. Current medications can only increase patient warning signs. Chemical structures were drawn using Chemsketch software. Spartan’14 software was used to optimize the structures using density functional theory (DFT). The PaDEL software was used to generate the descriptors. The genetic function algorithm (GFA) and multi-linear regression (MLR) approaches were used to generate the QSAR model.

Results

In the present study, we performed a computational investigation, molecular docking, and pharmacokinetics analysis of 1,3-dimethylbenzimidazolinone derivatives. The descriptors generated in the model are AATS7i, MATS5p, SpMin7_Bhe, and GATS6c. Compounds 13 and 21 have the best binding scores, 11.2 kcal/mol and 10.8 kcal/mol, respectively, and optimal protein–ligand interactions with AChE. These compounds have brilliant pharmacokinetic and physicochemical properties.

Conclusions

The model was validated and found to have good internal and external assessment parameters: R2 = 0.937, $$R_{{{\text{adj}}}}^{2}$$ R adj 2  = 0.863, $$Q_{{{\text{cv}}}}^{2}$$ Q cv 2  = 0.788, $$R_{{{\text{test}}}}^{2}$$ R test 2  = 0.756, LOF = 0.0268, $$cR_{{\text{p}}}^{2}$$ c R p 2  = 0.677. In summary, these data suggested that compounds 13 and 21 are promising multifunctional agents against AD.

Anticancer pyridines induce G2/M arrest and apoptosis via p53 and JNK upregulation in liver and breast cancer cells

In the present study, the synthesis and biological evaluation of one novel pyridine and one novel pyridone anticancer compound is reported. The compounds 6-(2,4-dimethoxyphenyl)-4-(3,4-methylenedioxyphenyl)-1H-pyridin-2-one (1) and 2-(2,4-dimethoxyphenyl)-4-(3,4-methylenedioxyphenyl)pyridine (2) were synthesized from a chalchone precursor. 1 was more active than 2 in inhibiting the proliferation of MCF-7 and HepG2 cells, whereas HepG2 cells were more sensitive to the antiproliferative activity of these compounds compared with MCF-7 cells. The lowest IC₅₀ value was noted for compound 1 in HepG2 cells (IC₅₀=4.5±0.3 µM). The mechanism of action involved induction of G2/M arrest and apoptosis. Both 1 and 2 further induced downregulation of the cell cycle-associated protein cyclin D1 and upregulation of the cell cycle inhibitors p53 and p21 and the apoptosis-associated protein JNK in HepG2 cells. Compound 1 was further shown to induce phosphorylation of JNK in HepG2 cells. These results demonstrate promising cytostatic effects for the two novel anticancer compounds in human cancer cells.

Alzheimer's disease drug development based on Computer-Aided Drug Design

Alzheimer's disease (AD) is a common neurodegenerative disorder characterized by the excessive deposition of amyloids in the brain. The pathological features mainly include the extracellular amyloid plaques and intracellular neurofibrillary tangles, which are the production of amyloid precursor protein (APP) processed by the α-, β- and γ-secretases. Based on the amyloid cascade hypotheses of AD, a large number of amyloid-β agents and secretase inhibitors against AD have been recently developed by using computational methods. This review article describes pathophysiology of AD and the structure of the Aβ plaques, β- and γ-secretases, and discusses the recent advances in the development of the amyloid agents for AD therapy and diagnosis by using Computer-Aided Drug Design approach.

Screening of novel inhibitors targeting lactate dehydrogenase A via four molecular docking strategies and dynamics simulations

Lactate dehydrogenase A (LDHA) is a metabolic enzyme which catalyzes the interconversion of lactate and pyruvate in the glycolysis pathway, thus playing key roles in aerobic glycolysis. The inhibition of LDHA by small molecules has become an attractive strategy for anticancer therapy in recent years. However, very few LDHA inhibitors have been reported, even though a great deal of effort has directed into identifying LDHA inhibitors using structure-based approaches. Therefore, high-throughput and high-accuracy screening approaches are still urgently needed in order to target LDHA effectively. In the present work, after establishing that our docking strategies performed well using test datasets, we screened 32791 Specs products for their docking scores with the substrate-binding pocket and, separately, the cofactor-binding pocket of LDHA. We subsequently identified 76 hits (i.e., ligands that show low docking scores) for the cofactor-binding pocket and 27 hits for the substrate-binding pocket. Two representative compounds, ZINC20036549 and ZINC19369718, were then chosen for further MD simulation analysis, and we found that these compounds maintained their inhibitory activity during the MD simulations. Meanwhile, we found that ZINC19369718 interacts with a novel binding site close to the active site, and that this interaction may inhibit the catalytic activity of LDHA. Together, these results offer not only a new paradigm for identifying Specs drug-like products for novel therapeutic use but they also provide further opportunity to adopt LDHA inhibition as a strategy for cancer therapy.