Dementia is characterized by the impairment of cognition and behavior of people over 65 years. Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder in the world, as approximately 47 million people are affected by this disease and the tendency is that this number will increase to 62% by 2030. Two microscopic features assist in the characterization of the disease, the amyloid plaques and neurofibrillary agglomerates. All these factors are responsible for the slow and gradual deterioration of memory that affect language, personality or cognitive control. For the AD diagnosis, neuropsychological tests are performed in different spheres of cognitive functions but since not all cognitive functions may be affected, cerebrospinal fluid biomarkers are used along with these tests. To date, cholinesterase inhibitors are used as treatment, they are the only drugs that have shown significant improvements in the cognitive functions of AD patients. Despite the proven effectiveness of cholinesterase inhibitors, an AD carrier, even while being treated, is continually subjected to progressive degeneration of the neuronal tissue. For this reason, other biochemical pathways associated with the pathophysiology of AD have been explored as alternatives to the treatment of this condition such as inhibition of β-secretase and glycogen synthase kinase-3β. The present study aims to conduct a review of the epidemiology, pathophysiology, symptoms, diagnosis and treatment of Alzheimer's disease, emphasizing the research and development of new therapeutic approaches.

The enhancement of cholinergic functions via acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) inhibition is considered a valuable therapeutic strategy for the treatment of Alzheimer’s disease. This study aimed to evaluate the in vitro effect of ZINC390718, previously filtered using computational approaches, on both cholinesterases and to characterize, using a molecular dynamics (MD) simulation, the possible binding mode of this compound inside the cholinesterase enzymes. The in vitro cytotoxicity effect was also investigated using a primary astrocyte-enriched glial cell culture. ZINC390718 presented in vitro dual inhibitory activity against AChE at a high micromolar range (IC₅₀ = 543.8 µM) and against BuChE (IC₅₀ = 241.1 µM) in a concentration-dependent manner, with greater activity against BuChE. The MD simulation revealed that ZINC390718 performed important hydrophobic and H-bond interactions with the catalytic residue sites on both targets. The residues that promoted the hydrophobic interactions and H-bonding in the AChE target were Leu67, Trp86, Phe123, Tyr124, Ser293, Phe295, and Tyr341, and on the BuChE target, they were Asp70, Tyr332, Tyr128, Ile442, Trp82, and Glu197. The cytotoxic effect of Z390718, evaluated via cell viability, showed that the molecule has low in vitro toxicity. The in vitro and in silico results indicate that ZINC390718 can be used as chemotype for the optimization and identification of new dual cholinesterase inhibitors.

The antioxidant activity of molecules constitutes an important factor for the regulation of redox homeostasis and reduction of the oxidative stress. Cells affected by oxidative stress can undergo genetic alteration, causing structural changes and promoting the onset of chronic diseases, such as cancer. We have performed an in silico study to evaluate the antioxidant potential of two molecules of the zinc database: ZINC08706191 (Z91) and ZINC08992920 (Z20). Molecular docking, quantum chemical calculations (HF/6-31G**) and Pearson’s correlation have been performed. Molecular docking results of Z91 and Z20 showed both the lower binding affinity (BA) and inhibition constant (Ki) values for the receptor-ligand interactions in the three tested enzymes (cytochrome P450—CP450, myeloperoxidase—MP and NADPH oxidase—NO) than the control molecules (5-fluorouracil—FLU, melatonin—MEL and dextromethorphan—DEX, for each receptor respectively). Molecular descriptors were correlated with Ki and strong correlations were observed for the CP450, MP and NO receptors. These and other results attest the significant antioxidant ability of Z91 and Z20, that may be indicated for further analyses in relation to the control of oxidative stress and as possible antioxidant agents to be used in the pharmaceutical industry.

Models validation in QSAR, pharmacophore, docking and others can ensure the accuracy and reliability of future predictions in design and selection of molecules with biological activity. In this study, pyriproxyfen was used as a pivot/template to search the database of the Maybridge Database for potential inhibitors of the enzymes acetylcholinesterase and juvenile hormone as well. The initial virtual screening based on the 3D shape resulted in 2000 molecules with Tanimoto index ranging from 0.58 to 0.88. A new reclassification was performed on the overlapping of positive and negative charges, which resulted in 100 molecules with Tanimoto's electrostatic score ranging from 0.627 to 0.87. Using parameters related to absorption, distribution, metabolism and excretion and the pivot molecule, the molecules selected in the previous stage were evaluated regarding these criteria, and 21 were then selected. The pharmacokinetic and toxicological properties were considered and for 12 molecules, the DEREK software not fired any alert of toxicity, which were thus considered satisfactory for prediction of biological activity using the Web server PASS. In the molecular docking with insect acetylcholinesterase, the Maybridge3_002654 molecule had binding affinity of −11.1 kcal/mol, whereas in human acetylcholinesterase, the Maybridge4_001571molecule show in silico affinity of −10.2 kcal/mol, and in the juvenile hormone, the molecule MCULE-8839595892 show in silico affinity value of −11.6 kcal/mol. Subsequent long-trajectory molecular dynamics studies indicated considerable stability of the novel molecules compared to the controls. Communicated by Ramaswamy H. Sarma

The cyclooxygenase-2 receptor is a therapeutic target for planning potential drugs with anti-inflammatory activity. The selective cyclooxygenase-2 (COX-2) inhibitor rofecoxib was selected as a pivot molecule to perform virtual ligand-based screening from six commercial databases. We performed the search for similarly shaped Rapid Overlay of Chemical Structures (ROCS) and electrostatic (EON) compounds. After, we used pharmacokinetic and toxicological parameters to determine the best potential compounds, obtained through the softwares QikProp and Derek, respectively. Then, the compounds proceeded to the molecular anchorage study, which showed promising results of binding affinity with the hCOX-2 receptor: LMQC72 (∆G = −11.0 kcal/mol), LMQC36 (∆G = −10.6 kcal/mol), and LMQC50 (∆G = −10.2 kcal/mol). LMQC72 and LMQC36 showed higher binding affinity compared to rofecoxib (∆G = −10.4 kcal/mol). Finally, molecular dynamics (MD) simulations were used to evaluate the interaction of the compounds with the target hCOX-2 during 150 ns. In all MD simulation trajectories, the ligands remained interacting with the protein until the end of the simulation. The compounds were also complexing with hCOX-2 favorably. The compounds obtained the following affinity energy values: rofecoxib: ΔGbind = −45.31 kcal/mol; LMQC72: ΔGbind = −38.58 kcal/mol; LMQC36: ΔGbind = −36.10 kcal/mol; and LMQC50: ΔGbind = −39.40 kcal/mol. The selected LMQC72, LMQC50, and LMQC36 structures showed satisfactory pharmacokinetic results related to absorption and distribution. The toxicological predictions of these compounds did not display alerts for possible toxic groups and lower risk of cardiotoxicity compared to rofecoxib. Therefore, future in vitro and in vivo studies are needed to confirm the anti-inflammatory potential of the compounds selected here with bioinformatics approaches based on rofecoxib ligand.

Non-steroidal anti-inflammatory drugs are inhibitors of cyclooxygenase-2 (COX-2) that were developed in order to avoid the side effects of non-selective inhibitors of COX-1. Thus, the present study aims to identify new selective chemical entities for the COX-2 enzyme via molecular modeling approaches. The best pharmacophore model was used to identify compounds within the ZINC database. The molecular properties were determined and selected with Pearson’s correlation for the construction of quantitative structure–activity relationship (QSAR) models to predict the biological activities of the compounds obtained with virtual screening. The pharmacokinetic/toxicological profiles of the compounds were determined, as well as the binding modes through molecular docking compared to commercial compounds (rofecoxib and celecoxib). The QSAR analysis showed a fit with R = 0.9617, R² = 0.9250, standard error of estimate (SEE) = 0.2238, and F = 46.2739, with the tetra-parametric regression model. After the analysis, only three promising inhibitors were selected, Z-964, Z-627, and Z-814, with their predicted pIC₅₀ (−log IC₅₀) values, Z-814 = 7.9484, Z-627 = 9.3458, and Z-964 = 9.5272. All candidates inhibitors complied with Lipinski’s rule of five, which predicts a good oral availability and can be used in in vitro and in vivo tests in the zebrafish model in order to confirm the obtained in silico data.