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.

This study aimed to evaluate the effect of a methoxylated fraction from Vellozia dasypus Seub on myeloperoxidase (MPO)-chlorinating activity and subsequent in silico assays for binding profile prediction. Therefore, the ethyl acetate extract of aerial parts from Vellozia dasypus Seub was fractionated on open-column chromatography containing SiO₂ and eluted with solvent in crescent polarity to yield a fraction with a mixture of flavonols quercetin 3-O-methyl ether (1) and 6-C-methyl quercetin 3-O-methyl ether (2). Their chemical structures were proposed by HPLC coupled to photodiode array (HPLC-DAD) and mass spectrometer using electrospray ionization multistage analysis (HPLC-MS/MS). The fraction enriched with compounds 1 and 2 inhibited more efficiently the in vitro MPO-chlorinating activity (IC₅₀ = 40 µg/mL) than the ethyl acetate extract (IC₅₀ = 64.0 µg/mL). Molecular docking studies revealed that these compounds interact with MPO active pocket similarly to trifluoromethyl-substituted aromatic hydroxamate, a well-known MPO inhibitor, co-crystallized at the MPO binding site (PDB ID: 4C1M). Molecular dynamics trajectories confirmed that these two molecules interact with the MPO binding site with a similar energetic pattern when compared to the crystallographic ligand. Taken together, these data expand the sources of phenolic natural compounds that may be further investigated against inflammation-related diseases. Communicated by Ramaswamy H. Sarma

Tuberculosis (TB) is an infection caused by Mycobacterium tuberculosis, responsible for 1.5 million documented deaths in 2016. The increase in reported cases of M. tuberculosis resistance to the main drugs show the need for the development of new and efficient drugs for better TB control. Based on these facts, this work aimed to use combined in silico techniques for the discovery of potential inhibitors to β-ketoacyl-ACP synthase (MtKasA). Initially compounds from natural sources present in the ZINC database were selected, then filters were sequentially applied by virtual screening, initially with pharmacophoric modeling, and later the selected compounds (based on QFIT scores) were submitted to the DOCK 6.5 program. After recategorization of the variables (QFIT score and GRID score), compounds ZINC35465970 and ZINC31170017 were selected. These compounds showed great hydrophobic contributions and for each established system 100 ns of molecular dynamics simulations were performed and the binding free energy was calculated. ZINC35465970 demonstrated a greater capacity for the KasA enzyme inhibition, with a ΔG_bind = −30.90 kcal/mol and ZINC31170017 presented a ΔG_bind = −27.49 kcal/mol. These data can be used in other studies that aim at the inhibition of the same biological targets through drugs with a dual action.

Adenosine Receptor Type 2A (A_2AAR) plays a role in important processes, such as anti-inflammatory ones. In this way, the present work aimed to search for compounds by pharmacophore-based virtual screening. The pharmacokinetic/toxicological profiles of the compounds, as well as a robust QSAR, predicted the binding modes via molecular docking. Finally, we used molecular dynamics to investigate the stability of interactions from ligand-A_2AAR. For the search for A_2AAR agonists, the UK-432097 and a set of 20 compounds available in the BindingDB database were studied. These compounds were used to generate pharmacophore models. Molecular properties were used for construction of the QSAR model by multiple linear regression for the prediction of biological activity. The best pharmacophore model was used by searching for commercial compounds in databases and the resulting compounds from the pharmacophore-based virtual screening were applied to the QSAR. Two compounds had promising activity due to their satisfactory pharmacokinetic/toxicological profiles and predictions via QSAR (Diverset 10002403 pEC₅₀ = 7.54407; ZINC04257548 pEC₅₀ = 7.38310). Moreover, they had satisfactory docking and molecular dynamics results compared to those obtained for Regadenoson (Lexiscan^®), used as the positive control. These compounds can be used in biological assays (in vitro and in vivo) in order to confirm the potential activity agonist to A_2AAR.

The dual inhibition of human acetylcholinesterase (hAChE) and butyrylcholinesterase (hBuChE) plays an important role in Alzheimer’s disease treatment. Thus, this study aims identify promising dual inhibitors against hAChE and hBuChE by in silico approaches (pharmacophore-based virtual screening and molecular docking). Ten 3 D pharmacophore models for dual inhibitors using default genetic parameters were built by GALAHAD™ available on SYBYL-X 2.0. Validation steps were carried out according to Energy (0.70), Boltzmann-Enhanced Discrimination of ROC curve (BEDROC >0.50) and structure–activity relationship (SAR) for known inhibitors. The best dual pharmacophore model based on internal/external statistical parameters and SAR data (one hydrogen bond acceptor, two hydrogen bond donors and four hydrophobic centers) was employed in virtual screening at Sigma-Aldrich® subset (n = 214,446) of ZINC database by UNITY module of SYBYL-X 2.0. According to superposition values (QFIT), the best ranked compounds were prioritized for molecular docking and partition coefficient analysis (clog p < 5.0). 37 top-ranked compounds (QFIT > 64.22) from pharmacophore model showed affinity in hAChE (-10.2 < Affinity energy < −6.3 kcal/mol) and hBuChE (-10.9 < Affinity energy < −2.3 kcal/mol) binding sites. Next, liposolubity prediction and commercially available showed that ZINC43198636, ZINC43198637 and ZINC00390718 can be potential dual inhibitors against hAChE and hBuChE. Communicated by Ramaswamy H. Sarma

A set of 23 steroidal 1,2,4,5-tetraoxane analogues were studied using quantum-chemical method (B3LYP/6-31 G*) and multivariate analyses (PCA, HCA, KNN and SIMCA) in order to calculate the properties and correlate them with antimalarial activity (log RA) against Plasmodium falciparum clone D-6 from Sierra Leone. PCA results indicated 99.94% of the total variance and it was possible to divide the compounds into two classes: less and more active. Descriptors responsible for separating were: highest occupied molecular orbital energy (HOMO), bond length (O1-O2), Mulliken electronegativity (χ) and Bond information content (BIC0). We use HCA, KNN and SIMCA to explain relationships between molecular properties and biological activity of a training set and to predict antimalarial activity (log RA) of 13 compounds (#24-36) with unknown biological activity. We apply molecular docking simulations to identify intermolecular interactions with a selected biological target. The results obtained in multivariate analysis aided in the understanding of the activity of the new compound's design (#24-36). Thus, through chemometric analyses and docking molecular study, we propose theoretical synthetic routes for the most promising compounds 28, 30, 32 and 36 that can proceed to synthesis steps and in vitro and in vivo assays.