Development of Potential Multi-Target Inhibitors for Human Cholinesterases and Beta-Secretase 1: A Computational Approach

Alzheimer’s disease causes chronic neurodegeneration and is the leading cause of dementia in the world. The causes of this disease are not fully understood but seem to involve two essential cerebral pathways: cholinergic and amyloid. The simultaneous inhibition of AChE, BuChE, and BACE-1, essential enzymes involved in those pathways, is a promising therapeutic approach to treat the symptoms and, hopefully, also halt the disease progression. This study sought to identify triple enzymatic inhibitors based on stereo-electronic requirements deduced from molecular modeling of AChE, BuChE, and BACE-1 active sites. A pharmacophore model was built, displaying four hydrophobic centers, three hydrogen bond acceptors, and one positively charged nitrogen, and used to prioritize molecules found in virtual libraries. Compounds showing adequate overlapping rates with the pharmacophore were subjected to molecular docking against the three enzymes and those with an adequate docking score (n = 12) were evaluated for physicochemical and toxicological parameters and commercial availability. The structure exhibiting the greatest inhibitory potential against all three enzymes was subjected to molecular dynamics simulations (100 ns) to assess the stability of the inhibitor-enzyme systems. The results of this in silico approach indicate ZINC1733 can be a potential multi-target inhibitor of AChE, BuChE, and BACE-1, and future enzymatic assays are planned to validate those results.PPBE and PPGCF/UEFS; Fundação de Amparo à Pesquisa do Estado de Minas Gerais—FAPEMIG, grants APQ-02741-17, APQ-00855-19, APQ-01733-21, and APQ-04559-22Conselho Nacional de Desenvolvimento Científico e Tecnológico—CNPq-Brazil, grants 305117/2017-3, 426261/2018-6Fellowship of 2021 (grant 310108/2020-9

A review on mycogenic metallic nanoparticles and their potential role as antioxidant, antibiofilm and quorum quenching agents

The emergence of antimicrobial resistance among biofilm forming pathogens aimed to search for the efficient and novel alternative strategies. Metallic nanoparticles have drawn a considerable attention because of their significant applications in various fields. Numerous methods are developed for the generation of these nanoparticles however, mycogenic (fungal-mediated) synthesis is attractive due to high yields, easier handling, eco-friendly and being energy efficient when compared with conventional physico-chemical methods. Moreover, mycogenic synthesis provides fungal derived biomolecules that coat the nanoparticles thus improving their stability. The process of mycogenic synthesis can be extracellular or intracellular depending on the fungal genera used and various factors such as temperature, pH, biomass concentration and cultivation time may influence the synthesis process. This review focuses on the synthesis of metallic nanoparticles by using fungal mycelium, mechanism of synthesis, factors affecting the mycosynthesis and also describes their potential applications as antioxidants and antibiofilm agents. Moreover, the utilization of mycogenic nanoparticles as quorum quenching agent in hampering the bacterial cell-cell communication (quorum sensing) has also been discussed

Identification of New Rofecoxib-Based Cyclooxygenase-2 Inhibitors: A Bioinformatics Approach

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

Galantamine Based Novel Acetylcholinesterase Enzyme Inhibitors: A Molecular Modeling Design Approach

Acetylcholinesterase (AChE) enzymes play an essential role in the development of Alzheimer’s disease (AD). Its excessive activity causes several neuronal problems, particularly psychopathies and neuronal cell death. A bioactive pose on the hAChE B site of the human acetylcholinesterase (hAChE) enzyme employed in this investigation, which was obtained from the Protein Data Bank (PDB ID 4EY6), allowed for the prediction of the binding affinity and free binding energy between the protein and the ligand. Virtual screening was performed to obtain structures similar to Galantamine (GNT) with potential hAChE activity. The top 200 hit compounds were prioritized through the use of filters in ZincPharmer, with special features related to the pharmacophore. Critical analyses were carried out, such as hierarchical clustering analysis (HCA), ADME/Tox predictions, molecular docking, molecular simulation studies, synthetic accessibility (SA), lipophilicity, water solubility, and hot spots to confirm the stable binding of the two promising molecules (ZINC16951574-LMQC2, and ZINC08342556-LMQC5). The metabolism prediction, with metabolites M3-2, which is formed by Glutathionation reaction (Phase II), M1-2, and M2-2 formed from the reaction of S-oxidation and Aliphatic hydroxylation (Phase I), were both reactive but with no side effects. Theoretical synthetic routes and prediction of synthetic accessibility for the most promising compounds are also proposed. In conclusion, this study shows that in silico modeling can be used to create new drug candidate inhibitors for hAChE. The compounds ZINC16951574-LMQC2, and ZINC08342556-LMQC5 are particularly promising for oral administration because they have a favorable drug-likeness profile, excellent lipid solubility, high bioavailability, and adequate pharmacokinetics

Structure-based drug design for protein arginine deiminase Type IV (PAD4) receptor: Chemoinformatics approach

Rheumatoid Arthritis (RA) is the second most common type of arthritis with symptoms first appearing in patients between 40 and 60 years of age. The number of older persons is projected to double to 1.5 billion in 2050, globally. Peptidylarginine deiminase Type 4 (PAD4), which catalyzes the conversion of peptidyl-arginine to peptidyl-citrulline, is widely believed to play a causative role in RA disease. Nonsteroidal anti-inflammatories (NSAIDs) and corticosteroids encompass a large group of clinically effective compounds whose mode of action is well established, these compounds relieve pain and reduce inflammation by preventing prostaglandin synthesis through inhibition of cyclooxygenase 2 and the production of arachidonic acid, respectively. We developed a computational protocol/pipeline, using virtual screening approaches to search for new chemical agents (NCA), capable of inhibiting the action of PAD4, in potential, in view of the treatment of RA. Our results allowed the selection of structures with suitable indices of pharmacokinetic properties and estimated low toxicological, in potential, important evidence for selection of more promising molecular candidates against the studied disease. Molecules ZINC20452582 and ZINC67673633 presented better results, as well as the drug-receptor interactions were similar to those observed between the crystallographic compound (GSK147) here used. They presented excellent results for predictions of metabolites, and they can be indicated as promising molecules, resulting from virtual screening approaches, as new PAD4 receptor inhibitors with activity against RA, in potential

Rational Approach toward COVID-19’s Main Protease Inhibitors: A Hierarchical Biochemoinformatics Analysis

This study investigated the potential of selected compounds as inhibitors of SARS-CoV-2 Mpro through pharmacokinetic and toxicological analyses, molecular docking, and molecular dynamics simulations. In silico molecular docking simulations revealed promising ligands with favorable binding affinities for Mpro, ranging from −6.2 to −9.5 kcal/mol. Moreover, molecular dynamics simulations demonstrated the stability of protein–ligand complexes over 200 ns, maintaining protein secondary structures. MM-PBSA analysis revealed favorable interactions between ligands and Mpro, with negative binding energy values. Hydrogen bond formation capacity during molecular dynamics was confirmed, indicating consistent interactions with Mpro catalytic residues. Based on these findings, selected ligands show promise for future studies in developing COVID-19 treatments

Identification of Potential COX-2 Inhibitors for the Treatment of Inflammatory Diseases Using Molecular Modeling Approaches

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.Ye