Investigation of Potential Drug Targets Involved in Inflammation Contributing to Alzheimer's Disease Progression.

Alzheimer's disease has become a major public health issue. While extensive research has been conducted in the last few decades, few drugs have been approved by the FDA to treat Alzheimer's disease. There is still an urgent need for understanding the disease pathogenesis, as well as identifying new drug targets for further drug discovery. Alzheimer's disease is known to arise from a build-up of amyloid beta (Aß) plaques as well as tangles of tau proteins. Along similar lines to Alzheimer's disease, inflammation in the brain is known to stem from the degeneration of tissue and build-up of insoluble materials. A minireview was conducted in this work assessing the genes, proteins, reactions, and pathways that link brain inflammation and Alzheimer's disease. Existing tools in Systems Biology were implemented to build protein interaction networks, mainly for the classical complement pathway and G protein-coupled receptors (GPCRs), to rank the protein targets according to their interactions. The top 10 protein targets were mainly from the classical complement pathway. With the consideration of existing clinical trials and crystal structures, proteins C5AR1 and GARBG1 were identified as the best targets for further drug discovery, through computational approaches like ligand-protein docking techniques.

Investigation of Potential Drug Targets for Cholesterol Regulation to Treat Alzheimer's Disease.

Despite extensive research and seven approved drugs, the complex interplay of genes, proteins, and pathways in Alzheimer's disease remains a challenge. This implies the intricacies of the mechanism for Alzheimer's disease, which involves the interaction of hundreds of genes, proteins, and pathways. While the major hallmarks of Alzheimer's disease are the accumulation of amyloid plaques and tau protein tangles, excessive accumulation of cholesterol is reportedly correlated with Alzheimer's disease patients. In this work, protein-protein interaction analysis was conducted based upon the genes from a clinical database to identify the top protein targets with most data-indicated involvement in Alzheimer's disease, which include ABCA1, CYP46A1, BACE1, TREM2, GSK3B, and SREBP2. The reactions and pathways associated with these genes were thoroughly studied for their roles in regulating brain cholesterol biosynthesis, amyloid beta accumulation, and tau protein tangle formation. Existing clinical trials for each protein target were also investigated. The research indicated that the inhibition of SREBP2, BACE1, or GSK3B is beneficial to reduce cholesterol and amyloid beta accumulation, while the activation of ABCA1, CYP46A1, or TREM2 has similar effects. In this study, Sterol Regulatory Element-Binding Protein 2 (SREBP2) emerged as the primary protein target. SREBP2 serves a pivotal role in maintaining cholesterol balance, acting as a transcription factor that controls the expression of several enzymes pivotal for cholesterol biosynthesis. Novel studies suggest that SREBP2 performs a multifaceted role in Alzheimer's disease. The hyperactivity of SREBP2 may lead to heightened cholesterol biosynthesis, which suggested association with the pathogenesis of Alzheimer's disease. Lowering SREBP2 levels in an Alzheimer's disease mouse model results in reduced production of amyloid-beta, a major contributor to Alzheimer's disease progression. Moreover, its thoroughly analyzed crystal structure allows for computer-aided screening of potential inhibitors; SREBP2 is thus selected as a prospective drug target. While more protein targets can be added onto the list in the future, this work provides an overview of key proteins involved in the regulation of brain cholesterol biosynthesis that may be further investigated for Alzheimer's disease intervention.

Discovery of MurA Inhibitors as Novel Antimicrobials through an Integrated Computational and Experimental Approach.

The bacterial cell wall is essential for protecting bacteria from the surrounding environment and maintaining the integrity of bacteria cells. The MurA enzyme, which is an essential enzyme involved in bacterial cell wall synthesis, could be a good drug target for antibiotics. Although fosfomycin is used clinically as a MurA inhibitor, resistance to this antibiotic is a concern. Here we used molecular docking-based virtual screening approaches to identify potential MurA inhibitors from 1.412 million compounds from three databases. Thirty-three top compounds from virtual screening were experimentally tested in Listeria innocua (Gram-positive bacterium) and Escherichia coli (Gram-negative bacterium). Compound 2-Amino-5-bromobenzimidazole (S17) showed growth inhibition effect in both L. innocua and E. coli, with the same Minimum Inhibitory Concentration (MIC) value of 0.5 mg/mL. Compound 2-[4-(dimethylamino)benzylidene]-n-nitrohydrazinecarboximidamide (C1) had growth inhibition effect only in L. innocua, with a MIC value of 0.5 mg/mL. Two FDA-approved drugs, albendazole (S4) and diflunisal (S8), had a growth inhibition effect only in E. coli, with a MIC value of 0.0625 mg/mL. The identified MurA inhibitors could be potential novel antibiotics. Furthermore, they could be potential fosfomycin substitutes for the fosfomycin-resistant strains.

An Integrated Computational and Experimental Approach to Identifying Inhibitors for SARS-CoV-2 3CL Protease.

The newly evolved SARS-CoV-2 has caused the COVID-19 pandemic, and the SARS-CoV-2 main protease 3CLpro is essential for the rapid replication of the virus. Inhibiting this protease may open an alternative avenue toward therapeutic intervention. In this work, a computational docking approach was developed to identify potential small-molecule inhibitors for SARS-CoV-2 3CLpro. Totally 288 potential hits were identified from a half-million bioactive chemicals via a protein-ligand docking protocol. To further evaluate the docking results, a quantitative structure activity relationship (QSAR) model of 3CLpro inhibitors was developed based on existing small molecule inhibitors of the 3CLproSARS- CoV- 1 and their corresponding IC50 data. The QSAR model assesses the physicochemical properties of identified compounds and estimates their inhibitory effects on 3CLproSARS- CoV- 2. Seventy-one potential inhibitors of 3CLpro were selected through these computational approaches and further evaluated via an enzyme activity assay. The results show that two chemicals, i.e., 5-((1-([1,1'-biphenyl]-4-yl)-2,5-dimethyl-1H-pyrrol-3-yl)methylene)pyrimidine-2,4,6(1H,3H,5H)-trione and N-(4-((3-(4-chlorophenylsulfonamido)quinoxalin-2-yl)amino)phenyl)acetamide, effectively inhibited 3CLpro SARS-CoV-2 with IC50's of 19 ± 3 µM and 38 ± 3 µM, respectively. The compounds contain two basic structures, pyrimidinetrione and quinoxaline, which were newly found in 3CLpro inhibitor structures and are of high interest for lead optimization. The findings from this work, such as 3CLpro inhibitor candidates and the QSAR model, will be helpful to accelerate the discovery of inhibitors for related coronaviruses that may carry proteases with similar structures to SARS-CoV-2 3CLpro.

Synergistic Effect of Chlorogenic Acid and Caffeic Acid with Fosfomycin on Growth Inhibition of a Resistant Listeria monocytogenes Strain.

Listeria monocytogenes, a human foodborne pathogen that causes listeriosis with high-rate mortality, has been reported to be resistant to commonly used antibiotics. New antibiotics or cocktails of existing antibiotics with synergistic compounds are in high demand for treating this multi-drug-resistant pathogen. Fosfomycin is one of the novel and promising therapeutic antibiotics for the treatment of listeriosis. However, some L. monocytogenes strains with the FosX gene were recently reported to survive from the fosfomycin treatment. This work aims to identify FosX inhibitors that can revive fosfomycin in treating resistant L. monocytogenes. Since structures and activities of the FosX protein in L. monocytogenes have been well studied, we used an integrated computational and experimental approach to identify FosX inhibitors that show synergistic effect with fosfomycin in treating resistant L. monocytogenes. Specifically, automated ligand docking was implemented to perform virtual screening of the Indofine natural-product database and FDA-approved drugs to identify potential inhibitors. An in vitro bacterial growth inhibition test was then utilized to verify the effectiveness of identified compounds combined with fosfomycin in inhibiting the resistant L. monocytogenes strains. Two phenolic acids, i.e., caffeic acid and chlorogenic acid, were predicted as high-affinity FosX inhibitors from the ligand-docking platform. Experiments with these compounds indicated that the cocktail of either caffeic acid (1.5 mg/mL) or chlorogenic acid (3 mg/mL) with fosfomycin (50 mg/L) was able to significantly inhibit the growth of the pathogen. The finding of this work implies that the combination of fosfomycin with either caffeic acid or chlorogenic acid is of potential to be used in the clinical treatment of Listeria infections.