Finding Lead Compounds for Dengue Antivirals from a Collection of Old Drugs through In Silico Target Prediction and Subsequent In Vitro Validation.

Dengue virus (DENV) infection is one of the most widely spread flavivirus infections. Despite the fatality it could cause, no antiviral treatment is currently available to treat the disease. Hence, this study aimed to repurpose old drugs as novel DENV NS3 inhibitors. Ligand-based (L-B) and proteochemometric (PCM) prediction models were built using 62,354 bioactivity data to screen for potential NS3 inhibitors. Selected drugs were then subjected to the foci forming unit reduction assay (FFURA) and protease inhibition assay. Finally, molecular docking was performed to validate these results. The in silico studies revealed that both models performed well in the internal and external validations. However, the L-B model showed better accuracy in the external validation in terms of its sensitivity (0.671). In the in vitro validation, all drugs (zileuton, trimethadione, and linalool) were able to moderately inhibit the viral activities at the highest concentration tested. Zileuton showed comparable results with linalool when tested at 2 mM against the DENV NS3 protease, with a reduction of protease activity at 17.89 and 18.42%, respectively. Two new compounds were also proposed through the combination of the selected drugs, which are ziltri (zilueton + trimethadione) and zilool (zileuton + linalool). The molecular docking study confirms the in vitro observations where all drugs and proposed compounds were able to achieve binding affinity ≥ -4.1 kcal/mol, with ziltri showing the highest affinity at -7.7 kcal/mol, surpassing the control, panduratin A. The occupation of both S1 and S2 subpockets of NS2B-NS3 may be essential and a reason for the lower binding energy shown by the proposed compounds compared to the screened drugs. Based on the results, this study provided five potential new lead compounds (ziltri, zilool, zileuton, linalool, and trimethadione) for DENV that could be modified further.

In silico toxicity studies of traditional Chinese herbal medicine: A mini review.

With the availability of public databases that store compound-target/compound-toxicity information, and Traditional Chinese medicine (TCM) databases, in silico approaches are used in toxicity studies of TCM herbal medicine. Here, three in silico approaches for toxicity studies were reviewed, which include machine learning, network toxicology and molecular docking. For each method, its application and implementation e.g., single classifier vs. multiple classifier, single compound vs. multiple compounds, validation vs. screening, were explored. While these methods provide data-driven toxicity prediction that is validated in vitro and/or in vivo, it is still limited to single compound analysis. In addition, these methods are limited to several types of toxicity, with hepatotoxicity being the most dominant. Future studies involving the testing of combination of compounds on the front end i.e., to generate data for in silico modeling, and back end i.e., validate findings from prediction models will advance the in silico toxicity modeling of TCM compounds.

Structure-Activity Relationship Analysis of Flavonoids and Its Inhibitory Activity Against BACE1 Enzyme Toward a Better Therapy for Alzheimer's Disease.

Drug development in Alzheimer's disease (AD) suffers from a high attrition rate. In 2021, 117 agents tested in phases I and II and 36 agents tested in phase III were discontinued. Natural product compounds may be good lead compounds for AD as they contain functional groups that are important for binding against key AD targets such as ß-secretase enzyme (BACE1). Hence, in this study, 64 flavonoids collected from rigorous literature search and screening that have been tested from 2010 to 2022 against BACE1, which interferes in the formation of amyloid plaque, were analyzed. The 64 unique flavonoids can be further classified into five core fragments. The flavonoids were subjected to clustering analysis based on its structure, and each representative of the clusters was subjected to molecular docking. There were 12 clusters formed, where only 1 cluster contained compounds from two different core fragments. Several observations can be made where 1) flavanones with sugar moieties showed higher inhibitory activity compared to flavanones without sugar moieties. The number of sugar moieties and position of glycosidic linkage may also affect the inhibitory activity. 2) Non-piperazine-substituted chalcones when substituted with functional groups with decreasing electronegativity at the para position of both rings result in a decrease in inhibitory activity. Molecular docking indicates that ring A is involved in hydrogen bond, whereas ring B is involved in van der Waals interaction with BACE1. 3) Hydrogen bond is an important interaction with the catalytic sites of BACE1, which are Asp32 and Asp228. As flavonoids contain favorable structures and properties, this makes them an interesting lead compound for BACE1. However, to date, no flavonoids have made it through clinical trials. Hence, these findings may aid in the design of highly potent and specific BACE1 inhibitors, which could delay the progression of AD.