Toxicological assessment of SGLT2 inhibitors metabolites using in silico approach

Sodium-glucose cotransporter 2 inhibitors (SGLT2i) are the latest class of drugs approved to treat type 2 DM (T2DM). Although adverse effects are often caused by a metabolite rather than the drug itself, only the safety assessment of disproportionate drug metabolites is usually performed, which is of particular concern for drugs of chronic use, such as SGLT2i. Bearing this in mind, in silico tools are efficient strategies to reveal the risk assessment of metabolites, being endorsed by many regulatory agencies. Thereby, the goal of this study was to apply in silico methods to provide the metabolites toxicity assessment of the SGLT2i. Toxicological assessment from SGLT2i metabolites retrieved from the literature was estimated using the structure and/or statistical-based alert implemented in DataWarrior and ADMET predictorTM softwares. The drugs and their metabolites displayed no mutagenic, tumorigenic or cardiotoxic risks. Still, M1-2 and M3-1 were recognized as potential hepatotoxic compounds and M1-2, M1-3, M3-1, M3-2, M3-3 and M4-3, were estimated to have very toxic LD50 values in rats. All SGLT2i and the metabolites M3-4, M4-1 and M4-2, were predicted to have reproductive toxicity. These results support the awareness that metabolites may be potential mediators of drug-induced toxicities of the therapeutic agents.

Discovery of Potential, Non-Toxic Influenza Virus Inhibitor by Computational Techniques

Influenza infection continues to be a major problem in many parts of the world. Rimantadine is a first-line drug used to treat the influenza infection by targeting M2 proton channel. However, S31N mutation in M2 proton channel diminishes the efficiency of rimantadine and creates resistance. To address this issue, the present study was aimed to screen the effective lead candidate against drug resistance strain of influenza from DrugBank database. Initially, the lead molecules were filtered using Lipinski rule of five and the drug likeliness property. Subsequently, the data reduction was carried out by employing molecular docking study. Finally, molecular dynamics simulations techniques were performed to validate the lead compound. Most importantly, the -p LD50 of the screened lead molecule was calculated using CORAL software to estimate the Rat oral toxicity. Accordingly, memantine may possibly become a promising lead compound of rimantadine-resistant influenza virus strain.