Background: Absorption, Distribution, Metabolism, Excretion (ADME) properties along with drug induced
adverse effects are the major reasons for the late stage failure of drug candidates as well as the cause for the
expensive withdrawal of many approved drugs from the market. Considering the adverse effects of drugs, metabolism
factor has great importance in medicinal chemistry and clinical pharmacology because it influences the deactivation,
activation, detoxification and toxification of drugs.
Methods: Computational methods are effective approaches to reduce the number of safety issues by analyzing possible
links between chemical structures and metabolism followed by adverse effects, as they serve the integration of
information on several levels to enhance the reliability of outcomes.
Results and Discussion: In silico profiling of drug metabolism can help progress only those molecules along the
discovery chain that is less likely to fail later in the drug discovery process. This positively impacts the very high
costs of drug discovery and development. Understanding the science behind computational tools, their opportunities,
and limitations is essential to make a true influence on drug discovery at different levels. If applied in a scientifically
consequential way, computational tools may improve the capability to identify and evaluate potential drug molecules
considering pharmacokinetic properties of drugs.
Conclusion: Herein, current trends in computational modeling for predicting drug metabolism are reviewed highlighting
new computational tools for drug metabolism prediction followed by reporting large and integrated databases
of approved drugs associated with diverse metabolism issues.