COMPUTATIONAL APPROACHES TO PREDICTING DRUG METABOLISM

Abstract

One of the most important factors to be examined and improved in drug discovery initiatives is metabolism. It is crucial to identify metabolically unstable substances or possible inhibitors of crucial enzymes as soon as feasible. Strong computational techniques are required because there are more compounds being synthesized than can be studied experimentally. Goal: We provide a summary of the most recent in-silico techniques for forecasting experimental metabolic endpoints, emphasizing their suitability for the pharmaceutical sector. The metabolic fate and interaction with metabolizing enzymes are shown both macroscopically and microscopically. Methods: Approaches based on ligands, proteins, and rules are discussed. Conclusion: Despite significant advancements, the computations' outcomes still require close examination. It is necessary to consider both the models' domain of applicability and methodological constraints.