Drug Discovery Tools and In Silico Techniques: A Review

Abstract

Traditional drug discovery methods have proved effective in developing new medications, however the process from leads identification to clinical studies can take over 12 years and cost over $1.8 billion USD on average. To evaluate the safety of drugs, including toxicity and side effects, in vivo and in vitro methods are usually utilized. ADME-Tox evaluations have increased because to recent developments in in vitro models, such as organ-on-chip technology. These techniques are still expensive, tedious and time- intensive, though. In silico techniques have gained popularity for their ability to save time, labor, and costs associated with drug development. Computational approaches have effectively led to the development of several novel drugs. Finally, we provide effective instances of antibacterial, antiviral, and anticancer drug discoveries made utilizing computational approaches. This review outlines the general processes and techniques involved in in silico drug discovery, such as target protein identification, chemical library screening, and machine learning-based toxicity assessment. It also provides an overview of the databases and prediction tools that are currently available.