01556nas a2200253   4500000000100000008004100001260001500042653003300057653003100090653002600121653002400147653002200171100001700193700001700210700001500227700001700242700001400259245005100273856007200324300001100396490000800407520087300415022001401288       2021                            d  c2021-10-0110aComputational drug discovery10aComputer-aided drug design10aTarget identification10aToxicity prediction10aVirtual screening1 aBilal Shaker1 aSajjad Ahmad1 aJingyu Lee1 aChanjin Jung1 aDokyun Na00aIn silico methods and tools for drug discovery  uhttps://www.sciencedirect.com/science/article/pii/S0010482521006454  a1048510 v1373 aIn the past, conventional drug discovery strategies have been successfully employed to develop new drugs, but the process from lead identification to clinical trials takes more than 12 years and costs approximately $1.8 billion USD on average. Recently, in silico approaches have been attracting considerable interest because of their potential to accelerate drug discovery in terms of time, labor, and costs. Many new drug compounds have been successfully developed using computational methods. In this review, we briefly introduce computational drug discovery strategies and outline up-to-date tools to perform the strategies as well as available knowledge bases for those who develop their own computational models. Finally, we introduce successful examples of anti-bacterial, anti-viral, and anti-cancer drug discoveries that were made using computational methods.  a0010-4825