Abstract：
Prolonged antibiotic therapy for the bacterial infections has resulted in high levels of antibiotic resistance. Initially, bacteria are susceptible to the antibiotics, but can gradually develop resistance. Treating such drug-resistant bacteria remains difficult or even impossible. Hence, there is a need to develop effective drugs against bacterial pathogens. The drug discovery process is time-consuming, expensive and laborious. The traditionally available drug discovery process initiates with the identification of target as well as the most promising drug molecule, followed by the optimization of this, in-vitro, in-vivo and in pre-clinical studies to decide whether the compound has the potential to be developed as a drug molecule. Drug discovery, drug development and commercialization are complicated processes. To overcome some of these problems, there are many computational tools available for new drug discovery, which could be cost effective and less time-consuming. In-silico approaches can reduce the number of potential compounds from hundreds of thousands to the tens of thousands which could be studied for drug discovery and this results in savings of time, money and human resources. Our review is on the various computational methods employed in new drug discovery processes.
摘要：
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