Abstract
The field of drug research, guided by chemistry, pharmacology, and clinical sciences, has been a major contributor in progressing and development of medicine during the past century. The arrival of molecular biology and genomic sciences has had a profound effect in this field. The process of drug discovery and development are both very laborious and time-consuming. Consequently, application of computational resources to chemical and biological space for streamlining the process is under extensive research. In order to escalate the processes of hit identification, lead selection and optimization, analysis of ADMET (absorption, distribution, metabolism, excretion and toxicity) profile for lead compound, computer-aided, or in silico drug discovery is employed. Bioinformatics tools along with genomic sciences have provided insight into the genetic basis of multifactorial diseases, thereby revealing more suitable targets for designing future medicines and increasing therapeutic options. This chapter explains the computer-aided drug discovery protocols classified on the basis of availability of information for the target in question.
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Goyal, S., Jamal, S., Grover, A., Shanker, A. (2018). Drug Discovery: An In Silico Approach. In: Shanker, A. (eds) Bioinformatics: Sequences, Structures, Phylogeny . Springer, Singapore. https://doi.org/10.1007/978-981-13-1562-6_14
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