Modern Methods & Web Resources in Drug Design & Discovery

Author(s): Feroz Khan, Dharmendra Kumar Yadav, Anupam Maurya, Santosh Kumar Srivastava

Journal Name: Letters in Drug Design & Discovery

Volume 8 , Issue 5 , 2011

Become EABM
Become Reviewer
Call for Editor


Traditionally, the process of drug development has revolved around a screening approach and trial-and-error method, as no body knew which compound or approach could serve as a drug or therapy. This discovery process was very time consuming and laborious and discovery of a new drug used to take around 8-14 years and costs about US $1.8 billion. In order to minimize the time and cost in this drug discovery process, scientists around the world contributed tremendously and come up with a modern drug-designing program. The beauty of this modern drug designing is that now we can tailor the drug with desired combinations computationally before going for experimental laboratory work. In this review, traditional to modern methods of drug designing & discovery have been discussed. It covers the available web tools/databases and in silico techniques used in virtual screening and drug discovery processes to reduce the wet lab economy and time. Studies suggest that the best method for molecular docking based target identification is probably a hybrid of various types of algorithm encompassing novel search and scoring strategies e.g., PMF score, Dock score, Gold score etc. However, apart from in vitro assays and in vivo experiments, application of in silico QSAR & ADMET in the prediction of biological activity & bioavailability are proving beneficial in drug discovery process.

Keywords: Drug design, Drug discovery, QSAR, Lead identification, Lead optimization, Target identification, Web Resources, Cannabis sativa, Papaver somniferum, Nicotiana tabacum, bioassays, in silico, ADMET, Cancer, pharmacophores

Rights & PermissionsPrintExport Cite as

Article Details

Year: 2011
Page: [469 - 490]
Pages: 22
DOI: 10.2174/157018011795514249
Price: $65

Article Metrics

PDF: 10