Rational Drug Design (Molecular Modelling-Computational Chemistry)

Traditional drug discovery and development is well known to be time consuming and cost-intensive encompassing an average of 10 to 15 years until it is ready to reach the market with an estimated cost of 58.8 billion USD as of 2015 . These numbers are a dramatic 10% increase from previous years for both biotechnology and pharmaceutical companies. Of the library of 10,000 screened chemical compounds, only 250 or so will move on to further clinical testings. In addition, those that are tested in humans typically do not exceed more than 10 compounds. Furthermore, from a study conducted during 1995 to 2007 by the Tufts Center for the Study of Drug Development revealed that out of all the drugs that make it to Phase I of clinical trials, only 11.83% were eventually approved for market . In addition, during 2006 to 2015, the success rate of those drugs undergoing clinical trials was only 9.6% . The exacerbated cost and high failure rate of this traditional path of drug discovery and development has prompted the need for the use of computer-aided drug discovery (CADD) which encompasses ligand-based, structure-based and systems-based drug design . Moreover, the major side effects of drugs resulting in severe toxicity evokes the screening of ADMET (adsorption, distribution, metabolism, excretion and toxicity) properties at the early stage of drug development in order to increase the success rate as well as reduce time in screening candidates. . In particular, the typical role of CADD is to screen compounds against the target of interest thereby narrowing the candidates to a few smaller clusters to acquire compounds with good binding affinity to the target which are identified as hits and could be further developed as lead compounds .