Vol. 6, Issue 5 (2017)
A review: Recent computational approaches in medicinal chemistry: Computer aided drug designing and delivery
Dr. Sushil Kumar Sharma, Dr. Ekta Sharma and Yatendra Sharma
Traditional medicinal chemistry paradigms, relying initially on ‘wet’ chemistry followed by screening and lead optimizations, are expensive and time consuming. On the other hand, initial in silico screening that guides the synthesis and screening of selected compounds has proven to be a better approach to accelerate drug discovery and reduce the cost of the discovery phase. The Special Focus issue on computational chemistry and computer-aided drug discovery has aimed to assemble contributions covering a wide range of computational approaches with special relevance for medicinal chemistry and drug discovery, including new methodologies and practical applications. In addition, this Special Focus issue has been thought to provide a forum for critical – or even provocative – contributions, given the generally high degree of scientific heterogeneity that characterizes the publication landscape of computational medicinal chemistry. Moreover, prospective applications of computational approaches, established or new, have been most welcome, for example, investigations attempting to identify or design new active compounds. Such prospective applications often provide a good impression of the practical utility and impact computational methods may – or may not – have on experimental programs, which is a critical issue for medicinal chemistry. The aim of this special issue is to give an overview of and highlight the latest achievements in various computational approaches at a point in time when the field is experiencing tremendous algorithmic advancements in terms of speed and accuracy, with a constant enthusiasm and excitement to meet up the experiments.
How to cite this article:
Dr. Sushil Kumar Sharma, Dr. Ekta Sharma and Yatendra Sharma. A review: Recent computational approaches in medicinal chemistry: Computer aided drug designing and delivery. 2017; 6(5): 05-10.